ISSN 2188-5001
MATERIALS DESIGN AND
CHARACTERIZATION LABORATORYSUPERCOMPUTER CENTERACTIVITY REPORT

2020

THE UNIVERSITY OF TOKYOMaterials Design and Characterization Laboratory (MDCL)
The MDCL was established as the third research facility of the Institute for Solid
State Physics (ISSP) when the latter was reorganized in May 1996. Its aim is to promotematerial science with an emphasis on the “DSC cycle”, where DSC stands for design,synthesis and characterization, three processes for developing new materials.
The MDCL consists of two sections, Materials Design (MD) section and Materials
Synthesis and Characterization (MSC) section. The Supercomputer Center of the ISSP
(SCC-ISSP) is placed in the MD section, while in the MSC section there are seven laboratories for joint use; Materials Synthesis Laboratory, Chemical Analysis Laboratory, X-ray
Diﬀraction Laboratory, Electron Microscope Laboratory, Electromagnetic Measurement
Laboratory, Spectroscopy Laboratory, and High-Pressure Synthesis Laboratory.
Almost all the facilities of the MDCL are open to scientists in Japan through theUser Programs conducted by two steering committees of the MDCL. One is the steeringcommittee of the SCC-ISSP, under which the Supercomputer Project Advisory Committee
is placed for reviewing proposals. The other is the steering committee of the MSC facilities.
More than half of the members of these committees are from the outside of ISSP.

COVER FIGURE
Karman Vortex with cavilation
See Y. Asano et al. Page 36–46, ”Large-Scale Molecular Dynamics Simulations of Karman
Vortex and Sound Wave: Cavitation and Polymer Eﬀects”.

iiActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

PREFACEThe Supercomputer Center (SCC) is a part of the Materials Design and Characterization
Laboratory (MDCL) of ISSP. Its mission is to serve the whole community of computationalcondensed-matter physics of Japan providing it with high performance computing environment.
In particular, the SCC selectively promotes and supports large-scale computations. For thispurpose, the SCC invites proposals for supercomputer-aided research projects and hosts theSteering Committee, as mentioned below, that evaluates the proposals.
The ISSP supercomputer system consists of two subsystems: System B, which was replaced
recently (Oct. 2020), is intended for larger total computational power and has more nodes withrelatively loose connections. System B (ohtaka) consists of 1680 CPU nodes of AMD EPYC
7702 (64 cores) and 8 FAT nodes of Intel Xeon Platinum 8280 (28 cores) with total theoretical
performance of 6.881 PFlops. System C (enaga, installed in Jan. 2018) consists of 252 nodes of
HPE SGI 8600 with 0.77 PFLOPS. Replacement of the System C is scheduled in Spring 2022.
In addition to the hardware administration, the SCC puts increasing effort on the software
support. Since 2015, the SCC has been conducting “Project for advancement of software
usability in materials science (PASUMS).”In this project, for enhancing the usability of the
ISSP supercomputer system, we conduct several software-advancement activities: developing
new application software that runs efficiently on the ISSP supercomputer system, adding new
functions to existing codes, help releasing private codes for public use, creating/improving
manuals for public codes, etc. Three target programs were selected in fiscal year 2020 anddeveloped or enhanced the ustablity of software were released as (1) PHYSBO (proposal madeby R. Tamura (NIMS)), (2) 2DMAT (proposal made by T. Hoshi (Tottori Univ.)), and (3)MateriApps Installer (proposal made by S. Todo (Univ. of Tokyo)). In 2021, we also started thedata repository service.
All staff members of university faculties or public research institutes in Japan are invited topropose research projects (called User Program). The proposals are evaluated by the Steering
Committee of SCC. Pre-reviewing is done by the Supercomputer Project Advisory Committee.
In fiscal year 2020, totally 387 projects were approved. The total points applied and approved
are listed on Table. 1 below. Additionally, we supported FUGAKU and other computational
materials science projects through Supercomputing Consortium for Computational Materials
Science (SCCMS).
The research projects are roughly classified into the following three (the number of projects
approved):
First-Principles Calculation of Materials Properties (189)Strongly Correlated Quantum Systems (40)
Cooperative Phenomena in Complex, Macroscopic Systems (137)In all the three categories, most proposals involve both methodology and applications. The
results of the projects are reported in 'Activity Report 2020' of the SCC. Every year 3-4 projects
are selected for “invited papers” and published at the beginning of the Activity Report. In the
Activity Report 2020, the following three invited papers are included:"Some Recent Developments in ab initio Thermodynamics of Ion Disorder in Solids",
Shusuke KASAMATSU (Yamagata Univ.)iii

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo"High precision study of the Anderson transition”,
Tomi OHTSUKI (Sophia Univ.) and Keith SLEVIN (Osaka Univ.)"Large-Scale Molecular Dynamics Simulations of Karman Vortex and Sound Wave: Cavitation
and Polymer Effects",
Yuta ASANO (ISSP), Hiroshi WATANABE (Keio Univ.) and Hiroshi NOGUCHI (ISSP)
June 1, 2021
Naoki Kawashima(Chairman of the steering committee, SCC, ISSP)

iv

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

CONTENTSPREFACE
1 OUTLINE1

1.1 Supercomputer System
1.2 Project Proposals
1.3 Committees
1.4 Staﬀ

1
1
4
7

2 STATISTICS (SCHOOL YEAR 2020)
2.1 System and User Statistics
2.2 Queue and Job Statistics
2.3 Project for Advancement of Software Usability
in Materials Science
3 RESEARCH REPORTS

8
8
8
9
15

3.1 Invited Articles
3.2 First-Principles Calculation of Material Properties
3.3 Strongly Correlated Quantum Systems
3.4 Cooperative Phenomena in Complex Macroscopic
Systems
3.5 SCCMS Projects
3.6 Software Advancement Projects
and Workshop Support
4 PUBLICATION LIST

15
47
183
220
326
342

349

ISSP Joint Research Projects
SCCMS Projects
Doctor Theses
Master Theses

350
405
412
414

v

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1

OUTLINE

1.1

Supercomputer System

At the beginning of School Year 2020 (SY2020), the ISSP supercomputer center
provided users with two supercomputer systems: SGI ICE XA/UV hybrid system
named “sekirei” (System B) and HPE SGI 8600 system named “enaga” (System
C). In Oct. 2020, Systems B was replaced by Dell PowerEdge C6525/R940 system
named “ohtaka”, and this system will be called System B for the next six years.
System B is a massively-parallel supercomputer with two types of compute nodes:
8 “Fat” nodes and 1680 “CPU” nodes. “Fat” nodes are each comprised of fourIntel Xeon Platinum 8280 CPUs (28 cores/CPU) and 3 TB of memory per node.
“CPU” nodes have two AMD EPYC 7702 CPUs (64 cores/CPU) and 256 GB ofmemory per node. System B achieves about 6.881 PFLOPS in theoretical peak
performance with high power eﬃciency. The subsystem comprised of only CPU
nodes ranks 87st in the Nov. 2020 Top 500 List, which is a ranking based on total
performance measured by the HPL benchmark. The compute nodes communicate
to each other through HDR100 Inﬁniband and are connected in fat tree topology.
System B entered oﬃcial operation on Oct. 16th, 2020. Trial operation of System
B continued until Nov. 26th, 2020. 2020 was the ﬁrst year of the operation of thecurrent System B. System C is a massively-parallel supercomputer with 252 “CPU”
nodes, which have two Intel Xeon Gold 6148 CPUs (20 cores/CPU) and 192 GB ofmemory. System C achieves 774 TFLOPS in theoretical peak performance. 2020
was the third year of the operation of the current System C. For further details,
please contact ISSP Supercomputer Center (SCC-ISSP).
[Correspondence: center@issp.u-tokyo.ac.jp]

1.2

Project Proposals

The ISSP supercomputer system provides computation resources for scientists
working on condensed matter sciences in Japan. All scientiﬁc staﬀ members (including post-docs) at universities or public research institutes in Japan can submit
proposals for projects related to research activities on materials and condensed
matter sciences. These proposals are peer-reviewed by the Advisory Committee
members (see Sec. 1.3), and then the computation resources are allocated basedon the review reports. The leader of an approved project can set up user accounts
for collaborators. Other types of scientists, including graduate students, may also
be added. Proposal submissions, peer-review processes, and user registration are
all managed via a web system.
The computation resources are distributed in a unit called “point”, determined
as a function of available CPU utilization time and consumed disk resources. There
were calls for six classes of research projects in SY 2020. The number of projects
and the total number of points that were applied for and approved in this school
year are listed in Table 1.

1

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 1: Classes of research projects in SY 2020

Class

A
B
C
D
E
S
SCCMS
Total

Class

A
B
C
D
E
S
SCCMS
Total

Maximum
PointsSys–B Sys–C
100
50
500
100
5k
1k
10k
1k
15k
3k
–
–

Maximum
PointsSys–B Sys–C
100
50
1k
100
8k
1k
10k
1k
25k
3k
–
–

First semester (Apr.-Sep.)
Application # ofTotal points
Proj.
AppliedApproved
Sys–B Sys–C Sys–B Sys–C
any time
8
0.8k
0.4k
0.8k
0.4k
twice a year
61
28.4k
4.0k
22.8k
3.9k
twice a year
115 446.5k
80.1k 239.8k 42.4k
any time
3
22.5k
2.0k
15.0k
2.0k
twice a year
9 127.4k
27.0k
88.5k 21.4k
twice a year
0
0
0
0
0
11
23.7k
4.6k
23.7k
4.6k
207 649.3k 118.0k 390.6k 74.6k

Second semester (Oct.-Mar.)
Application # ofTotal points
Proj.
AppliedApproved
Sys–B Sys–C Sys–B Sys–C
1.0k
0.4k
any time
10
1.0k
0.4k
twice a year
57
46.6k
3.2k
22.0k
2.0k
twice a year
96 595.8k
59.0k 226.0k 22.3k
any time
00000
twice a year
7 175.0k
18.0k
87.0k
8.4k
twice a year
0
0
0
0
0
10
50.0k
4.5k
50.0k
4.5k
180 868.3k
85.0k 386.0k 37.5k

2

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

System B, Ohtaka
6.881 PFLOPS
memoryr : 420 TB
ry
storage : 2.3 PB

System C, Enaga
0.774 PFLOPS
memorymemoryry :: 47.25
ry
47.25 TB
TB
storagestorage :: 0.5
0.5 PBPB

Figure 1: Supercomputer System at the SCC-ISSP• Class A is for trial use by new users; proposals for Class A projects are
accepted throughout the year.
• Proposals for projects in Classes B (small), C (mid-size), E (large-scale), andS (exceptional) can be submitted twice a year. Approved projects in Classes
A, B, C, and E continue to the end of the school year.
• In Class D, projects can be proposed on rapidly-developing studies that needto perform urgent and relatively large calculations. An approved projectcontinues for 6 months from its approval.
• Class S is for projects that are considered extremely important for the fieldof condensed matter physics and requires extremely large-scale computation.
The project may be carried out either by one research group or cooperatively
by several investigators at different institutions. A project of this class should
be applied with at least 10,000 points; there is no maximum. We requiregroup leaders applying for Class S to give a presentation on the proposal to
the Steering Committee of the SCC-ISSP. Class S projects are carried out
within one year from its approval.
• Project leaders can apply for points so that the points for each system do
not exceed the maximum point shown in this table.
In addition, from SY 2016, ISSP Supercomputer has been providing 20% of
its computational resources for Supercomputing Consortium for Computational
Materials Science (SCCMS), which aims at advancing parallel computations incondensed matter, molecular, and materials sciences on the 10-PFlops K Computer3

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyoand the exascale post-K project. From SY 2020, about 10% of the computational
resources have been provided for SCCMS. Computational resources have also beenallotted to Computational Materials Design (CMD) workshops, as well as CCMS
hands-on workshops.

1.3

Committees

In order to fairly manage the projects and to smoothly determine the system
operation policies, the Materials Design and Characterization Laboratory (MDCL)of the ISSP has organized the Steering Committee of the MDCL and the Steering
Committee of the SCC-ISSP, under which the Supercomputer Project Advisory
Committee (SPAC) is formed to review proposals. The members of the committees
in SY 2020 were as follows:

Steering Committee of the MDCLKAWASHIMA, Naoki
HIROI, Zenji
OZAKI, Taisuke
NOGUCHI, Hiroshi
UWATOKO, Yoshiya
SUGINO, Osamu
KUBO, Momoji
ONO, Tomoya
YAMAURA, Jun-ichi
TAKAHASHI, Hiroki
MOTOME, Yukitoshi
HOSHI, Takeo
KIMURA, Kaoru
HASEGAWA, Masashi
NAKATSUJI, Satoru

ISSP (Chair person)
ISSP
ISSP
ISSP
ISSP
ISSP
Tohoku Univ.
Kobe Univ.
Tokyo Tech.
Nihon Univ.
Univ. of Tokyo
Tottori Univ.
Univ. of Tokyo
Nagoya Univ.
ISSP

Steering Committee of the SCC-ISSP
KAWASHIMA, Naoki
NOGUCHI, Hiroshi
OZAKI, Taisuke
SUGINO, Osamu
TSUNETSUGU, Hirokazu
KATO, Takeo
YAMASHITA, Minoru
MORITA, Satoshi
HIGUCHI, Yuji
FUKUDA, Masahiro
IDO, Kota

ISSP (Chair person)
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP

4

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoKAWAMURA, Mitsuaki
NAKAJIMA, Kengo
HATANO, Naomichi
MOTOME, Yukitoshi
ONO, Tomoya
TODO, Synge
KUBO, Momoji
OBA, Fumiyasu
WATANABE, Hiroshi
YOSHINO, Hajime
OKUMURA, Hisashi
HOSHI, Takeo
YOSHIMI, Kazuyoshi
YATA, Hiroyuki
FUKUDA, Takaki

ISSP
Univ. of Tokyo
Univ. of Tokyo
Univ. of Tokyo
Kobe Univ.
Univ. of Tokyo
Tohoku Univ.
Tokyo Tech.
Keio Univ.
Osaka Univ.
NINS-RSCS
Tottori Univ.
ISSP
ISSP
ISSP

Supercomputer Project Advisory Committee
KAWASHIMA, Naoki
NOGUCHI, Hiroshi
OZAKI, Taisuke
SUGINO, Osamu
TSUNETSUGU, Hirokazu
KATO, Takeo
YAMASHITA, Minoru
MORITA, Satoshi
HIGUCHI, Yuji
FUKUDA, Masahiro
IDO, Kota
KAWAMURA, Mitsuaki
NAKAJIMA, Kengo
HATANO, Naomichi
MOTOME, Yukitoshi
ONO, Tomoya
TODO, Synge
KUBO, Momoji
OBA, Fumiyasu
WATANABE, Hiroshi
YOSHINO, Hajime
OKUMURA, Hisashi
HOSHI, Takeo
TSUNEYUKI, Shinji
SUZUKI, Takafumi
YOSHIMOTO, Yoshihide
TOHYAMA, Takami

ISSP (Chair person)
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
Univ. of Tokyo
Univ. of Tokyo
Univ. of Tokyo
Univ. of Tsukuba
Univ. of Tokyo
Tohoku Univ.
Tokyo Tech.
Keio Univ.
Osaka Univ.
NINS-RSCS
Tottori Univ.
Univ. of Tokyo
Univ. of Hyogo
Univ. of Tokyo
Tokyo Univ. of Sci.

5

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoKITAO, Akio
ARITA, Ryotaro
IKUHARA, Yuichi
SHIBATA, Naokazu
AKAGI, Kazuto
YANASE, Yoichi
HATSUGAI, Yasuhiro
OKADA, Susumu
KOBAYASHI, Nobuhiko
NAKAYAMA, Takashi
HOTTA, Takashi
MATSUKAWA, Hiroshi
YAMAUCHI, Jun
HAGITA, Katsumi
KONTANI, Hiroshi
SAITO, Mineo
KAWAKAMI, Norio
YUKAWA, Satoshi
SUGA, Seiichiro
TATENO, Masaru
YASUDA, Chitoshi
OGATA, Masao
WATANABE, Satoshi
HUKUSHIMA, Koji
NEMOTO, Koji
YABANA, Kazuhiro
FURUKAWA, Nobuo
KUROKI, Kazuhiko
YASUOKA, Kenji
TANAKA, Yukio
MASUBUCHI, Yuichi
KUSAKABE, Koichi
SHIRAI, Koun
SAKAI, Toru
ISHIBASHI, ShojiOTANI, Minoru
TOMITA, Yusuke
MIYASHITA, Seiji
SHIRAISHI, Kenji
OGUCHI, Tamio
KAWAKATSU, Toshihiro
KOBAYASHI, Kazuaki
TATEYAMA, Yoshitaka
KIM, KangOTSUKI, Tomi

Tokyo Tech.
Univ. of Tokyo
Univ. of Tokyo
Tohoku Univ.
Tohoku Univ.
Kyoto Univ.
Univ. of Tsukuba
Univ. of Tsukuba
Univ. of Tsukuba
Chiba Univ.
Tokyo Metropolitan Univ.
Aoyama Gakuin Univ.
Keio Univ.
National Defense Academy
Nagoya Univ.
Kanazawa Univ.
Kyoto Univ.
Osaka Univ.
Univ. of Hyogo
Univ. of Hyogo
Univ. of the Ryukyus
Univ. of Tokyo
Univ. of Tokyo
Univ. of Tokyo
Hokkaido Univ.
Univ. of Tsukuba
Aoyama Gakuin Univ.
Osaka Univ.
Keio Univ.
Nagoya Univ.
Nagoya Univ.
Osaka Univ.
Osaka Univ.
Univ. of Hyogo
AIST
AIST
Shibaura Inst. Tech.
JPS
Nagoya Univ.
Osaka Univ.
Tohoku Univ.
NIMS
NIMS
Osaka Univ.
Sophia Univ.

6

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoMORIKAWA, Yoshitada
ODA, Tatsuki
OTSUKI, Junya
KOGA, Akihisa
SHIMOJO, Fuyuki
TAKETSUGU, Tetsuya
TSURUTA, Kenji
HAMAGUCHI, Satoshi
NISHIDATE, Kazume
KAGESHIMA, Hiroyuki
SATO, Tetsuya
ISHII, Fumiyuki
TATETSU, Yasutomi
YANAGISAWA, Susumu
SHUDO, Ken-ichi
OHMURA, Satoshi
NOGUCHI, Yoshifumi
NAKAMURA, Kazuma
GOHDA, Yoshihiro
HAMADA, Ikutaro
RAEBIGER, Hannes
TADA, Tomofumi

1.4

Osaka Univ.
Kanazawa Univ.
Okayama Univ.
Tokyo Tech.
Kumamoto Univ.
Hokkaido Univ.
Okayama Univ.
Osaka Univ.
Iwate Univ.
Shimane Univ.
Keio Univ.
Kanazawa Univ.
Meio Univ.
Univ. of the Ryukyus
Yokohama Natl. Univ.
Hiroshima Inst. Tech.
Shizuoka Univ.
Kyushu Inst. Tech.
Tokyo Tech.
Osaka Univ.
Yokohama Natl. Univ.
Tokyo Tech.

Staﬀ

The following staﬀ members of the SCC-ISSP usually administrate the ISSP Supercomputer.
KAWASHIMA, Naoki
NOGUCHI, Hiroshi
OZAKI, Taisuke
SUGINO, Osamu
IDO, Kota
FUKUDA, Masahiro
HIGUCHI, Yuji
KAWAMURA, Mitsuaki
MORITA, Satoshi
YOSHIMI, Kazuyoshi
MOTOYAMA, Yuichi
YATA, Hiroyuki
FUKUDA, Takaki
ARAKI, Shigeyuki

Professor (Chair person)
Associate Professor
Professor
Professor
Research Associate
Research Associate
Research Associate
Research Associate
Research Associate
Project Researcher
Project Researcher
Technical Associate
Technical Associate
Technical Associate

7Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

2

STATISTICS (SCHOOL YEAR 2020)

2.1

System and User Statistics

In the following, we present statistics for operation time taken in the period from
April 2020 to March 2021 (SY 2020). In Table 2, we show general statistics ofthe supercomputer system in SY 2020. The total numbers of compute nodes in
System B “sekirei”, System B “ohtaka” and System C “enaga” are 1891, 1688 and252, respectively. Consumed disk points amount to about a few percent of thetotal consumed points in both System B and System C.
Table 2: Overall statistics of SY 2020
System B
System B
System C
sekireiohtakaenaga(Apr.–Jun.) (Oct.-Mar.) (Apr.–Mar.)3
total service time (×10 node·hours)
4060
7252
1734
number of executed jobs
179504
19148382484
3
total consumed points (×10 point)
164
188
55
CPU points (×103 point)
158
185
54
3
disk points (×10 point)
6
4
2
total exec. time (×103 node·hours)
3626
5935
1454
availability
98.29 %
98.37%
94.59%
utilization rate
89.31 %
80.43%
83.40%In Fig. 2, availabilities, utilization rates, and consumed points in Systems B
and C are plotted for each month. Throughout the school year, the availability
and the utilization rates were very high, while these were reduced from July to
October due to the replacement of System B and the construction of the watercooling equipment.
The user statistics are shown in Fig. 3. The horizontal axis shows the rank of theuser/group arranged in the descending order of the execution time (hour×nodes).
The execution time of the user/group of the ﬁrst rank is the longest. The verticalaxis shows the sum of the execution time up to the rank. From the saturation
points of the graphs, the numbers of “active” users of Systems B and C are around
200 and 150, respectively. The maximum ranks in the graphs correspond to thenumber of the users/groups that submitted at least one job.

2.2

Queue and Job Statistics

Queue structures of Systems B and C in SY2020 are shown in Tables 3 and 4,
respectively. In System B “ohtaka”(“sekirei”), users can choose from two (three)types of compute nodes; jobs submitted to queues with “cpu” and “fat” (“cpu”,“acc”, and “fat”) at the end of their queue names are submitted to CPU and8

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Fat nodes (CPU, ACC, and Fat nodes), respectively, while only CPU nodes areavailable in System C “enaga”. See Sec. 1.1 for a description of each type ofcompute node. The user then has to choose the queue according to the numberof nodes to use and the duration of their calculation jobs. Queue names startingwith “F” are for jobs taking 24 hours or less, while those starting with “L” canrun much longer up to 120 hours. More nodes are allotted to “F” queues in orderto maximize the turnaround time of user jobs. The queue names starting with“i” are used for interactive debugging of user programs and the elapsed time limit
is 30 minutes. The number following “F”, “L”, or “i” correspond to the numberof nodes that can be used by one user job. Although we do not mention here indetail, to promote utilization of the massively parallel supercomputer, backgroundqueues (queue name starting with “B”) for Systems B and C which charge nopoints for the jobs have also been open.
To prevent overuse of the storage, points are charged also for usage of disk
quota in the three systems, as shown in Table 5. Disk points are revised often for
optimal usage of the resources by examining usage tendencies each year.
The number of jobs, average waiting time, and total execution time in eachqueue are shown in Tables 6 and 7. In System B, a large portion of jobs havebeen executed in “F” queues. The largest amount of the execution time has
been consumed in the large-scale “F144cpu” and “F72cpu” queues for sekirei andohtaka, respectively. However, substantial number of jobs were run in every queue,
suggesting that a wide variety of user needs are met by this queuing scheme. In
most of these queues, the queue settings meet the user’s tendencies in that thewaiting times are on the order of the elapsed-time limit.

2.3

Project for Advancement of Software Usability in Materials Science

From School Year 2015, the supercomputer center (SCC) has started “Project
for advancement of software usability in materials science”. In this project, forenhancing the usability of the supercomputer system in ISSP, we perform some
software-advancement activity such as implementing a new function to an existing
code, releasing a private code on Web, writing manuals. Target programs are
publicly oﬀered in December and selected in the review by the Steering Committeeof SCC. The projects are carried out by the software development team composedof three members in ISSP. In SY 2020, three projects were selected as listed inTable 8.

Acknowledgments
The staﬀs would like to thank Prof. Takafumi Suzuki (now at University of Hyogo)
for developing WWW-based system (SCM: SuperComputer Management System)
for management of project proposals, peer-review reports by the SPAC committee,
and user accounts. We also thank Ms. Reiko Iwafune for creating and maintaining
a new WWW page of the ISSP Supercomputer Center.

9

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

System B

System C

Figure 2: Availabilities, utilization rates and point consumptions of each month
during SY 2020.

System B, sekirei

System B, ohtaka

System C, enaga

Figure 3: User statistics. The horizontal axis shows the rank of the user/grouparranged in the descending order of the execution time (hour×nodes). The verticalaxis shows the sum of the execution time up to the rank.

10Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 3: Queue structures of System B in SY 2020
System B, sekirei
Memoryjob points
queue
Elapsed time # of nodes # of nodes
namelimit (hr)/job/queuelimit (GB)/(node·day)
F4cpu
24
1–4
216
120/node
1
L4cpu
120
1–4
108
120/node
1
24
5–36
288
120/node
1
F36cpuL36cpu120
5–36
144
120/node
1
F144cpu24
37–1441008
120/node 72(144)/(# of nodes)∗L144cpu120
37–144144
120/node 72(144)/(# of nodes)∗i18cpu0.5
1–18
72
120/node1
F18acc24
1–18
180120/node2
L18acc120
1–18
90120/node
2
i9acc
0.5
1–9
36
120/node
2
F2fat
24
1–2
17
1000/node
4
L2fat
120
1–2
6
1000/node
4
i1fat
0.5
1
2
1000/node
4∗

For F/L144cpu queue, the number of occupied node increases in increments of 72
nodes.

System B, ohtaka
queue
Elapsed time # of nodes # of nodes
Memorynamelimit (hr)/job/queuelimit (GB)
F1cpu
24
1
600
230/node
L1cpu
120
1
300
230/node
F4cpu
24
2–4
216
230/node
L4cpu
120
2–4
108
230/node
F16cpu24
5–16
288
230/node
L16cpu120
5–16
144
230/node
F36cpu24
17–36
72
230/node
L36cpu120
17–36
36
230/node
F72cpu24
72
576
230/node
L72cpu120
72
288
230/node
F144cpu
24
144
432
230/node
L144cpu
120
144
144
230/node
i8cpu
0.5
1–8
72
230/node
F2fat
24
1–2
7
2900/node
L2fat
120
1–2
3
2900/node
i1fat
0.5
1
1
2900/node11

job points/(node·day)
1
1
1
1
1
1
1
1
1
1
1
1
1
4
4
4

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 4: Queue structures of System C in SY 2020
System C, enaga
Memoryqueue Elapsed time # of nodes # of nodes
namelimit (hr)/job/queuelimit (GB)
F4cpu
24
1–4
54
170/node
L4cpu
120
1–4
18
170/node
1–4
18
170/node
i4cpu
0.5
F9cpu
24
5–9
36
170/node
L9cpu
120
5–9
18
170/node
F36cpu24
10–36
144
170/node
L36cpu120
10–36
36
170/node∗

job points/(node·day)
1
1
1
1
1
18(36)/(# of nodes)∗18(36)/(# of nodes)∗For F/L36cpu queue, the number of occupied node increases in increments of 18 nodes.

Table 5: Disk points of Systems B and C

System B sekirei

/home
/work
System B ohtaka /home/work
System C enaga /home
/work
∗
∗

point/day
0.001 × θ(q − 300)
0.0001 × θ(q − 3000)
0.001 × θ(q − 600)
0.0001 × θ(q − 6000)
0.001 × θ(q − 150)
0.0001 × θ(q − 1500)

q is denoted in unit of GB.
θ(x) is equal to the Heaviside step function H(x) multiplied by x, i.e., xH(x).

12Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 6: Number of jobs, average waiting time, total execution time, and average
number of used nodes per job in each queue of System B.

queue
F4cpu
L4cpu
F36cpuL36cpuF144cpu
L144cpu
i18cpuF18acc
L18acc
i9acc
F2fat
L2fat
i1fat

queue
F1cpu
L1cpu
F4cpu
L4cpu
F16cpuL16cpuF36cpuL36cpuF72cpuL72cpuF144cpu
L144cpu
i8cpu
F2fat
L2fat
i1fat

# of Jobs
58198
2563
4617
720
2434
59
16181
28444
1334
458
1667
417
492

# of Jobs
79020
3130
39592
2325
8550
1041
715
46
3215
80
1236
47
36070
4476
268
400

System B, sekirei
Waiting Time
Exec. Time # of nodes(hour) (×103 node·hour)
6.68
305.491.35
27.32
147.351.52
18.02
332.16
10.87
43.54
210.528.52
27.52
1799.18
95.31
131.70234.02106.17
0.32
21.10
8.61
3.36
245.80
3.23
7.72
85.87
1.83
3.40
0.06
0.13
11.92
15.90
1.33
23.29
7.78
1.09
0.03
0.09
1.00
System B, ohtaka
Waiting Time
Exec. Time # of nodes
3(hour) (×10 node·hour)
25.58
156.191.00
80.84
100.341.00
14.36
557.682.58
24.48
183.462.84
33.61
607.919.72
87.90
422.01
10.46
84.88
174.38
26.47
94.17
37.22
24.78
17.44
1782.87
72.00
49.64
190.6972.00
27.96
1156.23144.00169.13325.44144.00
0.12
22.44
3.63
1.05
8.87
13.11
22.37
5.54
1.03
0.47
0.05
1.00

13

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 7: Number of jobs, average waiting time, total execution time, and average
number of used nodes per job in each queue of System C.
System C, enaga
queue# of Jobs Waiting Time
Exec. Time # of nodes(hour) (×103 node·hour)
F4cpu
44830
9.74
221.91
1.31
L4cpu
1620
46.22
86.90
1.70
i4cpu
13624
0.13
3.15
2.26
F9cpu
4688
23.12
113.76
6.32
L9cpu
249
45.02
55.75
6.92
F36cpu4203
19.08
643.7322.76
L36cpu145
148.48162.7029.30

Table 8: List of Project for advancement of software usability in materials science
for SY 2020.
Project Proposer
Ryo Tamura
NIMS
Synge Todo
The University of Tokyo
Takeo Hoshi
Tottori University

Project Name
Bayesian optimization library COMBO
MateriApps Installer- Installation Tool for Open-source Software
Advancement of the experimental data analysis
for 2D material structure

14

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3
3.1

RESEARCH REPORTS
Invited Articles

Some Recent Developments in ab initio Thermodynamics
of Ion Disorder in Solids

16

Shusuke KASAMATSU

High Precision Study of the Anderson Transition

27

Tomi OHTSUKI and Keith SLEVIN

Large-Scale Molecular Dynamics Simulations of Karman Vortex
and Sound Wave: Cavitation and Polymer Eﬀects
Yuta ASANO, Hiroshi WATANABE, and Hiroshi NOGUCHI

15

36

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Some Recent Developments in ab initio Thermodynamics ofIon Disorder in Solids
Shusuke KASAMATSU
Academic Assembly (Faculty of Science), Yamagata University
Kojirakawa, Yamagata-shi, Yamagata, JAPAN 990-8560

Abstract
Configurational disorder of ions in solids often
play key roles in determining the properties offunctional materials. A natural way to obtain thermodynamically relevant structures from the combinatorially increasing number of configurations in
multicomponent systems is to combine computational statistical physics methods such as Metropolis sampling with ab initio methods. Since ab initio methods incur high computational costs, theusual approach is to fit ab inito datasets to lowcost models such as cluster expansion, then use
those models for sampling. However, obtaining reliable low-cost models for complex oxide systems
have turned out to be challenging. To circumvent
this problem, we have recently been examining
the feasibility of direct sampling on ab initio energies, as well as turning to more flexible neural network models as an alternative to cluster expansion.
Here, we review some of our recent works in thisdirection; we also introduce our open source code
abICS, which is designed to harness the computational capacity of modern supercomputers to perform configurational sampling on complex multicomponent systems.

1

perature and chemical potentials. Such disorderoften plays significant roles in determining materials properties, and many materials in e.g., battery or magnet applications utilize impurities tocause disorder on purpose so as to obtain desirable
properties. Thus, the ability to simulate such disorder as a function of temperature should be immensely helpful for prediction and design of properties in materials with realistic levels of disorder.
To achieve this, it is necessary to perform sufficient thermodynamic sampling based on statistical mechanics. First-principles molecular dynamics is the method of choice for sampling quicklyrelaxing (e.g., liquid) systems, but it is nearly useless for sampling solid state systems with very
high energy barriers between different configurations. On the other hand, Monte Carlo methods
are not limited by realistic relaxation time scales
since they can employ “unphysical” trial steps suchas swapping of atom positions. However, standard Metropolis Monte Carlo sampling can still get
trapped in local minima, and it is usually not efficient enough to allow for a direct combination with
first-principles calculations. Thus, many workers
have opted to first derive lightweight models fromfirst-principles calculations, then use those models
for Monte Carlo sampling.

Introduction

Functional materials for various applications including energy conversion, nanoelectronics devices, and structural materials exhibit varying levels of configurational disorder which depend on
the details of materials processing including tem-

For modeling of systems that can be mapped
to a lattice (i.e., crystalline systems with configurational disorder), the cluster expansion approach
has seen much success [1–8]. This method expands the total energy in terms of “clusters” of16

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 1: Clusters within the conventional BCC
cell. From Chang et al. [8] (Creative Commons
Attribution License 3.0, https://doi.org/10.
1088/1361-648X/ab1bbc).
atoms (Fig. 1):
E(~
σ) =

X

mα Vα Φα (~
σ),

(1)

α

where α denotes empty, single, and multicomponent clusters, mα is the cluster multiplicity,~ is the occupation vector. Φα is the clusterand σbasis function, which for a binary system takes thesimple form of
Y
Φα (~
σ) =
σp,
(2)
p∈α

where p are site indices and σ p = ±1 dependingon which component occupies site p. Vα is the effective cluster interaction (ECI), which represents
the contribution of each cluster to the total energy.
This model reduces to the classical Ising model
when considering only nearest neighbor pair clusters. The ECIs are usually obtained by fitting to energies of relaxed structures from many small-scale
first-principles density functional theory (DFT)
calculations, then used to perform Monte Carlosampling on a larger cell.
The efficiency of the cluster expansion approach
depends on the ability to quantitatively reproduce
configuration energies using as few clusters (andcorresponding ECIs) as possible. This is rarely
an issue for simple two-component metallic alloys
where considering only near-neighbor interactions

often leads to sufficient accuracy. However, complex systems such as multicomponent oxides often
require many clusters due to longer range coulombinteractions as well as complicated strain patterns.
In addition to this, increasing the number of components (i.e., ion types) leads to a combinatorial increase in the number of clusters which makes cluster expansion computationally unfeasible. Anotherissue that has been recognized when using cluster
expansion is that surface calculations require many
more clusters than bulk calculations for sufficientaccuracy [9].
There are two possible ways to tackle the above
issue. One approach is to bypass the use of models and sample directly on first-principles energies. Although this approach is computationallyexpensive as mentioned above, the use of parallel sampling algorithms combined with modernday supercomputers have made it just barely feasible in recent years. Another approach is to utilize recently-developed machine-learning models
which is expected to be more flexible than the cluster expansion model. We have been working on
both fronts; we will review some of the literature aswell as our recent developments on the former approach in Sec. 2 and the latter approach in Sec. 3.
A software framework that incorporates these developments, which we have named ab Initio Configuration Sampling Toolkit, or abICS for short, isintroduced in Sec. 5.

2

Directcouplingoffirstprinciples calculations withreplica exchange sampling [10]There have already been some reports of firstprinciples Monte Carlo simulation in the literature, but they were limited to relatively simple
and quickly relaxing systems where first-principles
molecular dynamics may be just as efficient [11,12]. The issue, as noted above, is the tendency
to get stuck in local minima, especially at low
temperatures. One may think that with the increase in computer power available to researchers
today, simply performing many Metropolis sam-17

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

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0&VDPSOLQJFRQWUROʞOn the other hand, we have been working extensively on combining first-principles calculation
with another popular extended ensemble method,i.e., the replica exchange Monte Carlo (RXMC)
method [17]. This approach considers an ensemble of Nrep replicas of a given system at Nrep different temperatures. Each replica is simulated in
the canonical ensemble, so the low temperature
replicas would still have the minima trapping issue. However, the problem is alleviated by allowing swaps of temperatures between replicas according to the following Metropolis criterion for

0&VDPSOLQJFRQWURO

6WUXFWXUHʞThis is where the so-called extended ensemble
sampling comes to the rescue. Using histogram
reweighting [13], it is possible, in theory, to convert between arbitrary ensembles. Thus, we are notlimited to sampling in a single canonical ensemble
at a given temperature, and this allows for choosing ensembles that can avoid the minima trapping
issue. For example, one can choose to sample
an ensemble where each configuration is realizedwith probabilities proportional to the inverse of thedensity of states. This is the idea behind multicanonical [14] and Wang-Landau [15] methods. In
fact, the Wang-Landau method was recently usedsuccessfully in combination with order-N firstprinciples Korringa-Kohn-Rostoker approach (albeit without structural relaxation) to calculate theorder-disorder transition in a 250-atom CuZn supercell [16].

0&VDPSOLQJFRQWUROʞpling calculations in parallel would lead to a sufficient number of samples for obtaining statistically
relevant results. However, such embarrassingly
parallel sampling is useless if each parallel image
cannot achieve equilibrium. The reason for getting trapped in local minima is that the Metropolis algorithm samples the canonical ensemble; agiven configuration is sampled with a probability
proportional to exp(−βE), where β is the inverse
temperature and E is the energy of the configuration. Thus, configurations residing at or near energy barriers on the potential energy surface will
rarely be accepted and the difficulty to cross suchenergy barriers increases exponentially with βE.

6WUXFWXUH')7 9$63

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Figure 2: Schematic of our scheme for coupling
the RXMC method with DFT codes. Reproduced
from Ref. [10]the ensemble of Nrep replicas:
P = min{1, exp[(βi − β j )(Ei − E j )]}.

(3)

Here, i and j are the indices of the replicas attempting the swap, and βi( j) and Ei( j) are the inverse temperatures and energies of each replica. According to this criterion, a replica with lower energy
will be assigned progressively lower energies, andvice versa. Essentially, a high-temperature replica
is given the task of a global scan of configuration
space; when it finds a new local minimum, it will
be assigned a lower temperature and will perform amore careful search within the newly found energy
basin. In this manner, the RXMC method provides
a good balance between global search and local optimization. At the same time, the canonical ensembles are easily recovered by collecting the replicas
at each temperature.
Figure 2 shows our computational scheme.
There are Nrep Metropolis samplers running at different temperatures; the samplers are coded using python and parallelized using mpi4py [18–20].
At each Metropolis step, each sampler performs aswap between atoms of different types (possibly
including vacancies), prepares input files for the
specified DFT code, and spawns parallel DFT processes using MPI-2 dynamic process management,i.e., the MPI COMM SPAWN function. The DFT

18

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 3: Comparison of the degree of inversion
as a function of temperature calculated by CESPCM (Seko et al. [21]; circles), the present approach (randomly initialized: squares; initializedwith an ordered spinel structure: triangles andexperimental neutron diffraction data [22]). The
spinel structure is shown in the inset. Reproduced
from Ref. [10] with addition of neutron diffraction
data.
processes perform local structural relaxation andenergy calculation, then the results are read automatically by the sampler to determine whether
to accept or reject the new configuration. The
samplers also attempt temperature swaps between
replicas at preset intervals according to Eq. 3. This
multilayered parallelism over replicas and DFT
processes makes it ideal for harnessing the powerof modern-day parallel supercomputers.
As a first benchmark for testing the feasibilityof this approach, we chose to calculate the degree of cation disorder in MgAl2 O4 spinel oxide[10]. Spinel oxides have a general formula ofA(II)B(III)2 O3 with A (B) representing a divalent(trivalent) cation, and are of interest in magnetic(spintronic) and electronic applications as well as
mineralogy. The structure is shown in Fig. 3. Usually, the divalent cation occupies the tetrahedral
sites and the trivalent cation occupies the octahedral sites. However, some inversion between thesites can occur, and some A(II)–B(III) combinations are known to exhibit completely inverse ordering, where all trivalent cations occupy the oc-

tahedral sites. The degree of inversion (DOI) is
quantified by the ratio of divalent cations at octahedral sites. Seko and coworkers have performed
calculations of the DOI in several spinels using
cluster expansion [4, 21], and we took their resultfor MgAl2 O4 as reference. We employed a calculation supercell containing 16 Mg, 32 Al, and64 O atoms, and sampled the configuration of Mg
and Al on the cation sublattice. No disorder on
the O sublattice was considered. We performed
two separate RXMC runs to check for convergenceand initial configuration dependence; one run was
initialized with random configurations and anotherwas initialized from the ordered spinel configuration. We used 16 replicas spaced evenly between
600 and 1500 K and performed 16750 steps forthe randomly initialized run and 13000 steps forthe run initialized from the ordered configuration.
This amounts to roughly 4000 node hours for eachrun on System C (enaga) at ISSP which has two
Xeon Gold 6148 processors per node. Figure 3
compares the calculated DOI vs. temperature forthe two runs as well as that obtained by a cluster
expansion model augmented by a screened point
charge model. We find the results to be virtually
identical, showing that sufficient sampling steps
were performed and it is indeed feasible to perform such calculations on meaningfully large supercells without resorting to fitted models. Moreover, the RXMC calculation initialized in the random configuration discovered the ground state ordered spinel configuration within 300 steps. We
think this is rather impressive considering that
there are 48 C16 = 2254848913647 possible configurations, and attests to the efficiency of the RXMC
method not only as a sampler but also as an optimizer. We also note that the deviation from experiment at lower temperature is seen in both our calculation and Seko’s. This is most likely due to thelow mobility of cations at low temperature which
inhibits the equilibration in the experiment.

19

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 4: The structure of the HDNNP. The
atomic coordinates are converted to a rotationallyand translationally invariant environment descriptor before feeding in to the neural network.

3

Accelerated sampling utilizing aneural network model combinedwith active learning [23]Although direct sampling using DFT-relaxed energies was shown to be feasible as detailed above,
the amount of required computer resources is quite
large, taking several days to a week to sample justone composition on a modern supercomputer. A
much higher throughput is necessary to enable materials design based on such simulations. Also,
because of the computational cost of DFT calculations, it is not feasible to go beyond a systemsize of about one hundred atoms and perform sufficient numbers of sampling steps. This is a problem when treating systems with, e.g., dilute doping
or long correlation lengths. To provide the necessary acceleration, we have no choice at this point
but to go back to lightweight models. However,as mentioned above, the de facto standard cluster
expansion approach has difficulty handling complex multicomponent systems that are of interestfor various applications.
To overcome this issue, we turned to the highdimensional neural network potential (HDNNP)
approach pioneered by Behler and Parinello [24,25]. This approach relies on the ansatz that the total energy can be expressed as a sum of atomic en-ergies determined by the environment around each
atom and uses a a feed-forward neural network to
represent those atomic energies (Fig. 4). The network weights are trained to reproduce DFT energies and forces (i.e., energy derivatives). Acceleration by 2–4 orders of magnitude compared to
DFT has been achieved while maintaining similarlevels of accuracy.
The HDNNP approach was developed for accelerating molecular dynamics simulations. There,
it is necessary to accurately reproduce the energy
and forces in continuous coordinate space. Thisis overkill when considering the lattice configuration problem; we only need to map the ideal lattice
structure with configurational disorder to the energy after local relaxation. Thus, we proposed totrain the HDNNP model to predict the relaxed energies from the set of atom coordinates and atom
species on the ideal lattice [23]. The new ansatz
here is that the total energy of a relaxed configuration can be expressed as a sum of atomic energies determined from atom environment descriptors calculated on the ideal lattice before relaxation. This may be expressed as follows:
Erel (
σ) =

atoms

i

 ∈ {
NNPrelσRi c ]) for σσlattice },ti ( f [(4) represents the coordinates of all atoms in
where σthe system, which is restricted, in our scheme, tothose on the ideal lattice. i represents atom in Ri cdices, ti is the corresponding atom type, and σrepresents the configuration of atoms within a cutoff radius from atom i. A separate neural net NNPti
is trained for each atom type; it takes as input
a rotationally and translationally invariant fingerprint of the atomic environment f [σRi c ] and outputs the contribution of the atom i to the relaxedtotal energy. In this work, we employed the Chebychev fingerprint proposed by Artrith and coworkers [26]. In this fingerprinting scheme, Chebychev expansion coefficients of the radial and angular distribution functions are used as the fingerprint. The atom type is encoded by multiplying with type-dependent factors when calculating
the radial/angular distributions. We use ænet code20

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo(http://ann.atomistic.net/) for the training
and evaluation of the neural network model.
An issue with neural network approaches ingeneral is that they are good at interpolating between training data but not at extrapolating. To
overcome this problem, we adopted the so-called“active learning” approach, where the neural network is retrained on-the-fly when the simulation
wanders into regions of structure space that were
not included in the original training data set [27–35]. Our approach is summarized as follows:
1. Prepare a training set consisting of DFTrelaxed energies of randomly generated configurations.
2. Perform neural network training.
3. Perform RXMC sampling using the trainedneural network model.
4. Perform DFT relaxations on a subset of configurations that appeared during RXMC sampling and check the prediction accuracy. If
sufficient accuracy is achieved, stop here.
5. If the accuracy is found to be insufficient, add
those configurations to the training set and repeat from step 2.
We benchmarked this approach, again, on the temperature dependence of the DOI in MgAl2 O4 . We
used a supercell with 192 cation sites compared to
48 in the previous section. The supercell size combined with the explosion of the possible number ofconfigurations (192 C64 ∼ 1051 ) makes this calculation completely out of reach for direct sampling on
DFT energies.
Figure 5 shows the correlation plot between theneural network predictions vs. reference DFT energies. The model trained on randomly generated
configurations performs well in the high energy region but shows a sizable deviation at lower energies. This is because the lower energy structureswith more ordering were obviously not included in
the original training data set. In our active learning scheme, these structures are then added to the

Figure 5: The correlation between reference DFT
energies and neural network predictions whentraining was performed on randomly generated
configurations (closed circles) and after performing active learning (open squares).
training set and the model is retrained. The resulting correlation after active learning is nearly perfect with deviations of less than a few meV/atom.
The active-learned neural network model was used
to sample the DOI vs. temperature (Fig. 6) from
480,000 RXMC steps with 15 replicas, and good
agreement was obtained with cluster expansion
and direct sampling on DFT energies explained in
the previous section.

4

Applications

We have only just started to apply the thermodynamic sampling methods outlined in previous sections to complex oxide systems that were difficult
to treat using previously available methods. Here,
we briefly present some results obtained for a couple of systems of interest in solid state ionics andelectrochemistry.

Acceptor-doped BaZrO3
Ceramic-based electrolytes are under intense research for application in battery, fuel cell, andelectrolyzer applications. Recently, we have been
focusing on acceptor-doped BaZrO3 , which is
known as a promising material to be used as the21Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 6: Comparison of the DOI calculated using
cluster expansion (blue circles), direct samplingon DFT energies (orange triangles), and the neural network model (open green squares) compared
to experiment (red triangles).
proton conducting electrolyte in solid oxide fuelcells. The material is an insulator without doping,but oxygen vacancies with an effective charge of+2 can be induced by substituting Zr4+ by trivalent
acceptor cations such as Y3+ . This is expressed inKröger-Vink notation as follows:
2Zr×Zr + O×O + Y2 O3 → 2Y0Zr + V••
O + 2ZrO2 . (5)These oxygen vacancies are immobile in the temperature range of interest, but highly mobile protons can be induced by a hydration reaction withthese vacancies:×•
H2 O + V••
O + OO → 2(OHO ).

(6)

The maximum dopant concentration can reach up
to 60% depending on the dopant species [36] (although it may be questionable whether it is appropriate to refer to such high concentrations as “doping”). Conventionally, dopants were assumed to
distribute randomly on the Zr sites. On the other
hand, some recent works have pointed out thatthe configuration of dopants can impact the proton
mobility in both positive and negative ways [37–39]. For example, an isolated dopant or a cluster of
dopants can act as a trapping site for protons due
to coulomb attraction. On the other hand, dopants
may form a long-range percolating pathway along

which protons can diffuse relatively freely. Thus,
we performed RXMC sampling combined directlywith DFT for revealing what the realistic dopant
configurations will be under processing conditions
in Y-doped BaZrO3 with dopant concentration up
to 30%. We note that many works have discussed
the interaction between few dopants and O vacancies or protons, but none have treated such highly
doped systems rigorously within a statistical thermodynamics framework like ours. Our approachrevealed that the dopant configurations are far fromrandom even at the usual sintering temperature of∼ 1800 K. This originates from complex manybody interactions that cannot be explained simply
in terms of coulomb interactions between charged
defects. Detailed analysis based on the statistics
obtained from RXMC samples can be found in
Ref. [40]. We also fed the obtained configurations into a master equation model for proton diffusion [41] and found that the realistic dopant configurations obtained by RXMC sampling predicts
slightly higher conductivities compared to random
configurations [42]. Another insight obtained thereis that in general, the formation of deep trappingsites due to dopant clustering has much more profound effect than the formation of a percolating
pathway. Thus, avoiding dopant clustering would
be the route to higher conductivity in this system.
We are now performing the active learning NNRXMC approach of Sec. 3 to understand the hydration behavior and the recently reported highconductivity of 0.01 S/cm at 400 ◦ C in 60% Scdoped BaZrO3 [36]. Prior to this report, Y dopingof ∼ 20% was reported to result in the highest proton conductivity using BaZrO3 as the parent material. An issue was that further doping results inthe decline of proton conductivity, which was also
reproduced by our work mentioned above [42]. In
the case of Sc, however, the conductivity continues to increase up to 60% doping, which is the solubility limit for this system. It will be interestingand insightful to see how the character of different
dopants with the same formal charge can lead tosuch different behavior. We are working to contribute in this regard using ab initio thermodynam-

22

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo
(a)

(b)

Figure 7: (a) Evaluation of NN accuracy after active learning on The Pt/YSZ slab model and (b) the
obtained Y and O vacancy concentration profiles.
ics.

The ionic space charge layer
Another issue we are currently working on is theionic space charge effect at solid-solid interfaces.
The space charge concept is a central idea of semiconductor device physics, where a depletion or accumulation of holes or electrons occurs to alignthe Fermi level across the interface. The concept
should naturally be extended to mobile ions, which
are abundant in solid electrolytes, but the situation
is now much more complicated because various
ionic species can contribute to the effect, and ionscan even be introduced spontaneously (e.g., hydrogen in the atmosphere can spontaneously dope oxides [43]). A related (or maybe equivalent) concept in electrochemistry of liquid electrolytes isthe electrical double layer. The nanoscale atomistic details of the space charge layer is expected
to modify the ion dynamics in various ways. It
should impact the performance of solid state electrochemical devices such as solid-state batteries,
fuel cells, and electrolyzers, or may even lead tonovel functionalities. Because of this, the topic
is under intense study from both experimental
and theoretical standpoints (see, e.g., https://interface-ionics.jp/en/index.html).

In the past, we have combined ion defect formation energetics calculated using DFT with aPoisson-Boltzmann type model to calculate the ion
distribution near metal/solid electrolyte interfaces[44–46]. However, the energetics were calculated
in the bulk and do not include effects such as thechemical characteristics of the interface or the concentration dependencies of the dielectric constant.
Also, the interactions between defects were modeled considering only ideal point charge electrostatics. In other words, it is a mean field modelwith many assumptions and may not be reliable
enough for certain cases.
ab initio statistical thermodynamics approaches
introduced above are ideal for tackling this issue
and going beyond the simple mean-field picture.
As a first step, we calculated the ion distribution in
the Pt (111)/Yttria-stabilized zirconia (YSZ) (111)slab model (Fig. 7). Note that YSZ is a wellstudied oxide ion conductor for application in solidoxide fuel cells. The parent lattice is cubic fluorite
ZrO2 with 68 Zr sites and 126 O sites, and configurations of 12 Y ions on Zr sites and 6 O vacancies
residing on the O sites were sampled using our active learning NN-RXMC approach (Sec. 3). The
correlation between the DFT energies and NN predictions of the training, test, and verification sets

23

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

seems to be good enough, although not as perfectas the bulk MgAl2 O4 case (Fig. 5). The calculated
concentration profiles show a segregation of Y on
the outermost Zr layer and depletion on the second
and third Zr layers. There is also an increase in
the vacancy concentration on the second O layer.
The next challenge would be to consider variationsin the number of oxygen vacancies and perform
grand canonical sampling, so that the results can becompared directly with experiments which control
the oxygen partial pressure. We expect these calculations to be immensely useful for understanding the thermodynamics of space charge layer formation, and also to serve as a basis for understanding the modification of various materials properties
due to formation of interfaces.

5

ab Initio Configuration Sampling Toolkit (abICS)The software framework for direct couplingof RXMC sampling with DFT (Sec. 2) was
selected as an ISSP Project for Advancementof Software Usability in Materials Science for
SY2019. Parts of the prototype code developedby the author (S.K.) were rewritten in modular
fashion so as to enable easy extension of theframework. The original prototype only supported
VASP as the energy calculator, but interfaces
for OpenMX and Quantum Espresso are now
supported. In addition, a user interface employing
the human-readable and computer-friendly TOML
format (https://toml.io/en/) was developed
for setting up the calculations. The code has
been named ab Initio Configuration Sampling
Toolkit, or abICS for short, and released tothe public under an open source license (GPLver. 3), along with a user manual. It is under continous development (https://www.pasums.
issp.u-tokyo.ac.jp/abics/,
https://github.com/issp-center-dev/abICS),
and we are in the process of implementing theactive learning approach explained in Sec. 3.

6

Summary and outlook

In this report, we presented our recent efforts in enabling configurational sampling in complex oxidesystems from first principles. By harnessing thepower of modern day supercomputers in combination with extended ensemble sampling, it has now
become just barely feasible to perform sampling
directly on DFT energies on unit cells of ∼ 100
atoms. We also demonstrated that similar accuracy can be achieved with a speedup by a factor of∼ 104 by the use of a neural network model that
reproduces the configuration energetics. This has
made possible routine sampling on unit cells of afew hundred atoms with ab initio accuracy.
We have been implementing these approaches
in an open source framework abICS. We believethat this framework will be immensely useful formaking efficient use of the ever-increasing capacity of modern supercomputers. We are also aiming to bring together information science, materials simulation, and statistical physics using abICS
as a hub. Because of modular coding practices employed in our project, it should be relatively easy
to implement interfaces for other solvers, or to implement new sampling schemes. Please and do notrefrain from contacting us if you are interested inusing or extending this software.

Acknowledgements
abICS is developed by Yuichi Motoyama,
Kazuyoshi Yoshimi, Yoshiyuki Yamamoto, Osamu Sugino, Taisuke Ozaki, and the author (S.K.)
as part of the ISSP Project for Advancement ofSoftware Usability in Materials Science. The calculations presented in this work were performedon the ISSP Joint-Use Supercomputer Systems“sekirei”, “enaga”, and “ohtaka” as well as on the
supercomputer Fugaku provided by RIKEN for
the Fugaku Battery and Fuel Cell Project. This
report reviewed works supported over the years
by KAKENHI (Grant numbers JP18H05519,
19K15287, 20H05284), MEXT LEADER program, and JST CREST (JPMJCR15Q3) and24

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

FOREST (JPMJFR2037) programs.
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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo[32] T. Kostiuchenko, F. Körmann, J. Neugebauer,and A. Shapeev, npj Comput. Mater. 5, 1
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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

High precision study of the Anderson transition
TOMI OHTSUKI1
KEITH SLEVIN2
1) Dept. Phys., Sophia University, Chiyoda-ku, Tokyo 102-8554, Japan
2) Dept. Phys., Osaka University, Toyonaka, Osaka 560-0043, Japan(Dated: May 3, 2021)

INTRODUCTION

More than six decades have passed sinceAnderson’s seminal paper on localisation was
published[1]. During the subsequent decades, there
have been numerous important discoveries including weak localisation, universal conductance fluctuations, and the scaling theory of localisation[2].
Localisation phenomena are observed not only inelectron systems, but also in optical [3–9], acoustic [10–12], and cold atom systems [13–18].
Since the proposal of the scaling theory of
localisation[19–23], determining the critical behavior of the localisation-delocalisation transition,
which is usually referred to as the Anderson transition (AT), has continued to attract considerable
attention. Depending on the symmetry of the
Hamiltonian, systems are classified into orthogonal, unitary and symplectic symmetry classes, cf.
the classification of random matrices[24, 25]. This
classification was extended to include three classes
with chiral symmetry[26, 27], and four classes withparticle-hole symmetry[28]. These ten classes havealso proven useful in the discussion of whether or
not there is a topological phase and, if there is,what type of topological phase is realized, given
the symmetry class and the dimensionality of thesystem.[29, 30]
In this activity report, we review the numericalapproach for the study of the Anderson transition,
and also another type of transition, the metal tosemimetal transition. We emphasize the importance of the concept of universality class, and thescaling analysis of high precision numerical data.
The rest of this report is organized as follows. In
the next section, we explain the method, followedby the results for our recent high precision studies of three dimensional (3D) Anderson transitions
with and without time reversal symmetry. We thenreview the recent progress on the novel symmetry
classes with chiral and particle-hole symmetries aswell as the extension to non-Hermitian systems.
We conclude this report by discussing the metal

to semimetal transition and the scaling behavior ofthe density of states.

METHODS

We start with the Anderson’s model of
localisation[1],X
X
H=
Ei |ii hi| −|ii Vi,j hj| .
(1)
i

hiji

where |ii is an orbital localised on site i of a 3D
cubic lattice. The first sum is over all sites on thelattice and the second sum is over pairs of nearest neighbours. The unit of energy is the nearest neighbour transfer energy V = |Vi,j |, which we
set to unity V = 1. The orbital energies Ei are
assumed to be identically and independently distributed with a uniform distribution
1/W , |Ei | ≤ W /2 ,p (Ei ) =(2)0,otherwise .
The parameter W determines the strength of disorder. The Hamiltonian commutes with the complex
conjugation operator, i.e. a time reversal operator that squares to +1, and this model belongs tothe orthogonal symmetry class [21, 22, 24, 25] (seeTable I).
We can extend the Anderson model by including Peierls phases Vi,j = exp(iθi,j ), which describe
magnetic fields, in the nearest neighbour hoppings.
Here θi,j with i > j are randomly and uniformly
distributed between [0, 2π] and and θi,j = −θj,i .
We call this the U(1) model. In this case the Hamiltonian does not commute with a time reversal operator, and the model belongs to the unitary symmetry class.

Symmetry classification

We can further extend the model to include
spin/orbital degree of freedom by modifying Vi,j
and Ei and can realize different symmetry classes.

27

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo
Class

Symbol TRS PHS CS

Unitary
Orthogonal
Symplectic

A
AI
AII

No
1
-1

No No
No No
No No

Chiral Unitary
Chiral Orthogonal
Chiral Symplectic

AIII
BDI
CII

No
1
-1

No Yes
1 Yes-1 Yes

D
C
DIII
CI

No
No
-1
1

1
-1
1
-1

BdG

where ψx is the wavefunction on the slice at position x,(ψx )y,z = hx, y, z |Ψi .

(8)

Mx is the transfer matrix defined by,


No
No
Yes
Yes

Mx =

TABLE I. Classification according to TRS, PHS and
CS. For TRS (PHS), 1 means C T = C (C 0T = C 0 )whereas -1 means C T = −C (C 0T = −C 0 ). BdG means
Bogoliubov-de Gennes class.

−1−1 
Vx,x+1(E − Hx ) −Vx,x+1.
Vx+1,x
0N(9)

For the Anderson model where we set Vi,j = −1,
we have

 


ψx+1
Hx − E 1N
ψx=. (10)−ψx−1N 0N−ψx−1
Hx is the following sub-matrix of the Hamiltonian

Using the unitary operators C, C 0 and P , we canclassify the Hamiltonian according to whether itsatisfies the following symmetries[29],H = CH ∗ C −1 ,(3)for time reversal symmetry (TRS), andH = −C 0 H ∗ C 0−1 .

(4)

for particle-hole symmetry (PHS). Systems withTRS and PHS are further classified according towhether C or C 0 is symmetric or antisymmetric.
We also have chiral symmetry(Hx )y,z,y0 ,z0 = hx, y, z| H| x, y 0 , z 0 i .

(11)

0N and 1N are the N × N (N = L2 ) zero and unit
matrices, respectively. The boundary conditions in
the transverse directions influence some of the critical behavior[36]. In this report, we impose periodic
boundary conditions in the transverse directions.
We set the energy at the band centre, i.e. E = 0.
We note that the transfer matrix must satisfy thefollowing relation
MxT ΣMx = Σ ,

(12)

where
H = −P HP −1 , P 2 = 1 .

(5)Note that chiral symmetry is automatic when we
have both TRS and PHS.
The classification[29] is summarized in Table I.

Σ=

0N −i1N
i1N 0N
.

(13)

The wave-function amplitudes on the first twolayers are related to the wave-function amplitudes
on the last two layers as follows

The transfer matrix method
One of the ways to study the Anderson transition
with high precision is to calculate the quasi-one
dimensional localisation length and perform a finite
size scaling analysis [31–35].
We consider a system with a square cross section
L × L, which we divide into layers labelled by theirx coordinate. Then the Schrödinger equation for astate vector |Ψi and energy E
H |Ψi = E |Ψi ,is expressed in the following form




ψx+1
ψx
= Mx
,
Vx+1,x ψxVx,x−1 ψx−1

(6)

(7)

ψLx +1−ψLx

= MLx · · · M1

ψ1
−ψ0


,

(14)

which involves the product of Lx independently
and identically distributed random matrices M =MLx · · · M1 .
The following limiting matrix exists[37],ln M T M
.
Lx →∞
2Lx

Ω = lim(15)

The limit depends on the particular sequence ofrandom matrices, but the eigenvalues {γi } of Ω are
the same for all sequences (“all” means with probability one). These values are called Lyapunov exponents. From Eq. (12) these eigenvalues occur in28

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

pairs of opposite sign. It is usual to number themas follows
γ1 > · · · > γN > γN +1 = −γN > · · · > γ2N = −γ1 .
(16)This ± symmetry can be derived from Eq. (12).
To estimate the Lyapunov exponents we startwith a 2N × 2N orthogonal matrix, truncate thematrix product at a very large but finite Lx , andperform a QR decomposition of the result
QR = M Q0 .

(17)

Here, Q0 and Q are a 2N × 2N orthogonal matrix
and R is a 2N × 2N upper triangular matrix withpositive diagonal elements. We then defineγ̃i =1ln Ri,i .
Lx(18)

In the limit of infinite length
γi = lim γ̃i .
Lx →∞

(19)

For sufficiently large Lx , the {γ̃i } may be used toestimate the Lyapunov exponents.
This method requires the simulation of a single
very long sample. While this method has been employed very successfully in numerous simulations
over the preceding decades, the calculations are inherently serial and do not allow us to take advantage of massively parallel computers.

where h· · · i is the sample average. To generate such
matrices, we have found that the following procedure works well. We start with Q0 given by the
2N -dimensional unit matrix,
Q0 = 12N(22)

Q0 R = Mq · · · M1 Q0 .

(23)

and calculate

The matrix R is then discarded and we set Q0 = Q0 .
This procedure is then repeated a sufficient numberof times.
For a given L, we have found that, when a sufficient number of randomizing multiplications are
performed, the distribution of γ̃N becomes independent of the number of such multiplications[39].
We assess this by applying the KolmogorovSmirnov test to the data for γ̃N with different
numbers of randomizing multiplications. For sufficiently large number of randomizing multiplications we find that the Kolmogorov-Smirnov test
is unable to distinguish the distribution of γ̃Nobtained[39].

Fitting

Once we calculate γN , which is a function of thecross section size L and the strength of disorder W ,we defineΓ(W, L) = Lγ ,(24)

Parallel transfer matrix method

and assume the scaling form,
An alternative way is to simulate an ensembleof much shorter samples and consider an ensemble
average. While for simplicity we consider cubeswith Lx = L, the method is also applicable whenLx 6= L.
We note here that the matrix Q0 should be a
2N × 2N random matrix with orthogonal columns
sampled from a probability distribution that is invariant under convolution with the transfer matrix
distribution, i.e., with a distribution that is invariant under the operation[38]0Q R = Mx Q .

(20)For such a distribution, it immediately follows that[39]γN = hγ̃N i ,(21)

Γ(W, L) = F (φ1 , φ2 , φ3 , · · · ).

(25)

Each scaling variable φi on the right hand side has
a power law dependence on L
φ1 ≡ u1 (w)L1/ν ,φ2 ≡ u2 (w)L−y ,0φ3 ≡ u3 (w)L−y ,··· .
Here 1/ν (> 0) is the scaling dimension of the relevant scaling variable and −y is the scaling dimension of the least irrelevant scaling variable;· · · < −y 0 < −y (< 0).
In this report, we use the disorder strength W totune the system through the transition. We denotethe critical disorder where the transition occurs as

29

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Wc . We define w ≡ (W − Wc )/Wc . The functions uj (w) (j = 1, 2, · · · ) obey u1 (w = 0) = 0 anduj (w = 0) 6= 0 (j = 2, 3, · · · ). When w is sufficiently small, the u’s can be expanded in powers ofw
ui (w) ≡miXbi,j wj

are 3 WD classes (see Table I). Using System B
and simulating the Anderson and U(1) models, wehave determined the critical exponents of the 3D
orthogonal and unitary universality classes. The
results are summarized in Fig. 1 and Table II.

(26)
3.0

j=0

with i = 1, 2, · · · , b1,0 = 0, and bj,0 6= 0 (j =2, 3, · · · )[35, 40]. When the φ’s are sufficiently
small, the universal scaling function F can also be
expanded[41]. We keep only the relevant scaling
variable φ1 and the least irrelevant scaling variable
φ2 , while assuming the other irrelevant scaling variables to be zero, φ3 = · · · = 0. This should be reasonable for w sufficiently small and L sufficiently
large. We expand F in terms of φ1 and φ2 as
F =

n1 X
n2
X

aj1 ,j2 φj11 φj22 .

2.5

G

2.0

1.5

1.0

15.5

16.5

16.0

17.0

W

17.5

(a) 3D class AI(27)

j1 =0 j2 =0

To remove the ambiguity of fitting parameters, we
set a1,0 = a0,1 = 1. The parameter a0,0 is sometimes related to quantities of interest such as multifractal exponents[42], and we write it as Γc .
Whether the fit is plausible is determined by calculating the goodness of fit probability. When the
fit is plausible, we check the stability of the fit
against changes of the range of data being fitted
and of the orders of the polynomial expansions.
Fig. 1 shows an example of simulation data Γ andthe results of the fitting.
The confidence intervals of the fitting parameters
are determined by Monte Carlo simulations. From
the fitting function Fi = F (Wi , Li ) for the i-th data
(1 ≤ i ≤ ND , ND the number of data points), we
produce an ensemble of synthetic data sets with
Γ̃i = Fi + σi where σi is a random number, thevariance is the same as that of i-th data and themean zero. By fitting the synthetic data sets {Γ̃i }’s
we obtain the distribution of the critical parameterssuch as Wc and ν, and estimate their confidence
intervals.

NUMERICAL STUDIES OF THE
ANDERSON TRANSITION
Wigner-Dyson classes

For the Wigner-Dyson (WD) classes, neither theparticle-hole (PHS) or chiral (CS) is present. There

2.5

2.0

1.5

1.0
17.5

18.0

18.5

W

19.0

19.5

20.0

(b) 3D class A

FIG. 1. Γ as a function of the disorder strength W forvarious cross section size L. (a) 3D class AI, where L =12.18, 24, 32, 48 and 64. L = 96 is underway using new
System B. (b) 3D class A, where L = 4, 6, 8, 12, 16, 20
and 24. In the delocalised (localised) phase, Γ decreases(increases) with L. (a) is taken from [39] and (b) from[43].

The calculation time is proportional to the time
for the QR decomposition and the number of transfer matrix multiplications. The dimension of transfer matrix is proportional to L(d−1) , hence QR decomposition takes time proportional to L3(d−1) , dbeing the space dimension. In addition, to obtainthe same precision for larger L, we need to increase
the length Lx proportional to L. The calculation
time, therefore, is proportional to L3d−2 . This
rapid increase of calculation time for higher dimen-

30

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo
class

ν

Γc

Wc

ND NP p-y

3D AI 1.572[1.566,1.577] 1.7372[1.7359,1.7384] 16.543[16.541,16.545] 117 7 0.5 –3D A 1.443[1.437,1.449] 1.805[1.803,1.808]
1.805[1.803,1.808]
171 10 0.4 -3.1[-3.9,-2.4]
TABLE II. Results of the finite size scaling fits. Numbers are taken from Refs. [39, 43]. The systems sizes are
L = 24, 32, 48 and 64 for 3D orthogonal class (Anderson model, class AI), whereas they are L = 4, 6, 8, 12, 16, 20
and 24 for 3D unitary class (U(1) model, class A). The precision is expressed by 95% confidence intervals, ND
is the number of data points, NP the number of fitting parameters, and p the goodness of fit probability. For
the 3D orthogonal case, irrelevant scaling variables are not necessary. This is because we use only L ≥ 24 where
corrections to scaling are smaller than the precision of the data [35].

sion, at first sight, gives the impression that higher
dimensional simulation is almost impossible. However, the corrections to scaling are smaller in higher
dimensions, and the critical behavior in dimensions
higher than three has also been studied[43–45]. On
the other hand, the critical behavior of the quantum Hall transition, which occurs in two dimensions, is still controversial due to the very slowly
converging corrections to scaling[46].

Distribution of Kondo temperature

At the critical point, eigenstates exhibit multifractality. This is reflected in the fluctuations of
the local density of states. As a result, when we
consider magnetic impurities, the Kondo temperature TK has a broad distribution. It has been predicted that the distribution of TK has a power law
tail at small TK with a universal exponent whose
value is related to the multifractal exponent η [47].
Using the kernel polynomial method [48], we calculated the local density of states at the Andersontransition, and determined the distribution of TK .
The massively parallel calculations on System B enabled us to reach the small TK needed to check the
analytic prediction [49]. Experimental verification
may be possible by comparing with measurementsof the temperature dependence of the magnetic susceptibility.

Beyond the Wigner-Dyson classes

Systems with CS/PHS symmetries have attracted much attention recently, because manyof them are topological insulators or topologicalsuperconductors[29]. We note that these unconventional universality classes, i.e. classes other thanWigner-Dyson, are realized only at E = 0.
One way to realize a model with chiral symmetry

is to set all the orbital energies Ei = 0, and consider random hopping, Vi,j . Setting E = 0, we maythen vary the strength of the randomness of the
hopping and study the Anderson transition. Thisapproach, however, has proven to be difficult tohandle numerically because an unphysically large
disorder in the hopping is needed to cause an Anderson transition[50].
Fixing the hopping and changing the diagonal
disorder is easier for numerical calculations. Thiscan be realized by considering, for example, the following Hamiltonian, which corresponds to 3D classCI (see Table I). It is a two-orbital cubic latticemodel,XX
H≡|i, di[H](i,d|j,d0 ) hj, d0 |i,j d,d0

=

Xn



Ei + ∆ |i, aihi, a| − |i, bihi, b|i+ tk |i, aihi, b| + |i, bihi, a|
X X

+ t⊥
|i + eµ , di + |i − eµ , di hi, d|µ=x,y d=a,b+ t0k |i + ez , aihi, a| − |i + ez , bihi, b| + h.c.

o
.

(28)
Here d, d0 = a, b denotes the orbital index, i ≡(ix , iy , iz ) with ex = (1, 0, 0), ey = (0, 1, 0) andez = (0, 0, 1) is the site index on the 3D cubic
lattice. The orbital energies at two different lattice sites have no correlation; Ei Ej = δi,j W 2 /12.
The model has a particle-hole symmetry (PHP−1 =−H) as well as the time-reversal symmetry (H∗ =H) with [P](i,d|j,d0 ) ≡ (−1)ix +iy δi,j [σy ]d,d0 withthe 2 by 2 Pauli matrices, σx , σy and σz . Since
PT = −P, the Hamiltonian has a set of doubly
degenerate real-valued eigenstates at zero energy,
which results in the degeneracy of the Lyapunov
exponents at E = 0; the degeneracy is protectedby the particle-hole symmetry. For simplicity, we
set ∆ = tk = t0k = t⊥ = 1. As in the previ-

31

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyoous subsection, the localisation length of the zeroenergy eigenstates along the z-direction (λz ) is calculated via the transfer matrix method. The periodic boundary condition is imposed along x and y
directions. The density of states (DOS) of H withfinite disorder strength W is calculated in terms ofkernel polynomial expansion (KPE) method [48].
Due to the particle-hole symmetry, the calculated
DOS is symmetric about E = 0, while the DOS
at E = 0 remains finite at the critical point[51].
The exponent of 3D class CI thus estimated isν = 1.16 ± 0.02.
We can construct a similar Hamiltonian for the
3D class BDI, which is a model for disordered
nodal-line Weyl semimetal [51].

(a) 3D Anderson model

SUMMARY AND CONCLUDINGREMARKSphase diagram

In this review, we focused on the Anderson transition at E = 0 (center of the band). Once weknow the critical disorder Wc ≈ 16.54 at E = 0(see Table II), we can prepare thousands of delocalised (W < Wc ) and localised (W > Wc ) wave
functions. Then we can let a convolutional neural network (CNN) learn the features of these wave
functions[52, 53], and draw the phase diagram in
W − E parameter plane[54, 55].
Fig. 2(a) is an example. We take the training regions indicated by the arrows in Fig. 2(a), and let
the neural network calculate the probability thatthe states are delocalised in the rest of the parameter region. We can also draw the phase diagram forquantum percolation, where sites are present withprobability p and absent with probability 1 − p,and all the orbital energies are set to zero, Ei = 0.
From the training in the Anderson model where
the transfer matrix method is applicable, we candraw the phase diagram for the quantum percolation problem where the transfer matrix method
is not applicable. Fig. 2(b) is the phase diagram
for the quantum percolation problem drawn by theneural network trained using the Anderson model.

Beyond Hermitian classes

The symmetry classification according to TRS
and PHS can be extended to non-Hermitian (NH)(b) 3D quantum percolation

FIG. 2. Phase diagram of 3D Anderson transitions.
(a) is for Anderson model. The green arrows in (a) indicate the regions where the CNN is trained, whereas
the white dashed line and crosses indicate the phaseboundary estimated by other methods [56, 57]. (b) isfor site-type quantum percolation. The white dashedline is from the estimates by Ref.[58], whereas the green
horizontal dashed line indicates the classical percolation threshold. Taken from Refs.[54, 55].

systems [59]. For example, for TRS for Hermitian systems we have H = CH ∗ C −1 = CH T C −1
[Eq. (3)], but for non-Hermitian systems there are
two possibilities,
H = CH ∗ C −1 , H = CH T C −1 .

(29)

The latter symmetry is straightforwardly realized
for the Anderson model [Eq. (1)] by making theorbital energies Ej random complex numbers. We
then have H = H T but H 6= H ∗ . The system iscalled NH class AI† . Making the Ej complex in
the U(1) model realizes NH class A. The criticalbehaviors have been shown to be different from theHermitian classes AI and A[60, 61] via the finite

32

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

size scaling analyses.
These two classes are only a part of the 38 symmetry classes[59] in non-Hermitian disordered systems. The critical behavior for these classes is aninteresting topic left for the future.

Density of states scaling

So far, we have discussed the Anderson transition. There are other transitions in the same symmetry classes. For example, the semimetal to metaltransition[62] occurs in 3D Dirac and Weyl systems,
where the systems remains semimetal up to certain strength of disorder, then undergoes semimetal
to metal transition. (Further increase of disorderleads to an Anderson transition.) Though the symmetry classes are AII (Dirac) and A (Weyl), thecritical behaviors described by the scaling of thedensity of states[63, 64] is different from the Anderson transition, i.e., both the exponent ν and the
dynamical exponent z differ from those of the Anderson transition in the same symmetry class anddimensionality.

Experiments

Interpreting the critical behavior found experimentally in doped semiconductors remains difficult
because the role of the electron-electron interaction, which may be relevant in the renormalisation group sense, is not well understood. In experiments, the critical exponent s, which describes
how the zero temperature conductivity vanishes as
the critical point is approached from the metallic side, is measured. This exponent is related
to the critical exponent ν by Wegner’s relations = (d − 2)ν[19]. As yet there is no agreement
between theory and experiment and understanding
the critical behaviour at the metal-insulator transition in doped semiconductors remains an open
problem[65, 66].
The quantum kicked rotor with suitable quasiperiodic modulation exhibits an Anderson transition in the the same universality class as that inAnderson’s model of localisation in 3D. This experimental realisation of the quantum kicked rotor
has provided an alternative avenue for experimental investigation of the Anderson transition.[13–15].
The value ν = 1.63 ± 005 [15] found in these experiments agrees well with our numerical estimate.

Light waves [3, 4, 7–9] and acoustic waves [10–12] also localize and interaction effects play less ofa role. For small loss, such systems are describedby the 3D class AI. When the loss is not negligible,
the system might show the critical behavior in 3Dclass AI† . Quantitative studies and detailed comparisons between theory and experiment are interesting topics left for the future.
Acknowledgement The work was partly supported by JSPS KAKENHI Grants 19H00658.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Large-scale molecular dynamics simulations of Kármán
vortex and sound wave: cavitation and polymer effects
Yuta Asano 1, Hiroshi Watanabe 2, and Hiroshi Noguchi 1
1

Institute for Solid State Physics,

The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581, Japan2

Department of Applied Physics and Physico-Informatics,

Keio University, Yokohama, Kanagawa 223-8522, Japan

Abstract

lives. Therefore, a thorough understanding of the

In many industrial flows, microscale effects

flow phenomena will improve our lives, also

have a significant impact on their macroscalesignificantly

flows. Turbulent drag reduction by polymer

environmental protection. Flow control in

addition and cavitation around rotating turbines

industrial processes is an essential topic in fluidin water are typical examples. In these flows,engineering, such as turbulence drag reduction

phenomena in a wide range of scales coexist,

by polymer addition [5] and gas-liquid multi-

from molecular scale motion to macroscale fluid

phase flow due to the cavitation [6]. Thus, many

motion, and these interact with each other underresearchers have conducted experiments andstrongly non-equilibrium. Therefore, it isnumerical simulations based on the Navier—challenging to clarify the underlying mechanism

Stokes equation to clarify the mechanisms.

by its complexity.

However, since various phenomena in a wide

We have performed large-scale molecularrange of scales coexist and interact with each

dynamics (MD) simulations of complex flows,other in non-equilibrium, the analyses are

such as polymer solutions and cavitating flow, as

challenging issues. Therefore, it is crucial towell as MD of sound propagation, using theanalyze all phenomena simultaneously, from

ISSP supercomputer. In this activity report, wemolecular-scale dynamics to fluid motion topresent a brief overview of these studies [1-4].

understand the complex flows.

contributes

toglobal

Mesoscale analysis methods such as the

1. Introduction

lattice Boltzmann method [7] and Multi-particle

Fluid flows play a vital role in a wide range

collision dynamics [8,9] have been developed toof fields, from tap water familiar to our daily

analyze the flow considering the effects oflives to fuel pipelines in energy supply systems.

molecular-scale dynamics. Also, the micro-

It is no exaggeration to say that flow sustains our36Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

macro coupling approaches [10,11] have been
proposedtoinvestigate

more

detailed

molecular-scale information. However, in lightof today's computational power, it is possible tosimulate flows by all-particle simulations,
namely a molecular dynamics (MD) simulation.
In the MD simulation, molecular-scale dynamics,
such as phase transition and polymer motion,
naturally appear in the flow by simply solving
the Newtonian equations of motion, only
providing the interparticle interactions. In
conventional

fluid

analysis

methods,

phenomenological models, such as constitutive
equations and an equation of state, are required
to describe these phenomena. Instead, we haveto prepare a sufficiently large computational cell
that

can

resolvecharacteristics.

themacroscale

flow

Therefore,

althoughitisinevitably a large-scale simulation, it will help

Fig. 1: Instantaneous vorticity fields for

us understand complex flow phenomena.

(a) the Newtonian fluid, (b) polymer

In this report, we present a brief overview offlow

analysisbyusing large-scale

solution with the number of segmentsMD

𝑵𝐬 = 𝟏𝟎, and (c) polymer solution withsimulations. We explain the effect of polymer

𝑵𝐬 = 𝟏𝟎𝟎 at the Reynolds number 𝑹𝒆 =addition and cavitation on the flow around a𝟔𝟒 [1].

cylinder in sections 2 and 3, respectively. In

Adding a tiny amount of polymer into a

section 4, we describe the application to

Newtonian fluid involves significant changes insoundwave propagation in a simple fluid. In

the flow characteristics, such as a dramatic

section 5, we explain the recent study of

reduction in frictional drag [5] and suppression

cavitating flow in a polymer solution. Section 6of the Kármán vortex [12]. Since most industrial

is a summary.

flows are turbulent, the flow control by adding
polymers is an attractive method in engineering

2. Effects of polymer addition on

applications

Kármán Vortex [1]37

becauseitsaves

energyActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

necessary to elucidate the effects of polymers on
vortices from the molecular scale. We focus on
the flow around a cylinder, which is the mosttypical flow accompanied by vortices and issuitable for analysis due to its periodicity. We
investigate the effects of polymers on vortices inthe two-dimensional flow around a circularcylinder by MD simulations.
Figure 1 shows typical snapshots of thevorticity field. As for the Newtonian fluid, analternating vortex street, the Kármán vortex
street, appears behind the cylinder. Similar
vortices appear for the short-chain polymers.
However, for long-chain polymers, the vortices
are blurred. Therefore, the chain length of thepolymer significantly affects vortex formation.
Fig. 2: Fourier spectra of the lift

Figure 2 shows the Fourier spectra of the lift

coefficient at 𝑹𝒆 = 𝟔𝟒 [1]. (a) Newtonian

coefficient. For the Newtonian fluid, a sharp

fluid. (b) Polymer solution with 𝑵𝐬 = 𝟏𝟎

peak appears, which indicates periodic vortex

and volume fraction 𝝓 = 𝟏𝟎. (c) Polymer

shedding. Note that the peak frequency issolution𝝓=slightly increased by the finite size effects we

𝟎. 𝟎𝟐.(d) Polymer solution with 𝑵𝐬 = 𝟏𝟎𝟎

reported in Ref. 13. The short-polymer solutionand 𝝓 = 𝟎. 𝟏𝟎𝟕 .

andshows a similar sharp peak. On the other hand,horizontal dotted lines denote the peak

the peak position shifts to a lower frequency, andposition and height for the Newtonian

the spectrum broadens for the long-polymer

fluid, respectively.

solution. These effects enhance with increasingwith

𝑵𝐬 = 𝟏𝟎𝟎
Theandverticalpolymer concentration. The effects of polymer

consumption. However, the mechanism is not

addition on the flow, (1) vortex blurring, (2)well understood because the polymer rheology

frequency reduction, and (3) chain length effect,in a flow is unclear.

obtained by MD simulations, are in good

The interaction between polymers and vortices

agreement with experimental results [12].

presumably plays a significant role in the

Figures 3(a) and 3(b) show the gyration

changes in flow characteristics. Therefore, it isradius of short- and long-chain polymers,

38

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

the other hand, long-chain polymers are
significantly stretched near the cylinder and in
the vortex behind the cylinder. Furthermore, thevortex also entrains the polymer in its vicinity.
Figures 3(c) and 3(d) show the orientational
order Q of the short- and long-chain polymers,
respectively. When the polymer aligns in theflow direction, 𝑄 = 1

the polymer aligns

perpendicular to the flow, 𝑄 = −1 the polymer
directs randomly, 𝑄 = 0 . For the short-chain
polymer, polymers orient randomly in the entire
area. However, for long-chain polymers, thepolymers are aligned in the flow direction near
the cylinder. Furthermore, the polymers also
tend to align in the flow direction in the vortices
behind the cylinder. The reduction of theorientational order behind the cylinder is due tothe entrainment by the vortex. Therefore, thestretching and entrainment of the polymer play asignificant role in vortex suppression. As aconsequence, the shapes of the vortices become
blurred.
Fig. 3 Spatial distributions of the gyration
radius 𝑹𝐠 and orientational order Q for
the polymer solutions with (a, c) 𝑵𝐬 = 𝟏𝟎
and (b, d) 𝑵𝐬 = 𝟏𝟎𝟎 at 𝑹𝒆 = 𝟔𝟒 and 𝝓 =𝟎. 𝟏𝟎𝟕[1]. 𝑹𝐠𝟎 is the gyration radius in theabsence of the flow.

3. Effects of cavitation on the Kármán
vortex behind circular-cylinder arrays[2]
Cavitation is a phenomenon of forming
bubbles due to local pressure drop in a flowing
liquid with high velocity [14]. When cavitation

respectively. For short-chain polymer, theoccurs in fluid machinery, such as pumps andgyration radius is virtually identical to that in theturbines, it causes various adverse effects suchstationary fluid. Therefore, the polymer flows

as performance degradation, noise and vibration,with an almost spherical shape as a particle. On

and erosion. Therefore, it is vital in fluid

39

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Fig. 5: Instantaneous void fraction fieldsfor (a) 𝑻 = 𝟏. 𝟑 , (b) 𝑻 = 𝟏. 𝟐𝟓 , and (c) 𝑻 =𝟏. 𝟐 [𝟐].

Fig 4: Instantaneous vorticity fields forthe (a) non-cavitating flow (𝑻 = 𝟐) andthe vorticity and void fraction field, respectively.

(b-d) cavitating flows (𝑻 = 𝟏. 𝟓, 𝟏. 𝟐𝟓,

At high temperature (𝑇 = 2), no bubbles appear

and 1.2) [2].

(i.e., non-cavitating flow). The Kármán vortex
appears behind the cylinders, and the upper andengineering to clarify the cavitation mechanism

lower vortex streets synchronize in anti-phase.

for appropriate control of the cavitating flow.
However,

becauseofthelimitations

As temperature decreases, bubbles appear in theofvicinity

discussing the dynamics of microscopic bubble

of

the

cylinderat 𝑇 = 1.3 inconjunction with vortex shedding (Fig. 5 (a)).

nuclei in a macroscopic flow, the cavitationThe

mechanism is still not understood well. To

vortexstreets

behindthecylindersynchronize in anti-phase, as in the case of 𝑇 =clarify the effects of cavitation on the flow, we

2 (Figs. 4(a) and 4(b)).

performed a large-scale MD simulation of the

At 𝑇 = 1.25, the gas phase region is formed

flow for the Lennard-Jones (LJ) aroundbehind the cylinder and is attached to thecylinders in a side-by-side arrangement.

cylinder (Fig. 5(b)). Also, the phase difference

Figures 4 and 5 show the typical snapshots of

between the upper and lower vortex streets40

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyoof the lift coefficient 𝐴L and the vortex
formation length 𝐿f . For comparison, the figure
also shows the results for the Newtonian fluid.
For the reference liquid, 𝐴L and 𝐿f tend toincrease and decrease with increase Re,
respectively. However, in the case of LJ fluids,
they exhibit non-monotonic behavior to 𝑅𝑒 .
This behavior is probably due to the conflicting
effects of increasing 𝑅𝑒 and bubble generation.
𝐴L rapidly decreases and finally disappears dueto the bubble generation. Simultaneously withthe disappearance of 𝐴L, 𝐿f rapidly increases.
For the Newtonian fluid, 𝐴L and 𝐿f show

Fig. 6: 𝑹𝒆 dependence of (a) the lift

almost the same trend for the two-cylinder

coefficient amplitude and (b) vortex

system and the one-cylinder system, which hasformation for the LJ fluid and Newtonian

only one cylinder with the same distance

fluid [2]. Double and Single in the legend

between the neighboring (periodic image)denote two- and one-cylinder systems,

cylinders (therespectively.

vortex streets are always

synchronized in-phase). In the case of LJ fluid,slightly shifts (Fig. 4(c)). At 𝑇 = 1.2 , the gas

however, the behavior before bubble generation

phase region behind the cylinder expands further

is different. The upward and downward peaks(Fig. 5. (c). In addition, the upper and lower

appear in 𝐴L and 𝐿f , respectively. Theirvortex structures become asymmetric (Fig. 4(d)).

positions for one- and two-cylinder systems areThis asymmetric vortex structure switches over

𝑅𝑒 = 105 and 101, respectively. These peaks

a long period. For the fluid without phaseare probably due to a small nucleus generationtransition, such a change in the flow field does

which is the precursor of the cavitation or

not occur with temperature change. We founddensity fluctuations originating from the criticalthat the density fluctuation caused by the bubble

phenomena. Since the phase retraction amplifies

generation has a significant effect on the vortex

the oscillation amplitude, the peak appears at astructure.

higher temperature in the two-cylinder system

As the vortex structure changes, the lift force

than in the one-cylinder system. After bubble

acting on the cylinder is also affected. Figure

generation, the bubbles weaken the interference6(a) shows the 𝑅𝑒dependence of the amplitude

between the vortex street, and the effect of the41

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Fig. 8: Waveforms of the LJ fluid for theFig 7: Waveforms of the LJ fluid for the(a) 𝒇 = 𝟎. 𝟎𝟎𝟐 and 𝑨 = 𝟓, (b) 𝒇 = 𝟎. 𝟎𝟎𝟐(a) amplitude 𝑨 = 𝟐. 𝟓 (b) 𝑨 = 𝟓 (c) 𝑨 =and 𝑨 = 𝟏𝟎 (c) 𝒇 = 𝟎. 𝟎𝟎𝟒 and 𝑨 = 𝟓 ,𝟏𝟎 , and (d) 𝑨 = 𝟐𝟎 at frequency 𝒇 =and (d) 𝒇 = 𝟎. 𝟎𝟎𝟒 and 𝑨 = 𝟏𝟎 [𝟑] . The

𝟎. 𝟎𝟎𝟏 [3]. The red and black lines

red and black lines represent the results

represent the results of MD simulationof MD simulation and the Burgers'

and the Burgers' equation, respectively.

equation, respectively.
phase difference is almost negligible. We foundthat the bubble generation significantly affects

extend in a wide range of applications, such as

the vortex structures, vortex interference, and lift

medical treatment and food processing. For

due to vortex shedding.

these applications, it is crucial to understand thecharacteristics of ultrasonic cavitation and the

4. Soundwave propagation in simple

propagation in complex fluids. Therefore, it is

fluid [3]necessary

toanalyze

the

sound

wave

propagation from the molecular scale.

Sound waves are a familiar phenomenon in
our daily lives, such as the voices and sound of

We apply the MD simulation to the soundmusical instruments. Because of the soundpropagation in the LJ fluid. Moreover, weproperties of propagating a wide range of solid,

perform the fluid dynamics calculation utilizing

liquid, and gaseous materials, their application

Burgers' equation to justify the validity of theexists in a wide range of engineering fields. In

MD simulation for the sound waves. When theparticular, applications of ultrasonic cavitation

same fluid is analyzed, the two results should

42

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyodeviatethe magnitude of the deviations

becomes greater for higher amplitudes. Thisdeviation is due to the acoustic flow that occurs
by the high nonlinearity owing to high frequency.
Since Burgers' equation is not applicable in theregion where acoustic flow occurs, a fluid
analysis

involvinghigher-order

terms

is

necessary for a quantitative discussion. The MD
simulation provides a waveform reflecting thenonlinearity, thus obtaining a
Fig.

9:

𝒙

dependences

of

the

frequency-

dependent sound speed.

(a)normalized amplitude and (b) attenuation

The attenuation coefficient of a sound wave

coefficient of the LJ fluid [3]. The solid

is estimated from the decrement in amplitude.

and broken lines represent the results of

Figure 9(a) shows the amplitude decrement at

MD simulation and Burgers' equation,

𝑓 = 0.001 . When the amplitude is small, therespectively. The dotted line in panel (b)deviation of the MD simulation from theshows

Burgers’ equation is slightly different due to thetheclassical

attenuation

thermal fluctuations. As the amplitude increases,

coefficient.

the agreement between them becomes better. We

agree within the statistical error.

estimate the attenuation coefficient by the

Figure 7 shows the amplitude dependence oflogarithmic decrement rate of the amplitude at

the waveform of the LJ fluid at frequency 𝑓 =each position 𝑥 . Figure 9(b) shows the0.001 . For small amplitudes, the waveform isattenuation coefficient as a function of 𝑥 . The

sinusoidal owing to the weak nonlinearity. As

dotted line shows the value of the attenuation

the amplitude increases, the waveform becomescoefficient evaluated from the classical theory.

a sawtooth waveform (Figs. 7(c) and 7(d)). The

The results of the Burgers’ equation approach

black dotted lines in Fig. 7 are the numericalasymptotically to the classical attenuation

solutions of Burgers' equation, which is in goodcoefficient at a sufficient distance from theagreement with the results of the MD simulation.

sound source position ( 𝑥 = 0 ). Although the

Figure 8 shows the frequency dependence of

results of the MD simulation are in good

the waveform at higher frequencies. As theagreement with the results of Burgers' equation

frequency increases, the waveforms of the MD

when the amplitude is large, the attenuation issimulation and Burgers' equation become

overestimated by the nonlinearity. On the other43

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Fig. 10: Instantaneous void fraction fields of the (a) LJ fluid and (b) polymer solution, andtime-averaged void fraction of the (c) LJ fluid and (d) polymer solution at 𝑻 = 𝟏. 𝟐𝟓 [𝟒].
hand, the attenuation coefficient is hardly

flows, it has attracted attention. Although it isestimated for small amplitudes due to thermal

challenging to simultaneously analyze polymer

fluctuation. Therefore, to obtain the classicalmotion,attenuation coefficient by the MD simulation,

macroscopic flow, the analysis should be

the practical method is to estimate thepossible by integrating the methods described inparameters of the Burgers’ equation from theSections 2 and 3. Here we briefly describe only

waveform of MD simulation.

the main results.

bubblenucleusdynamics,

andWe investigate the effect of the polymer

5. Effects of the polymer addition on the

addition on the cavitating flow around a circular

cavitating flow [4]cylinder. Figure 10 shows the distribution of

Finally, we briefly describe our recent

void fraction in the cavitating flow of the LJ

analysis on the cavitating flow. In extreme cases,

fluid at 𝑇 = 1.25 , at which the cavitation occurs

the adverse effects on fluid machinery caused byas described in Sec. 3. The polymer addition

cavitation are prevented by controlling the flow

dramatically suppresses theto suppress cavitation. However, in general,

bubbles. Note that the polymer addition has

most industrial flows are highly irregularnegligible effects on the phase transition in the

turbulent fields, and it is difficult to achieve suchabsence of the flow. From the temperature

flows by mechanical design. Since polymer

changeaddition is one of the methods to realize suchconformation change in the polymer, we found

44

in

the

fluid

formation ofelement

andtheActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

that the vortex suppression and the entropic

Morii, Shinichi Tsuda, Yuichi Kunishima, andelasticity by the polymer have essential roles in

Yuji Higuchi for helpful discussions. This

the suppression of cavitation.

researchwassupported

by

MEXT

as

“Exploratory Challenge on Post-K computer”

6. Summary(Challenge

of

Basic

Science

Exploring

We performed large-scale MD simulations

Extremes through Multi-Physics and Multi-

for complex fluids involving polymers, gas-

Scale Simulations) and JSPS KAKENHI (Grant

liquid multi-phase flows owing to cavitation,No.

and sound waves. The direct analysis from theSupercomputer Center, Institute for Solid State

molecular scale enables us to analyze the flow

Physics (ISSP), University of Tokyo, Research

field reflecting the micro-scale effects, such asCenter for Computational Science (RCCS),

the elongation properties of polymers, phase

Okazaki, Japan, and Center for Computationaltransitions that are difficult to model byMaterials Science, Institute for Materials

conventional computational fluid dynamics. In

Research (IMR), Tohoku University for the use

particular, we were able to analyze cavitation inof their supercomputers (Project No.20S0026

complex fluids, which was one of the mainfor MASAMUNE-IMR in IMR).

JP19H05718).

We

acknowledgetheobjectives at the beginning of our research. This
achievement would not have been possible

References

without using the ISSP supercomputer system B[1] Y. Asano, H. Watanabe, and H. Noguchi, J.

(Ohtaka).

Chem. Phys. 148 (2018) 144901.

Compared to conventional fluid analysis[2] Y. Asano, H. Watanabe, and H. Noguchi, J.

methods, MD simulation does not require

Chem. Phys. 152 (2020) 034501.

phenomenological models such as equations of[3] Y. Asano, H. Watanabe, and H. Noguchi, J.

state. The advantage of MD simulations is that

Chem. Phys. 153 (2020) 124504.

all physical quantities and phenomena are[4] Y. Asano, H. Watanabe, and H. Noguchi, J.

obtained from molecular motion. Therefore, theChem. Phys. 155 (2021) 014905.

MD simulation is a suitable tool to analyze[5] G. E. Gadd, Nature 206 (1965) 463.

complex flow phenomena, such as the multi-[6] R. E. Arndt, Ann. Rev. Fluid Mech. 34 (2002)

phase and multi-component flow around a143.

propeller.

[7] S. Succi, The Lattice Boltzmann Equation:
For Fluid Dynamics and Beyond, Oxford

Acknowledgment

University Press Inc., New York (2001).
[8] R. Kapral, Adv. Chem. Phys. 140 (2008) 89.

We thank Toshihiro Kawakatsu, Youhei

45Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo[9] G. Gompper, T. Ihle, D. M. Kroll, and R. G.
Winkler, Adv. Polym. Sci. 221 (2009) 1.
[10] T. Murashima, ISSP Supercomputer
Activity Report 2015 (2015) 35.
[11] X. Xu and P. Yu, J. Non-Newtonian Fluid
Mech. 229 (2016) 27.
[12] J. R. Cressman, Q. Bailey, and W. I.
Goldburg,

Phys.

Fluids13(2001)

867.

[13] Y. Asano, H. Watanabe, and H. Noguchi, J.
Phys. Soc. Jpn. 88, 075003 (2019).
[14] C. E. Brennen, Cavitation and Bubble
Dynamics, Oxford University Press, (1995).

46

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.2

First-Principles Calculationof Material Properties

47

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Simulation of electrochemical interfaces
Osamu Sugino
Institute for Solid State Physics,
The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581
The electrochemical interface provides a

calculated results are used then to investigate theunique environment for efficient redox reactions.

activity. So far various structures with different

The platinum-electrolyte interface has long beenstability and activity are obtained and thisfocused on the fuel-cell study because of thevariety can be recognized as the characteristics

efficient oxygen reduction reaction (ORR), butof this material. Comparison with experiment is

defective TiO2 has attracted attention for its

now underway.

enhanced reactivity and durability. It was

Through the abICS calculation, we have

explained in our previous first-principles study

constructed a machine learning model of thethat the various adsorption forms taken by theinterface, and we plan to predict the activity after

ORR intermediates, such as OH and O2H, is theobtaining sufficient number of samplings.

reason for the reactivity [1]. This contrasts to themetal electrocatalysts where the variety in the

References

adsorption is quite small and thus the ORR[1] Y. Yamamoto et al., J. Phys. Chem. C 2019,activity

123, 32, 19486–19492.

islimitedthereby[2].

Further

investigation of the oxide electrocatalyst is the[2] A. Kulkarni et al., Chem. Rev. 2018, 118,

target of this project.

2302– 2312.

Together with experimentalists, we modeled[2] abICS is a software of first-principles Montea ZrO2 surface introduced with oxygen

Carlo simulation developed by Dr. S. Kasamatsu.

vacancies and foreign dopants to study the ORR

https://github.com/issp-center-dev/abICS

reactivity. To make the model realistically mimic
the experiment, we have performed the firstprinciples Monte Carlo simulation using abICS[2] and obtained equilibrium structures for theinterface at the annealing condition. The

48

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Mechanisms of Semiconductor Interface Formation and its Electronic
Properties based on Quantum Theory
Atsushi Oshiyama
Institute of Materials and Systems for Sustainability, Nagoya University
Furo-cho, Chikusa-ku, Nagoya 464-8601
In the fiscal year of 2020, on the basis of thenanoscience and technology. We have performed

total-energy electronic-structure calculations andfirst-principles calculations that elucidate atomic

molecular

thestructures and formation energies of the surface

density-functional theory, we have studied thesteps of GaN (0001) surfaces, unveil atom-scale

epitaxial growth of power semiconductors, atomic

elementary processes of N incorporation at theand electronic structures of semiconductor-

step edges, and then provide a microscopic

insulator interfaces, and the complex of line

picture of the step-ow epitaxial growth of GaN.

dynamics simulations within

defects and impurities. The main computational
tools are our RSDFT (Real Space Density
Functional Theory) code and RS-CPMD (CarParrinello Molecular Dynamics) code. We haveclarified 1) the atom-scale mechanism of GaN
epitaxial growth [1], 2) the mechanism of theFig.1: Calculated electron densities near
the GN step (a) and the Ga2 step (b). The
densities are represented by the yellow
isovalue surfaces. The small yellow
clouds reflect the presence of the low
electron density, indicating that the GaGa weak bonds are formed at the stepedges. The Ga, Ga-ad (Ga adatom), and N
atoms are represented by the green, pink,
and blue balls, respectively.

adatom diffusion on SiC stepped surface[2], 3)
the formation of dangling-bond free interface of
GaN and a gate insulator[3,4], and 4) atomic andelectronic structures of the dislocation-impurity
complex in GaN [5].
The group identification codes for theachievements above are k0042 and m0001. The

Epitaxial growth usually takes place on Ga-

below is the explanation of the issue 1) above.

rich vicinal surfaces in which the (0001) surface

Step-flow epitaxial growth of GaN

is slightly inclined toward [1100] or [11-20]

Growth of high-quality epitaxial thin films of

direction. There are five distinct mono-bilayer

GaN is indispensable for the energy-saving power

steps on such vicinal surfaces depending on theelectronics and the clarification of the mechanism

atomic species, Ga or N, at the step edges and theof the epitaxial growth is essential to advance

inclined directions. We have performed the49Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

geometry optimization for all the possible step

We have previously shown that the NH3edges and calculated the step formation energies.

provided in Metal-Organic Vapor Phase Epitaxy

Typical structures of the step edges are shown(MOVPE) arrives at the terrace of the growing

in Fig. 1 along with the electron density. The

Ga-rich surface and is decomposed into the NH

characteristics is the presence of Ga-Ga bonds atunit [Fig. 2(c)] [6]. Now we have found this NH

the step edges. As is clear from the small electron

unit diffuses on the surface terrace with theclouds in Fig. 1, the Ga-Ga bonds are relatively

activation energy of 0.6 eV (Fig. 2).

weak and thus become hot spots for the epitaxial
growth.

Fig. 3: The GN step-edge structure with
two NH units intervening in the Ga-Ga
bonds. Burgandy, green, blue and orange
balls depict Ga adatom, Ga, N and H
atoms, respectively.

This indicates that the NH units wander on theterrace and occasionally reach the surface stepedges. We have indeed examined the energetics ofthe reaction in which two isolated NH units on theterrace diffuse toward a step edge and intervene
into the adjacent Ga-Ga bonds as in Fig. 3. We

Fig. 2: Diffusion pathway and thecorresponding energy barrier of an NH
unit on the terrace of GaN(0001)
surface. (a) The total-energy landscapealong the diffusion pathway. The left
and the right ends correspond to theinitial and the final geometries,
respectively. (b) Diffusion pathway in a
top view represented by the small redballs which denote the lateral positionsof the N atom in the NH during the
diffusion. (c) An initial geometry of the
NH unit which intervenes in the weakbond between the Ga adatom and the
top Ga atom. (d) A final geometry of the
NH unit which intervenes in theadjacent Ga-Ga weak bond. Burgandy,
green, and blue balls depict Ga adatom,
Ga and N atoms, respectively.

have found this reaction is exothermic with theenergy gain of 0.45 eV.
Then the next step is the incorporation of Ga
atom at the step edge. Since the growing surface
is Ga rich, it is highly likely that an additional Ga
atom approaches the step edge where the two NH
units are incorporated [Fig. 4(a)]. We have thenexamined a reaction in which the two H atoms aredesorbed as an H2 molecule and the arriving Ga isincorporated at the step edge [Fig. 4(b)]. We haveidentified a pathway of this reaction, andcalculated the energy profile [Fig. 4(d)]. We have50

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

free-energy gain at growth temperature and under
the typical H2 partial pressure. It is evaluated tobe 2.1 eV. This certainly compensates theobtained zero-temperature energy cost of 1.8 eV,
indicating that this reaction is favorable.
The top view of the final structure is shown in
Fig. 4(c).

The step edge before this reaction

proceeds one unit by incorporating two N atoms
from the NH units and a new Ga atom. This is theelementary process of the step-flow epitaxial
growth.

Related Publications[1] K. M. Bui, K. Shiraishi and A. Oshiyama,Appl. Surf. Sci. 557, 149542 (2021).

Fig.4: An elementary process in the stepflow growth of GaN. (a) Stable structureof the GN step edge attached with 2 NH
units and an additional Ga atom nearby.
(b) Stable structure of the GN step with
H2 desorbed from the structure (a). (c)The top view of the stable structure
shown in (b). Color code of the balls
depicting atoms are the same as in Fig. 3.
The additional Ga adatom is shown bypurple. (d) Calculated energy profile forthe reaction from (a) to (b).

[2] K. Seino and A. Oshiyama, Appl. Surf. Sci.
(2021) to be published.
[3] K. Chokawa, T. Narita, D. Kikuta, T. Kachi, K.
Shiozaki, A. Oshiyama and K. Shiraishi, Phys.
Rev. Applied 14, 014034 (2020).
[4] K. Chokawa, K. Shiraishi and A. Oshiyama,Appl. Phys. Lett. (2021) to be published.

found that the energy cost of this reaction is 1.8[5] T. Nakano, Y. Harashima, K. Chokawa, K.

eV. However, by examining the obtained energy

Shiraishi, A. Oshiyama, Y. Kangawa, S. Usami,

profile in Fig. 4(d), this is the cost to make 2H

N. Mayama, K. Toda, A. Tanaka, Y. Honda, andatoms on the surface an H2 molecule in the gas

H. Amano, Appl. Phys. Lett. 117, 012105 (2020).

phase. In the gas phase, the H2 molecule gains the[6] K. M. Bui, J.-I. Iwata, Y. Kangawa, K.

free energy owing to its translational, vibrational

Shiraishi, Y. Shigeta, and A. Oshiyama, J. Phys.

and rotational motions. We have evaluated such

Chem. C 122, 24665 (2018).

51

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Analyses on electronic structure and magnetoelectric effect inhigh-performance spintronics and magnetic materials
Tatsuki ODA1,2, Indra PARDEDE1, Daiki YOSHIKAWA2, Tomosato KANAGAWA2,
Nurul IKHSAN2, Hasan Al RASYID2, Marleni WIRMAS2, Masao OBATA1,2
1

Institute of Science and Engineering, Kanazawa University, Kanazawa, Ishikawa 920-1192
2

Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa,
Ishikawa, 920-1192
We studied the magnetic anisotropy and its

magnetization directions. In addition, the non-electric field (EF) effect in the thin film related

collinear spin density can estimate the shapewith spintronic devices [1]. We obtained anmagnetic anisotropy energy (SMAE) by using

qualitative agreement between theory andthe scheme developed before in our researchexperiment on magnetic anisotropy of thegroup [3]. In the present applications, themagnetic thin film including the Fe/MgO

contributions of MCAE and SAME haveinterface with Cr underlayer, by taking into

different sign in the numerical values.

account an alloying effect of Fe-Cr. Without

Therefore, an accurate numerical computation

alloying in the theoretical calculation, the total

is required for obtaining a realistic result.

magnetic anisotropy indicates an in-plane

We used the thin films in the followings;

magnetization. Such theoretical consequencevacuum/Cr(6ML)/Fe(4ML)/MgO(5ML)/vacu

had been solved in the comparison with theum(S-I) and vacuum /Cr(6ML)/Fe(1ML)/Cr

experimental result [2] that showed a(1ML)/Fe(3ML)/MgO(5ML)/vacuum(S-II).

perpendicular anisotropy. The introduction of

The magnetic anisotropy energy (MAE) was

alloying effect may be consistent with thecalculated from the total energy difference

fabrication condition in the experiment. As abetween in-plane magnetization ([100]) andresult, our first-principles approach reveals aout-of-plane magnetization ([001]), MAE =potential to describe magnetic anisotropies ofE[100]-E[001]. To apply an EF, we used themagnetic thin film.

effective screening medium (ESM) method.

In

the

computational

approach,we

employed the plane-wave basis electronicSys.

structure calculation with using a scheme ofnon-collinear

spin

relativistic

ultra-soft

VCMA MCAE SMAE MAE(fJ/Vm) (mJ/m2) (mJ/m2) (mJ/m2)

fully

S-I [1]85

0.586

pseudopotential

S-II [1]

89

1.280

densityand(including spin-orbit coupling). This scheme

Exp. [2] ~300

can provide the magnetocrystalline anisotropy−−1.336 −0.750−1.053−0.227~ 0.500

Table I. Results of VCMA, MCAE, SMAE,
MAE(=MACE+SDA) and comparisons withexperimental results.

energy (MCAE) from the difference between
the total energy calculations for the different

52

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

with those from the density functional theory
(DFT)

based

on

generalized

gradient

approximation (GGA). Half-metallicity wasobserved, where the band energy gap appears
in the majority spin state. Such property at the
Fermi level is the reason why the material has
been considered as a candidate of spintronics
application. The QSGW indicated that the gap
is larger than that of the corresponding GGA
case. The QSGW may yield more localized
3d-orbitals, compared with those from the
GGA. Based on the projected density of states(PDOS) analysis, Co atoms of the octahedral
site

negligibleacontribution

to

the

total

of tetrahedral [Co(tet)] site (high spin state).

As shown in Table 1, the alloying system

The QSGW indicated the difference of(S-II) shows a perpendicular anisotropy

octahedral crystal fields on the different cation(positive value for MAE). The most importantsites of Co(oct) and Ni(oct). The electronic

key for the perpendicular is that the MCAE

states near the Fermi level consist mainly of

increases by the alloying of Fe-Cr. As depicted

Co(tet) 3d eg-orbitals. The comparison within Fig. 1, the increase appears at the interface

the results of one-shot GW reveals that thewith MgO layer. This means that the magnetic

self-consistent treatment introduces visible

anisotropy energy at the Fe/MgO interface ischanges in the electronic structures.

sensitive to the termination of Fe layer in thethin film.

References

GW[1] I. Pardede et al., Crystals 10 (2020) 1118.

(QSGW) ele-ctronic structure calculation [4][2] T. Nozaki et al., Phys. Rev. Appl. 5 (2016)

was performed in the spinel structures of044006.

ternary magnetic compound NiCo2O4, using[3] T. Oda and M. Obata, JPSJ 87 (2018) 064803.

the software ecalj. The QSGW method iselectronicbetotal magnetization is provided by Co atoms

for MgO).

ontomagnetization. The largest contribution to thetook into account the dielectric constant (9.8

state-of-the-art

found(low spin state) among them, resulting in a

To obtain the EF inside the MgO layer, weself-consistentwere

nonmagnetic/weak magnetic configuration

Figure 1. Atom resolved MCAE in (a)S-I and(b) S-II.

Quasi-particle[Co(oct)][4] T. Kotani et al., PRL 96 (2006) 226402.

structureinvestigation without using any empiricalparameter. The results were also compared53

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of first-principles electronic-structure
and transport calculation code RSPACE andsimulations for device
Tomoya ONO
Graduate School of Engineering, Kobe University
Rokkodai-cho, Nada, Kobe 657-8501

4H-SiC is one of the major enabling materials for advanced high power and high temperature electronics applications. However, theperformance of the metal-oxide-semiconductor
field-effect-transistor (MOSFET) using SiC isseverely limited due to their field-effect mobility being much lower than the ideal electron
mobility. SiC based MOSFETs are usuallyfabricated on the front side of 4H-SiC(0001)
wafer (Si face) by the thermal oxidation in
dry O2 ambience. On the other hand, it isreported that MOSFETs fabricated on the C
face, which is the back side of the same wafer,by wet oxidation in H2 O ambience contain low
density of interface defects and exhibit higher
carrier mobility than that on the Si face. Electrically detected magnetic resonance (EDMR)
spectroscopy revealed that characteristic defects, which are called “C-face defects”, are observed in the wet-oxidized C face[1]. However,the details of the generation of C-face defects
are unclear.
In this project, we have conducted firstprinciples study on the formation energy ofC-face defects at SiO2 /SiC(0001) interface.
RSPACE code[2, 3, 4], which is also developedin this project is used for the first-principles
calculations. The lateral lengths of the su√
percell are chosen to be 2 3a and 4a along
the [11̄00] and [112̄0] directions of the 4HSiC(0001) surface, where a is the lattice constant of SiC, and integration over the Brillouin zone is carried out using a 2 × 2 ~k-point

mesh. The surface C atoms are connected to
OH groups to imitate oxide and the Si atoms
are terminated by H atoms. For comparison,
the formation energy of the defects in 4H-SiC
bulk is also calculated. The dimension of the√supercell is 2 3a, 4a, and c along the [11̄00],[112̄0] and [0001] directions, respectively, withc being the lattice constant of 4H-SiC bulk.
The C face defects are CSi VC c-axial,
CSi VC basal, VSi VC c-axial, and VSi VC
basal defects. It has been reported that only
CSi VC c-axial and VSi VC basal are observedat the wet-oxidized C face among them. The
CSi VC defects are generated by removing a
Si atom and moving C atom to VC site fromthe neighboring C site. We remove Si atomfrom the first or second SiC bilayer. In addition, VSi VC defects are created by removing C
atoms at the Si site from the CSi VC defects.
The computational model for the case of theCSi VC c-axial defect is shown in Fig. 1. Table 1 corrects the formation energies and magnetic moments of the defects.
When Si atom in the first SiC bilayer of theinterface is removed, CSi VC basal, VSi VC caxial, and VSi VC basal defects are hardly generated because the dangling bonds of C atom
are passivated by the O atom which comesfrom the oxide layer. As a result, the formation energy of CSi VC c-axial defect, in which
Si atom at the first bilayer is removed, is themost stable among CSi VC defects. In the caseof the VSi VC defects, the formation energy

54Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 1: Formation energies Ef and magnetic moments of C-face defects. The zero of theformation energy is set at the lowest models among CSi VC (+) at the interface, CSi VC (+) in
bulk, VSi VC at the inerface, and VSi VC in bulk.
Defects
CSi VC (+) c-axial @ 1st layer
CSi VC (+) c-axial @ 2nd layer
CSi VC (+) basal @ 2nd layer
CSi VC (+) c-axial @ bulk
CSi VC (+) basal @ bulk
VSi VC c-axial @ 2nd layer
VSi VC basal @ 2nd layer
VSi VC c-axial @ bulk
VSi VC basal @ bulk

Formation energy (eV)
0.0
+0.92
+0.49
+0.10
0.0
+0.96
+0.49
0.0
+0.09

Magnetic moment (µB )
1
1
0
1
1
1
2
2
2

of the c-axial structure is lower than that of
the basal one. Although this result is not inagreement with the experimental result, themagnetic moment of the basal defect at theinterface corresponds with that in bulk while
the magnetic moment of the c-axial does not.
This indicats that our calculated results support the experimental situation.

References[1] T. Umeda, Y. Kagoyama, K. Tomita,
Y. Abe, M. Sometani, M. Okamoto, S.
Harada, and T. Hatakeyama, Appl. Phys.
Lett. 115, 151602 (2019).
[2] K. Hirose, T. Ono, Y. Fujimoto, and S.
Tsukamoto: First Principles Calculations
in Real-Space Formalism (Imperial College, London, 2005).
[3] T. Ono, M. Heide, N. Atodiresei, P.
Baumeister, S. Tsukamoto, and S. Blügel,
Phys. Rev. B 82, 205115 (2010).
[4] Y. Egami, S. Tsukamoto, and T. Ono,
Phys. Rev. Research 3, 013038 (2021).

Figure 1: Computational model for SiC/SiO2
interface with CSi VC c-axial defect. Blue,
brown, and red balls are Si, C, and O atoms,
respectively. The supercell contains 95 Si, 96
C, 16 O, and 32 H atoms. H atoms are used fortermination of dangling bonds at the surfaces.

55

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Analyses related to atomic structures and atom
dynamics at complex structures such as surfaces,interfaces and defects
Satoshi WATANABE
Department of Materials Engineering, the University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656

1

Introduction

The understanding on structures and dynamics at surfaces, interfaces and defects on
nanoscale is crucial to facilitate developmentsof novel information and energy devices. Firstprinciples calculation has sufficient accuracy of
prediction for this purpose, but its computational cost is often too high to model such devices realistically.
Keeping the above in minds, we have been
investigating atomic structures and atom dynamics in various systems via first-principles
calculations combined with multi-scale ormachine-learning approaches. In the following,some of our results in the fiscal year 2020 are
described.

2

Phase stability of Au-Li binary systems

Aiming to deepen our understanding on theoperation mechanisms of novel memory device named VolRAM [1] and all-solid-state Liion batteries, we examined Li ion distribution at the interfaces between γ-Li3 PO4 andmetal electrodes by combining first-principles
data of defect formation energies with a onedimensional continuum model [2] in the previous year. However, we have not achieved thorough understanding because of alloy formation
between Au and Li: The Au-Li binary system
is known to exhibit various alloy phases over awide range of compositional ratios. Therefore,
in the fiscal year 2020, we have explored thealloying properties of Au and Li [3].
For this purpose, we constructed ahigh-dimensional neural network potential (HDNNP) [4] based on density functional
theory (DFT) calculations. The predictions
by the constructed HDNNP on lattice parameters and phonon properties agree well withthose obtained by DFT calculations. The
predictions on the mixing energy of Au1−x Lix
also show excellent agreement with DFT
verifications. The lack of consensus on the
Au-Li stable phases in previous studies canbe understood from the existence of various
compositions with structures on and slightly
above the convex hull.
We have also examined the alloying process starting from the phase separated structure to the complete mixing phase by performing molecular dynamics simulations with theconstructed HDNNP. Our results reveal thatwhen multiple adjacent Au atoms dissolved
into Li, the alloying of the entire Au/Li interface started from the dissolved region.

3

Band alignment tuning via
thin-film insertion

Recently, interfacial resistance between the
Nb-doped SrTiO3 (STO) metal and a LiCoO2(LCO) mixed conductor has been found to de-56

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 1:
Calculated local density ofstates of (A) LiCoO2 (104)/SrTiO3 (001)and (B) LiCoO2 (104)/three unit cells of
LaAlO3 /SrTiO3 (001) along the Z-axis direction perpendicular to the interfaces [5].
crease significantly (by more than five orders ofmagnitude) upon the insertion of a 1 nm thickinsulating LaAlO3 (LAO) layer at the interface [5]. To clarify the origin of this behavior,
we have performed DFT+U calculations for
LCO/STO and LCO/LAO/STO heterostructures. In our calculation, we have adopted theundoped system for both LCO and STO, considering the fact that Nb-doping shifts only the
Fermi level, and the position of the conduction
band minimum, measured from the vacuum
level, is nearly the same between the undoped
and Nb-doped STO.
Figure 1 shows the local density of statesof the structurally optimized LCO/STO andLCO/3 unit cells of LAO/STO systems along
the Z-axis direction perpendicular to the interface. In the LCO/STO model, upward (downward) band bending of ∼0.20 eV (0.06 eV)near the interface on STO (LCO) is seen. The
difference in the valence band maximum energy of LCO and the conduction band minimum energy of STO was ∼1.8 eV. In contrast,
the energy level difference decreased to 0.28 eV
when 3 LAO unit cells were inserted at the interface. The linear change in the LAO band
level along the Z-axis shows the presence ofa built-in electric field. The electric field was
2.2 eV/nm (0.67 eV per LAO unit cell), whichis comparable to the values deduced from theexperiments [5] (0.4 eV per LAO unit cell).
The shift in the energy level via LAO insertion

suggests a reduction in the Schottky barrierheight.
We have also performed quantum mechanical calculations for electron tunneling bysolving the time-independent one-dimensional
Schrödinger equation with a simple model constructed based on the above behavior of bandalignment change due to the LAO layer insertion. The result reproduced the observed interfacial resistance change with the LAO layer
thickness: The 4 u.c. LAO case had a minimum resistance.
This study provides a proof-of-concept
demonstration of an approach to reduce theinterfacial resistance by tuning the Schottky
barrier at the interfaces of metals and mixed
conductors.

References[1] I. Sugiyama, R. Shimizu, T. Suzuki, K.
Yamamoto, H. Kawasoko, S. Shiraki, and
T. Hitosugi: APL Mater. 5 (2017) 046105.
[2] K. Shimizu, W. Liu, W. Li, S. Kasamatsu,
Y. Ando, E. Minamitani, and S. Watanabe: Phys. Rev. Mater. 4 (2020) 015402.
[3] K. Shimizu, E. F. Arguelles, W. Li, Y.
Ando, E. Minamitani, and S. Watanabe:
Phys. Rev. B 103 (2021) 094112.
[4] J. Behler and M. Parrinello: Phys. Rev.
Lett. 98 (2007) 146401.
[5] K. Nishio, T. Shirasawa, K. Shimizu, N.
Nakamura, S. Watanabe, R. Shimizu, and
T. Hitosugi: ACS Appl. Mater. Interfaces
13 (2021) 15746.

57Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical Approach to Reduce the Interface-State Density in
SiC-MOS Devices
Yu-ichiro MATSUSHITATokyo Institute of Technology, Ookayama Meguro-ku, Tokyo 152-8550
Theoretical

SiC power MOSFETs have shown

calculations

showedthat

remarkable energy-saving effects andcarbon-related defects were generated

havecommercialized.

near the interface under the temperature

However, the SiC/SiO2 interface, which

and oxygen partial pressure conditions

plays a fundamental role in SiC power

used in the actual experiments. In

MOSFETs, still has a high interfacial

particular, the residual carbon defects

defect density, and most of the inversion

distributed just at the interface werelayer carriers induced by the gate voltage

found to be stabilized and present inare trapped in the interfacial defects. In

large amounts. This calculation result

fact, only 10% of the theoretical electron

indicates that the formation of residual

mobility has been achieved in SiC-

carbonMOSFETs.

theenergetically stable and that thermal

microscopic

oxidation inevitably produces residual

already

In

been

order

interface-state

todensity,

reduceTherefore,

We have performed density-functional
toinvestigate

at

the

interfaceiscarbon defects at the interface.

identification of them is needed.

calculations

defects

wethoughtthattheformation of carbon defects due tothemicroscopic structure of interface defects.

thermal

One of the most promising candidates ofunavoidable, and we sought a way tointerface defects is the residual carbon-

overcome this problem. As a result, we

related defects at the interface. In thissucceeded in forming a high-quality

study, the stability of carbon-related

interface

defects distributed in three regions (SiC

eliminates the thermal oxidation of SiC

bulk, SiO2 film, and SiC/SiO2 justand removes the carbon defects near theinterface)on

SiC surface, followed by the formation oftemperature and oxygen partial pressure

an oxide film [2]. In the proposed process,were clarified by theoretical calculationsa Si thin film is deposited after hydrogenbased on density-functional theory [1].

etching and oxidized to SiO2 at a

and

their

dependence

58

oxidation

by

using

of

a

SiC

processwasthatActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

temperature where the oxidation of SiC
does not proceed. Subsequent nitridation
after the oxide film formation is effective
in reducing defects. The effectiveness ofthe proposed method was confirmed
experimentally,andahigh-quality

interfacial structure with an interfaciallevel density of (1-4) × 1010 cm-2eV-1,
which is one order of magnitude smaller
than the conventional 1011 cm-2eV-1, wasFig. 1: Successful reduction in interface-stateachieved.

density in SiC/SiO2

References[1] T. Kobayashi and Y. Matsushita, JAP,
126, 145302 (2019).

[2] T. Kobayashi, T. Okuda, K. Tachiki, K.
Ito, Y. Matsushita, T. Kimoto, APEX, 13,091003 (2020).

59

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-Principles Molecular-Dynamics Study of Structural andElectronic Properties of Covalent Liquids and Glasses under
Pressure
Fuyuki SHIMOJO
Department of Physics, Kumamoto University, Kumamoto 860-8555
For the investigation of the dynamic

constructed ANN potential precisely reproduces

properties of covalent liquids and glasses under

the FPMD results. The V-T relation calculatedpressure, it is important to consider the stabilityby the ANN potential trained with potentialof materials states under various conditions

energy only (E-fit) or with potential energy andfrom the viewpoint of free energy. We haveatomic forces (EF-fit) is completely different

been using the thermodynamic integration (TI)

from that by FPMD, though the E-fit method

method [1] for this purpose. The first-principles

gives almost correct V before melting. We also

molecular

simulations

found that the 128-atom system with 4k points

would be the most powerful and accurate toolfor Brillouin zone integration gives nearly

to perform TI calculations. Due to the highconverged results for the melting temperature.

dynamics(FPMD)

calculation cost, however, FPMD simulations
have been carried out only for small-sized
systems. One of the solutions to solve this costproblem is to use machine-learning interatomic
potential based on artificial neural networks(ANN) trained from the results of FPMD
simulations.
This study aims to establish the training
requirements

for

the

ANN

potential

toreproduce the phase properties of sodium as an
Fig. 1: Temperature dependence of volume V of
Na obtained by FPMD and ANN-MD
simulations.

example. Figure 1 shows the temperaturedependence of calculated volume V. The black
circles show V obtained by FPMD. It is seen

References

that, only when the virial stress tensor, as well

[1] D. Frenkel and A. J. C. Ladd, J. Chem. Phys.

as the potential energy and atomic forces, is81, 3188 (1984).

taken into account in the training (EFP-fit), the60Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Quantum Simulations on Dynamical Heterogeneous
Catalysts
J. I. ENRIQUEZ, H. H. HALIM, S. E. M. PUTRA, T. N. PHAM, Y. J. WONG,
Y. HAMAMOTO, K. INAGAKI, I. HAMADA, and Y. MORIKAWA
Department of Precision Engineering, Graduate School of Engineering,Osaka University, 2-1 Yamadaoka Suita, Osaka 565-0871

In 2020-2021, we carried out theoretical investigation of chemical processes at surfaces
and interfaces, oxidative etching process of diamond [1], multi-scale simulation of Cu adatom
diffusion on Cu surfaces [2], formic acid adsorption in polymeric form and decomposition
on Cu(111) [3], oxygen vacancy induced metalinsulator transition of LaNiO3 thin film over
SrTiO3 [4].
In this report, we report the oxidative etching process of the diamond (100) surface [1].
Diamond possesses a unique combination ofsuperlative properties that makes it an attractive material for several novel applications. Of
all semiconductors, diamond has the highest
dielectric breakdown field, saturated electron
drift velocity, and thermal conductivity whichmake it an ideal material for next-generationelectronics that will outperform current systems in terms of operating frequency andpower handling capacity. In addition, diamond’s wide band gap, optical transparency,chemical inertness, hardness, and low thermal
expansion have led to a number of specialized photonics applications including spacecraft window, optoelectronic microlens, photodetector, high energy particle detector, UV
and infrared LED, and Raman laser. Diamondhas color centers that functions as bright single photon source (SPS) at room temperaturesand can be potentially implemented in quantum metrology and quantum information science.

At present, a theoretical study that investigates the entire oxidation process, startingfrom the adsorption of gas phase O2 up to thedesorption of CO and etching of the surface,
has never been done. This kind of study isnecessary to develop a comprehensive knowledge of diamond oxidation mechanism. For
this reason, van der Waals-corrected density
functional theory simulations of the oxidationof the C(100) surface have been performed.
Density functional theory (DFT) calculations have been performed using STATE code
package (Simulation Tool for Atom TEchnology) with generalized gradient exchangecorrelation functional (GGA) based on thework of Perdew, Burke and Ernzerhof (PBE).
Semi-empirical van der Waals correction was
implemented. Core electrons were treated using ultra-soft pseudopotentials. Wave functions were expanded using plane-wave basiswith wave function and augmentation charges
cutoff of 36 Ry and 400 Ry, respectively.
We simulated the succeeding desorption of
CO up to the complete etching of the top C
layer. The reaction paths and optimized structures are shown in Fig. 1. Following the desorption of the first CO, there are two possible
locations where the second CO could desorb,
the adjacent CObridge towards the [011̄] direction where O is on top site and the CO fromthe adjacent ether group towards the [011] direction. The former and the latter have Ebarrierof 4.53 eV and 3.62 eV, respectively. Succeed-61Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

ing CO desorptions along [011] (Fig. 1 B-E)
all have lower Ebarrier compared to [011̄], suggesting a preferred etching direction. The calculated desorption activation energies vary between 1.01 - 4.68 eV. Initial desorption of CO
along a given row in [011] direction has thehighest desorption activation energy (reaction
A→ B and E → F), while succeeding energy
barriers are lower (Fig. 1 A-E, E-I). Analysis of the reaction path geometries shows thatfor these two reactions, the initial CO desorption proceeds by the near-simultaneous breaking of two CObridge-C bond. The point defectleft by the initial desorption allows the next
CObridge to break one bond with second layer
C and form CO on top (COtop ) structure. The
non-simultaneous bond breaking reduces theheat released by the reaction and the desorption activation barrier. This suggests that the
point defect functions as nucleation point for
CO desorption along [011] direction. This nucleation function was first proposed by Johnet al. based on their observation that the surface roughness of diamond (100) did not increase even after removal of over 5300 atomic
layers, suggesting that the removal rate of rowsof atoms is more rapid than the removal rate oflayers. Our work is the first theoretical study
to support their prediction.

In summary, we performed density functional theory calculations with van der Waals
corrections to elucidate diamond oxidation
mechanism on the atomic-level which could
lead to insights that will advance the improvement of nascent nanofabrication technologies.
We developed a comprehensive theory of oxidative etching of the diamond (100) surface,from the adsorption of gas phase O2 , including
details of metastable adsorption states, intersystem crossing, and induced surface dereconstruction, to the desorption of CO and CO2 ,complete etching of the top surface layer andits subsequent stabilization.

!

Figure 1: Etching of the top-layer atoms ofC(100)-(1 × 1): Obridge surface through successive CO desorption. The heat of reactions
and activation energies in electron-volts areshown in black and blue texts, respectively.
Physisorption energies of CO are shown in orange text. Grey and red spheres correspond tocarbon and oxygen atoms, respectively, while
the dangling bonds are represented by blue
cylinder.

References[1] J. I. Enriquez, F. Muttaqien, M. Michiuchi, K. Inagaki, M. Geshi, I. Hamada,and Y. Morikawa: Carbon 174 (2021) 3651.
[2] H. H. Halim, et al., : ACS Omega 6 (2021)
5183.
[3] A. Shiotari, S. E. M. Putra, et al., : Small,in press.
[4] H. D. Nguyen, et al., : Phys. Rev. B 102(2020) 165411.

62

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development and application of ﬁrst-principles
algorithms for long-range electron transport
simulation
Yoshiyuki EGAMI
Division of Applied Physics, Faculty of Engineering, Hokkaido University
Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628

In this subject, an eﬃcient computational
procedure based on the real-space ﬁnitediﬀerence formalism[1] was developed to evaluate the electron-transport properties of longsystems containing more than 105 atoms under the zero temperature and zero bias limits
in the steady state without accuracy deterioration. In the procedure, a transition region isrepresented by arranging multiple parts along
the transport direction. The Green’s function of the whole transition region extended
towards the transport direction was obtainedby recursively combining the Green’s functionsof the adjoining parts one by one. The computational cost for calculating the submatrices of
the Green’s functions required to estimate thetransport properties can be suppressed linearly
for the number of the combined parts.

To exemplify the eﬃciency of the proposed
procedure we demonstrate large-scale electrontransport calculations for BN-doped doublewalled carbon nanotubes composed of 196,608
atoms (Fig. 1), which make, to the bestof our knowledge, the largest system in theﬁrst-principles electron-transport calculation.
These works have been performed on System B
and System C of the Supercomputer Center,the Institute for Solid State Physics, the University of Tokyo.
6

Conductance (G0)

In recent years, a lot of ﬁrst-principles studies on various materials have been energetically
performed toward the development of novel
devices. First-principles calculations generally require a computational cost proportional
to the cube of the system size. In order toperform large-scale simulations, the development of O(N ) algorithms and the improvement of parallelization eﬃciency of parallel calculations have been promoted. So far, great
progress has been made in atomic structure
calculations and electronic structure calculations, but reducing the computational cost remains a major issue in electron-transport property calculations.

54

㻌 periodic doping㻌 random doping

3
2
1
0
-1.0

-0.5

0.0

0.5

1.0

Incident Energy from the Fermi level (eV)Figure 1: Conductance trace of BN-doped
double-walled carbon nanotubes consisting of
196,608 atoms.

References[1] Y. Egami, S. Tsukamoto and T. Ono:
Phys. Rev. Res. 3, 013038 (2021).

63

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo“Prediction of hydrogen function by advanced
calculation of solids containing hydrogen”“Development of data assimilation method for crystal
structure prediction and its application to hydrogencontaining compounds”
Shinji TSUNEYUKI
Department of Physics, School of Science,
The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo 113-0033
Institute for Solid State Physics,
The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581
One of the most challenging problems in

crystal structure determination of materials

first-principles simulations of materials is tofound by high-pressure experiments where thepredict crystal structure by searching the global

range of the diffraction angle is limited or thoseminimum in multi-dimensional potential energy

containing hydrogen atoms whose positions are

surface (PES). It takes a sizeable computationaldifficult to be determined by X-ray diffraction.

cost to calculate the electronic energy of even a

The data assimilation method might accelerate

single atomic configuration from first principles.

materials exploration in combination with

It is, therefore, practically difficult to find the

combinatorial synthesis and measurement.

most stable crystal structure when the number ofThis year, we showed that the method is very

atoms in the unit cell is large and when PES has

robust against noise in the experimental data if

many local minima.

we tune the control parameter representing the

The problem is partially solved by a data

weight of the data assimilation [2].

assimilation method which we have proposed

We also extended the method to assimilate[1]. In the data assimilation method, we

multiple experimental data, such as X-ray andincorporate powder diffraction data to constrain

neutron diffraction data, at the same time. Bothsearch space based on Bayes’ theorem, by whichreflect the same interlayer distances of thewe can drastically accelerate finding a probable

crystal but with different peak intensities, giving

crystal structure. The method is valid even if theus more information. We applied this method todiffraction data is incomplete and is insufficient

Zn(OH)2 to confirm that using both sets of data

for structure determination by ordinary data

significantly improved the success rate of crystal

analysis methods. Typical applications are

structure prediction [2].

64Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Then we applied the method to two systems
containing a considerable number of atoms in aunit cell. The first one is a Li-ion conductor
LiCB9H10. The Li-ion conductivity of thismaterial is known to increase two orders ofmagnitude at around 330-360K. Still, theFig. 1 Top and side views of a theoretically
predicted structure of CaxAlyHz. Large,
middle and small spheres denote Ca, Al andH atoms.

mechanism and associated crystal-structurechange have not been clarified yet. From oursimulation, the difference in the crystal structure
below and above the transition temperature is

These works have been done in collaboration

essentially the orientation and rotative motion ofwith the experimental groups of the Grant-in-)- complex ions. Since the diffusive

Aid for Scientific Research on Innovative Areas

the (CB9H10

motion of Li ions is strongly correlated with the"Hydrogenomics:

Creationof

Innovativerotation of a nearby complex ion (CB9H10)-, it isMaterials, Devices, and Reactive Processes

greatly enhanced by its rotation in the high-using Higher-Order Hydrogen Functions" (FY

temperature phase [3].

2018-2022).

The second is a metal hydride CaxAlyHz
newly synthesized at high pressure. Although

References

powder X-ray diffraction data is available, the[1] N. Tsujimoto, D. Adachi, R. Akashi, S.

unit cell seems to be quite large, and neither its

Todo and S. Tsuneyuki, Phys. Rev. Materials 2,

accurate chemical composition nor the crystal

053801 (2018).

structure is clarified experimentally. We tried its[2] S. Yoshikawa, Ph.D. dissertation (Thestructure determination and found a plausible

University of Tokyo, 2021); S. Yoshikawa etmodel containing more than one hundred atomsal., in preparation.

in a unit cell, as shown in Fig.1 [2,4][3] R. Sato et al., in preparation.
[4] R. Sato et al., in preparation.

65

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First Principles Studies on Atomic and Electronic Structuresof Impurity-Screw Dislocation Complexes in GaN
Kenji Shiraishi
Institute for Materials and Systems for Sustainability,
Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601
Recentexperimentssuggestthat

Mg

We find that threading screw dislocations

condensation at threading screw dislocationsindeed attract Mg impurities as shown in Fig.2.

(TSD) induces current leakage, leading todegradation of GaN-based power devices. To
investigate this, we performed first-principles
total-energy calculations for various Mg anddislocation complexes. Figure 1(a) shows an
atomistic

configuration

of

a

TSD.

The
Fig. 2. (a) Binding energies of the Mg-TSD
complexes of the D<0|2>, S<0|6>, and S<0|3>
cores. dMg-dis is the distance of the Mg from thedislocation line. (b)–(d). The most stable core
structures of the Mg–TSD complexes of theD<0|2>, S<0|6>, and S<0|3> cores, respectively.
The position of the Mg atom is inindicated by theorange sphere. A red cross denotes the position ofa dislocation line.

dislocation has the Burgers vector of [0001]. To
model the TSD, the atoms are initially aligned ina helical manner along the [0001] dislocation
line.34,35 A periodic boundary condition is then
imposed on all axes of the system. The system
contains 812 Ga and N atoms in total, and avacuum layer is added on lateral planes

These findings provide a picture in which theperpendicular to the [0001] direction [Fig. 1(b)].

Mg, being a p-type impurity in GaN, diffuses
toward the TSD and then locally forms an n-type
region. The appearance of this region along the
TSD resultsin local formation of an n–n junction
and leads to an increase in the reverse leakage
current.

Fig. 1. (a) Model of a TSD. The Burgers vector is [0001],

References

and the dislocation line runs along [0001]. Green andblue spheres are Ga and N atoms, respectively. Thelarger
spheres highlight the dislocation core. (b) Schematic of
the [0001] plane of the unit cell. The green region
represents GaN, surrounding which is thefictitioushydrogen. The outermost region is vacuum. The
red cross indicates the position ofthe dislocation line.

[1] T. Nakano,Y. Harashima, K. Chokawa, K.
Shiraishi, A. Oshiyama, Y. Kangawa, S.
Usami,N. Mayama, K. Toda, A. Tanaka, Y.
Honda, and H. Amano, Appl. Phys. Lett., 117,012105 (2021).

66

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical Studies on Semiconductor MOVPE GrowthBased on Multi-Physics Simulation
Kenji Shiraishi
Institute for Materials and Systems for Sustainability,
Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8601
We examined the main reaction pathway ofobtained in our study shows that when H2 isthe TMG (Ga(CH3)3) decomposition processes

sufficiently present as a carrier gas, amino

[1].

the

groups, which are responsible for the formation

decomposition rate from the Gibbs energy ofof a wide variety of polymers, are difficult toactivation and calculated the mole fraction ofform. Therefore, we were able to reduce theeach chemical species. Asa result, in B3LYP, thenumber of chemical reactions considered indecomposition pathway of TMG

is theconventional fluid simulations. GaH3 molecules

sequential reaction with NH3followed by themust be considered in the surface reaction ofreaction with H2. In M062X, the decomposition

GaN MOVPE. Furthermore, it may be effective

proceeds through repeated reactions with NH3 as

to decompose TMG at ahigh temperature ofin the previous study. Using the reaction rates weabout 1300 K for a certain period of timet oobtained, we calculated the mole fractions ofcontrol carbon contamination..

We

calculated

andcomparedeach chemical species at 1300 K. It was foundthat GaH3 was the most abundant species in
B3LYPand Ga(NH2)3 in M062X. When we
tested the difference between the two exchangecorrelation functions using the high precision
CCSD method, it was found that the results of
the CCSD method were closer to those of B3LYP.

Fig. 1: Mole fraction of each chemical species after
1s at 1300 K and main reaction pathway of TMGa
decomposition written in red obtained by the firstprinciples calculations. [Ref.1]

Moreover, the experiment also supports thereaction paths obtained byB3LYP. Therefore, themain reaction pathway of TMG decomposition

References

is shown in Fig.1: Ga(CH3)3 → Ga(CH3)2NH2 →[1] S. Sakakibara, K. Chokawa, M. Araidai, A.

Ga(CH3)2H → GaCH3HNH2 → GaCH3H2 →Kusaba, Y. Kangawa, and K. Shiraishi, Jpn. J.

GaH2NH2 → GaH3. The main reaction pathway

Appl. Phys. 60, 045507 (2021).

67

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Mechanisms of Chemical Reaction of β-diketones Moleculeswith a Metallic Nickel Surface in Thermal Atomic Layer
Etching Processes
Satoshi HAMAGUCHI
Center for Atomic and Molecular Technologies,
Osaka University, 2-1 Yamadaoka, Suita, Osaka 567-0871
Thermal atomic layer etching (ALE) is one

the mechanisms of decomposition ofof the key manufacturing technologies for

β−diketones molecules – such as; hexa-

nano-scale electronic devices [1] as it canfluoroacetylacetone

be used for precise and damagelessacetylacetone (tfacH), and acetylacetone

etching of metals. Thermal ALE of Ni(acacH) – on a metallic Ni surface and thewith hfacH starts with the deprotonation

effectof hfacH molecules after oxidizing the Ni

decomposition concerning thermal ALE.

surface.

By

increasing

the

of

surface(hfacH),roughnesstrifluoro-

on

the

surface

My research assistant A. H. Basher has usedtemperature in the range of 300 ~ 400 °C,

ISSP supercomputer to study the chemicalvolatile nickel complex Ni(hfac)2 andreaction of hfacH, tfacH, and acacH

water H2O molecules are formed on themolecules on flat and rough metallic Ni

surface and remove the NiO layer. In thissurfaces. In this study, we employ van derprocess, once a new metallic Ni surface

Waals (vdW) inclusive [7] periodic density

appears, no further etching occurs, whichfunctional theory (DFT) to investigate theensures the self-liming nature of theadsorption and reaction of hfacH on a metallic

thermal ALE process [2-5]. It has been

Ni surface, and clarify the surface chemistry in

known experimentally [5,6] that, when

the atomic layer etching (ALE) process of Ni.

hfacH molecules are supplied to a metallic

We

Ni surface, they decompose and form

pseudopotential code STATE [8]. In ourneither Ni(hfac)2 nor H2O molecules, andcalculation, we have used 5 nodes for eachas a result no etching of Ni takes place.

submitted jobs to run the calculations on 120

The origin of the self-limiting process inprocessors parallelly and more than 1800 hours

the thermal ALE of Ni with hfacH

has been consumed.

used

our

in-houseplane-wave

exposure was discussed in an earlier

We have investigated several adsorption sites

study[4]. The aim of this work is to clarify

to find the most stable one thermodynamically68

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

with and without vdW forces. Second, thehavedissociationwas

nature of thermal ALE for Ni withinvestigated using nudged elastic band (NEB)

β−diketone gases in general, which ismethod as well as climbing image NEB (ciNEB)

consistent

to get more accurate results. Third, theobservations [5,6].

dissociation

References

C-F

bond in

bond

of

O-H

hfacH

in

hfacH

demonstrated

with

the

earlier

self-limiting

experimental(deprotonation) was studied by two methods: a)[1] G. S. Oehrlein and S. Hamaguchi, Plasmachecking

Sources Sci. Technol. 27, 023001 (2018).

thedeprotonation

manuallybyincreasing the distance between O and H atoms.

[2] A. H. Basher, M. Krstić, T. Takeuchi, M.

b) using NEB then ciNEB methods that is still

Isobe, T. Ito, M. Kiuchi, K. Karahashi, W.

running.
Ithasphysisorption

been

found

energiesthatofWenzel, and S. Hamaguchi, J. Vac. Sci. Technol.

theA 38, 022610 (2020).

those[3] A. H. Basher, M. Krstić, F. Karin, T. Ito, K.

β−diketones are almost the same while

Karahashi, W. Wenzel, and S. Hamaguchi, J. Vac.

the chemisorption energy is higher for aSci. Technol. A 38, 052602 (2020).

β−diketone with a higher polarity and thevan der Waals forces play a decisive role[4] A. H. Basher, I. Hamada, and S. Hamaguchi,,in determining the adsorption energy. The

Jpn. J. Appl. Phys. 59, 090905 (2020).

dissociation processes of β−diketones have[5] T. Ito, K. Karahashi, and S. Hamaguchi, Proc.

been studied with a climbing imageof the 39th Int. Symp. on Dry Process (DPS2017)

nudged elastic band method, which has(Tokyo, Japan, 2017) 45, 2017.

shown the cleavage of a C-F bond of a[6] H. L. Nigg and R. I. Masel, J. Vac. Sci.

β−diketone is more likely to take place

Technol. A 17, 3477, (1999).

than the deprotonation. The surface
roughness can also help to form C-Ni

[7] I. Hamada, Phys. Rev. B 89, 121103 (2014).

bonds, which were also observed in[8] Y. Morikawa, H. Ishii and K. Seki, Phys. Rev.

experiments. In this way, our simulations

B, 69 (2004) 041403.

69

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Thermodynamic properties of icy materials
in the interior of planets and satellites
Yu Komatsu
Astrobiology Center / National Astronomical Observatory of Japan,
Osawa 2-21-1, Mitaka, Tokyo, Japan.

In this study, the equation of state (EOS) ofhydrogen sulﬁde under high pressure is investigated, which is applicable to predicting theinternal structure of icy satellites, such as Europa, and icy planets. H2 O, NH3 , CH4 andH2 S are thought to be the typical icy materials, reﬂecting conditions before establishing
the planetary system [1]. We focus on thermodynamical properties of hydrogen sulﬁde as thecomponent, whose property under high pressure and low temperature has been investigated well due to its superconductivity, butthere are no studies under a wider range oftemperature and pressure.
DFT-MD calculations of hydrogen sulﬁdesystems with a large parameter space withtemperature and density were performed using
Quantum ESPRESSO. As initial conﬁgurations, not only typical structures of hydrogensulﬁde but also the Cmca and P1 structures,
which were obtained by the structure prediction, were selected because they were suggested to be stable under higher pressure [2].
Figure 1 shows self-diﬀusion coeﬃcients
caluculated for the Cmca structure from 500
to 10,000 K, as a function of the density. Inhigh temperature ranges above 5,000K, the diffusion coeﬃcients as well as radial distributionfunctions starting from diﬀerent initial structures converged to nearly identical values atgiven temperature and density. These analyses
would be a good basis for further reﬁnement of
the new EOS for icy bodies, as the next stepof our study.

Figure 1: The self-diﬀusion coeﬃcient for thehydrogen atom (a) and the sulfur atom (b) as
function of the density of the Cmca structurewith four diﬀerent temperatures (500, 1,000,
5,000 and 10,000 K).

References[1] T. V. Johnson et al., ApJ 752, 192 (2012).
[2] Y. Li, et al., J. Chem. Phys. 140, 174712(2014).

70

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Electrochemical reaction analysis using density functional
calculation + implicit solvation model 2
Jun HARUYAMA
Institute for Solid State Physics,
The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581
The rechargeable Li-ion battery (LIB) is a

F = EDFT + Fvib – TSconf(2)

successful energy storage device due to its highwhere F are the free energies of LIG atenergy density and long cycle life. In order tocomposition LixC6, metal Li, and AB stacked

improvequantitativegraphite C6. Free energy is represented as theunderstanding of elementary reactions in thefollowing three terms: DFT total energy EDFT,

LIB such as the reaction of Li intercalation

vibrational free energy Fvib, and configu-

from electrolyte solution into graphite andrational entropy term TSconf.

crystal structure change in graphite during theAtomic configurations and cell parameters ofreaction must be a great help. In previous

Li/6C, Li/9C, Li/12C, Li/18C, Li/24C, andstudies, we have studied charge transfer

Li/36C in-plane structures (see Fig. 1a) werereactions at electrode/solution interfaces in Li-

investigated within van-der-Waals (vdW) levelion batteries (LIB) using density functional

DFT calculations. Interlayer configurations

theory (DFT) calculations combined with

were set to AA, AB, and mix stacking (Fig. 1b).

implicit solvation model. [1–4]

Mix stacking is defined that Li-intercalated

Structure change of Li-intercalated graphite

layers were set to AA stacking and the other(LIG) during the charge/discharge processes

layers were AB stacking. We performed spin-

was recently observed by operando X-ray

unpolarized density functional theory (DFT)diffraction measurements using a synchrotron

calculations with Quantum ESPRESSO (QE)radiation at SPring-8. [5, 6] The operando XRD

package. [7]data cannot explained by conventional staging

The vibrational free energy was approximatedmodel for LIG. To compare and discuss theseby using independent harmonic oscillators

experimental

first-

representation. In this representation, phonon

principles calculations for the phase stability ofdensity of state (DOS) was obtained from

LIG.

density functional perturbation theory (DFPT)

Formation free energy ∆Ff is defined as

implemented in QE. Lattice gas model of∆Ff (LixC6) = F(LixC6) − xF(Li) − F(C6) (1)suitableits

performance,

results,

weconduct

71

constraint

wasappliedtotheActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

configurational entropy term.
Figure 1c shows the calculated formation freeenergies. LiC6, Li1/2C6, and Li1/3C6 stablestructures are AA-stack Li/6C stage1, stage2,
and AA stack Li/9C stage2, these structures are
consistent with experiment. [1] AB stacking isstable at the region of x < 0.05 in LixC6. Weemphasize that formation energies using only
DFT term failed to describe higher stage region(C6 – Li1/3C6) especially Li1/3C6 and AB
stacking cannot become convex hull. The
calculation also shows the existence of mix
stacking at intermediate region (0.05 < x < 0.3).
The expected AB–mix phase transition isslightly different from AA–AB phase transition

Figure 1: (a) In-plane configurations of Li/6C,

at x ≈ 0.1 suggested from X-ray diffraction

Li/9C, Li/12C, … structures. (b) Interlayer

analysis. [1] Finally, the computational AB–

configurations of AA and AB stackings. (c)mix phase transition well explained the entropy

Formation

behavior comparing with electrochemicallydiamonds, and crosses) and convex hull (blackobserved entropy. [8, 9]

solid line) obtained from eq. (1).

freeenergies(closedcircles,

References[1] J. Haruyama, T. Ikeshoji, and M. Otani, J.

[6] H. Fujimoto et al., The 59th Battery

Phys. Chem. C 122, 9804 (2018).

Symposium, 2E16 (2018).

[2] J. Haruyama, T. Ikeshoji, and M. Otani,[7] P. Giannozzi et al., J. Phys.: Condens.

Phys. Rev. Mater. 2, 095801 (2018).

Matter 21, 395502 (2009); ibid 29, 465901[3] M. Otani and O. Sugino, Phys. Rev. B 73,(2017).

115407 (2006).

[8] R. Yazami and Y. Reynier, J. Power Sources[4] S. Nishihara and M. Otani, Phys. Rev. B 96,

153, 312 (2006).

115429 (2017).

[9] J. Haruyama, S. Takagi, K. Shimoda, I.

[5] S. Takagi et al., The 60th Battery

Watanabe, K. Sodeyama, T. Ikeshoji, and M.

Symposium, 1B20 (2019).

Otani, in preparation.

72

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study of ferromagnetism in Pt(100) thin films by firstprinciples calculation
Tatsuru Yamada1, Hiroyuki Kageshima2, and Tetsuya Sato1
1Department of Applied Physics and Physico-Informatics, Keio University, 3-14-1 Hiyoshi,
Kohoku-ku, Yokohama 223-0061, Japan
2Graduate School of Natural Science and Technology, Shimane University, 1060
Nishikawatsu-cho, Matsue 690-8504, Japan

Recently,It

wasreported

thicknessthatdependence

of

the

magnetic

appears in an oscillatory

moment of Pt. As a result of the calculations

manner in the Pt(100) thin films depending onof electronic structures for the free-standing

the film thickness[1][2]. However, few studies

Pt(100) thin films from 2 monolayers(ML)have focused in the ferromagnetism in Pt(100)up to 17 ML, it was confirmed thatthin film and the mechanism for appearance offerromagnetism appeared in an oscillatory

ferromagnetism in Pt(100) thin film remains

manner with a period of 6 ML (Fig. 1). By

unclear. In this study, we performed the first-

examining the energy band structure, we

principles calculations of freestanding Pt(100)found that the flat band near the Γ point

thin films to understand the mechanism forcomposed of 5𝑑𝑥𝑧,𝑦𝑧 orbitals overlaps withappearance of ferromagnetism in Pt(100) thin

Fermi

film. We performed first-principles calculations

appears. This flat band is the quantum wellbased on the density-functional theory with theband (Fig. 2).

ferromagnetism

energy(𝐸F)whenferromagnetism

generalized gradient approximation. Projector-

From the phase model, the period at which

Augmented Wave method was adopted as thethe quantum well band in Pt(100) thin film

pseudopotential of Pt. We used 88×88×1 koverlaps with 𝐸F is 5.7 ML[1]. This ispoints (based on Monkhorst-Pack) and aconsistent with experimental result of thecutoff energy of 36 Rydberg.

previous research[2] and calculated results. So,We

calculated

latticeconstant

that

it was concluded that oscillatory magnetic

minimizes the energy. Using the obtained

behavior in Pt(100) thin film can be explained

lattice constant, we calculated the Pt layer

by quantum well states.

73

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Fig. 2: Band structure of 3ML Pt(100) thin film.

Fig. 1: Magnetic moment per Pt atom inPt(100) thin films (circles) and total energy
differences between the paramagnetic (para)

References

and ferromagnetic (ferro) states (diamonds).

[1] A. M. N. Niklasson et al.: Phys. Rev. B 75,
172402 (2007).
[2] K. Ochiai et al.: JPS2019, Gifu, 10aPS27(2019).

74

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Born-Oppenheimer MD Simulations of Excited States for
Firefly Oxyluciferin Anions in Aqueous Solutions
Yoshifumi NOGUCHI
Department of Applied Chemistry and Biochemical Engineering, Graduate School ofEngineering, Shizuoka University, Johoku 3-5-1, Hamamatsu, Shizuoka 432-8561, Japan
statesFirefly oxyluciferin anion, known as the

BOMD

simulations

showedthatlight emitter in firefly bioluminescence process,phenolate-keto was the most stable isomers,has garnered significant attention because

whose energy was 0.38 eV and 0.57 eV lower

obtaining a deep insight on oxyluciferin anions

than that of the phenolate-enol and phenol-

could be an essential first step towards

enolate, respectively [3]. We analyzed theunderstanding the mechanism of the fireflytrajectories in detail and elucidated that thebioluminescence process. However, majority ofstabilizing mechanism of the oxyluciferinstabilizingofanions in the explicit aqueous solutions is theexternaldifference between at the ground and excitedoxyluciferin

andopticalanionsproperties

in

the

states.

environments are still a mystery.

Cumulative average for BLYP total energy (eV)We have performed first-principles BornOppenheimer molecular dynamics simulations(BOMD) for three possible isomers of firefly
oxyluciferin anions (phenolate-keto, phenolateenol, and phenol-enolate) surrounded by 64
explicit water molecules and elucidated theirstabilizing mechanism in the aqueous solutions-33272.3
HO-33272.4

ENOLATE

S

N

N

S

O-

-33272.5

0.19 eV-33272.6-33272.7-33272.8-O

ENOL-33272.9

S

N

N

S

OH

0.38 eV-33273.0-33273.1-O-33273.2-33273.3

1660

KETO
1680

1700

S

N

N

S

1720

O

1740

Time (ps)

1760

1780

1800

in the excited states. To attain the equilibrium

Fig. 1. Cumulative average for BLYP

conditions, we had to run BOMD up to 1.8 ns

total energies.

(corresponding to 3.7 million MD steps).

References

Figure 1 shows the cumulative average for[1] Y. Noguchi, et al., J. Phys. Chem. B, 120,

BLYP total energies simulated for phenolate-8776 (2016).

keto,[2] Y. Noguchi, et al., J. Chem. Theor. Comput.,

phenolate-enol,

andphenol-enolate.

Unlike similar level BOMD simulations in the15, 5474 (2019).

ground state in which the phenolate-enol form

[3] Y. Noguchi, et al., J. Chem. Phys., 153,

was the most stable [1,2], the current excited

201103 (2020).

75

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Analysis of Thermoelectric Properties of Clathrate Compounds with Ab
Initio Calculations
Masato OHNISHI
Department of Mechanical Engineering,
The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656

compoundsarealuminumcandidates

forenhance

Clathrate
promising

substitutions

canthermoelectric

thermoelectric materials in terms of

performancethe “electron-crystal phonon-glass”

clathrates, type-I Ba8Ga16Si30 (Fig.

concept. Clathrate compounds are

1(a)).

composedatoms

thermoelectric figure of merits (ZT)

encapsulated in cagelike structures.

with those obtained in experiment,

It is expected that electrons can

we concluded that (a) aluminumsmoothly transport in the frame

additive enhances ZT with lowering

work while phonons are scattereddopingby guest atoms. Particularly, insuppression of doping level can

type-I clathrate compounds, guest

enhance

atoms

investigate

ofvibrate

guest

in

a

strongofsilicon-based

Comparinglevel

calculated

and

ZT

(b)

furthersignificantly.

To

thermoelectricanharmonic potential because they

properties, we obtained possible

are composed of a Weaire-Phelan

structures at finite temperatures

structure, which divides a spacewith using a cluster expansion andwith the maximum volume with theMontesame cross-sectional area. While off-

thermoelectric

properties

center clathrates such as type-I

averageddifferent

Ba8Ga16Sn30, in which guest atoms

structures. As shown in Fig. 1(b),vibrate in a double-well anharmonicformationenergies

potential,

thermalstructurescansilicon-based

predicted

withclathrates are preferable for actual

expansionuse in terms of the material cost.

properties of the clathrates wereconductivity,

have

low

In this study, we show thatCarlocalculated

76

methods

for

of

be

using

and
were

possiblearbitraryaccuratelythemethod.
with[1]cluster
Phononaself-

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

consistentphonon

(SCP)

based

on

first-principles

calculations[2].

theoryconcentration, as shown in Fig. 1(c).

WhileReferences

carrier[1] M. Ångqvist, P. Erhart et al., Chem.

concentrations are around 1022 cm-3

Mater. 29, 7554 (2017) and 28, 6877

for Si-based clathrates, our analysis(2016).

shows[2] Tadano et al. Phys. Rev. Lett 120,experimentally-observed

that

thermoelectric

properties of the clathrate can be105901 (2018).

improved by suppressing carrier

Fig. 1. Enhancement of thermoelectric properties of Si-based Clathrate. (a)Crystal structure of Ba8Ga16Si30. (b) Prediction of formation energy with acluster expansion method. (c) Dimensionless thermoelectric figure-of-merit(ZT) of the clathrate at different carrier concentrations.

77

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles calculation for low-temperature oxygen
transfer in metal oxide
Akira Yoko
WPI-Advanced Institute for Materials Research,
Tohoku University, Katahira 2-1-1, Sendai, Miyagi 980-8577
relaxed within a cubic cell, and the lattice

We have studied oxygen storage and releasematerials experimentally and computationally.

parameters of perfect CeO2 and Cr-doped CeO2

This term CeO2 and Cr-doped CeO2 were

were obtained using the Murnaghan equation ofstudied with first-principles calculations.

state. Forces were converged to 0.01 eV/Å inPlane-wave basis density functional theory

all calculations.

(DFT) calculations were conducted to elucidate

Nudged elastic band (NEB) calculations

the Cr doping effects on CeO2 structure using

were performed to obtain diffusion paths andthe VASP code [1,2]. The generalized gradientbarrier energies with seven replicas, including

approximation (GGA) proposed by Perdew,

five nudged intermediate images. The spring

Burke, and Ernzerhof (PBE) [3] was employed

constant linking images was 5.0 eV/Å and theas the exchange correlation energy functional.

conversion criteria were defined that resultant

The DFT+U method introduced by Dudarev etforces, including the spring forces, were lessal. [4] was used to treat the electron

than 0.01 eV/ Å. The energy barrier was

localization. The parameter, U-J was set as 3.5

obtained by applying the climbing imageeV for Cr3d, 5.0 eV for Ce4f, and 5.5 eV for

algorithm [7], which allowed the determination

O2p states, respectively, based on the previousof the saddle point at the transition state.

studies of Cr2O3 and CeO2 [5,6]. The valence

To elucidate the mobility of oxygen for pureconfigurations of the pseudopotentials were

and Cr-doped CeO2, nudged elastic band

3s23p63d54s1 for Cr, 5s25p64f15d16s2 for Ce andcalculation was conducted. Figures 1a and 1b

2s22p4 for O. The energy cutoff for the plane-show the diffusion path of an oxygen atom towave basis was set at 500 eV for all thethe vacancy site and migration barrier.

calculations and provided the convergence ofCompared to pure CeO2 (0.41 eV), a muchthe total energy in the unit cell of CeO2 (12lower migration barrier was observed in Cr-

atoms). Defect calculations were conducted

doped CeO2 (0.28 eV). In the case of the pureusing the 2 × 2 × 2 extension (96 atoms) ofCeO2, electron polaron (Ce3+) exists at the next

CeO2 unit cell with Monkhorst–Pack k-pointnearest neighbor of the oxygen vacancy, andmesh of 4 × 4 × 4. Atomic positions werediffusion of the polaron accompanied with78

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

oxygen diffusion was observed; Rapid polarondiffusion in reduced CeO2 has been discussed

References

previously [11]. As a result of the NEB[1] Kresse, G.; Furthmuller, J., Phys. Rev. B

calculation, diffusion constants at 400 °C are

1996, 54 (16), 11169-11186.

5×10-11 m2 s-1 for CeO2 and 5×10-10 m2 s-1 for[2] Kresse, G.; Joubert, D., Phys. Rev. B 1999,

Cr-doped CeO2. The high diffusivity of oxygen

59 (3), 1758-1775.G. [3] Perdew, J. P.; Burke,

in Cr-doped CeO2 is one of the origins to cause

K.; Ernzerhof, M., Phys Rev Lett 1996, 77 (18),high oxygen mobility at low temperature

3865-3868.

observed in the experiments. This result was[4] Dudarev, S. L.; Botton, G. A.; Savrasov, S.

published in ref. [12].

Y.; Humphreys, C. J.; Sutton, A. P., Phys. Rev.

(A)

B 1998, 57 (3), 1505-1509.
[5] Wang, J.; Gong, X.-Q., Appl. Surf. Sci.
2018, 428, 377-384.
[6] Keating, P. R. L.; Scanlon, D. O.; Morgan,
B. J.; Galea, N. M.; Watson, G. W., J. Phys.
Chem. C 2012, 116, 2443-2452.
[7] Henkelman, G.; Uberuaga, B.P.; Jonsson,
H., J. Chem. Phys. 2000, 113 (22), 9901-9904.
[8] Wang, B.; Xi, X.; Cormack, A. N., Chem.
Mater. 2014, 26, 3687-3692.

(B)[9] M.V. Ganduglia-Pirovano, J.L. Da Silva, J.
Sauer, Phys. Rev. Lett., 102 (2009), Article
026101[10] Yu, M.; Trinkle, D. R., J. Chem. Phys.
2011, 134, 064111.
[11] Nakayama, M.; Ohshima, H.; Nogami, M.;
Martin, M., Phys. Chem. Chem. Phys., 2012,
Figure 1 Energy barrier of oxygen atom

14, 6079-6084.

diffusion to a vacancy site obtained by NEB[12] X. Hao, A. Yoko, K. Inoue, Y. Xu, M.

calculation for (A) CeO2 and (B) Cr-doped CeO2.

Saito, C. Chen, G. Seong, T. Tomai, S. Takami,

Light green, sky blue, dark blue, red, and

A.L. Shluger, B. Xu, T. Adschiri, Y. Ikuhara,,orange balls represent Ce4+ ion, Ce3+ ion, Cr, O,

Acta Materialia, 203, 116473 (2021)

and diffusing oxygen, respectively.

79

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Reduction of Rare Metals in Formic Acid Decomposition
Catalysts and Oxygen Storage Materials
Yuji KUNISADA
Center for Advanced Research of Energy and Materials, Faculty of Engineering,
Hokkaido University, Sapporo, Hokkaido 060-8628
We investigated the catalyst adsorption

reaction activities. We found that the stableand diffusion properties on light-element

Cu atoms embedded in graphene show higher

element doped graphene with the aid of theactivity than unstable Cu clusters on graphene.

first-principles calculation based on the

We investigated the oxygen absorption

density functional theory (DFT). Besides, weproperties of partially substituted Ca2AlMnO5.

investigated the oxygen absorption properties

We revealed that rotation of coordinationof heteroatom-substituted brownmillerite-type

polyhedra of cations releases the distortionoxides.

induced by heteroatom doping. In addition,

At first, we investigated the stabilities of

we investigated the effects of Pt addition on

Cu atoms embedded in light-element doped

oxygen storage properties.

graphene. We considered embedded Cu atoms

We also studied the adsorption properties

coordinated with various substituted dopants.

and catalytic activities [3] and chemical

We performed the total energy and electronicbonding states [4] of Pt sub-nano clusters on

structure calculations using The Vienna Ab

light-element element doped graphene.

initioReferences

simulation

package(VASP).

We

installed a parallelized VASP with Intel® MPI[1] J. S. Yoo, F. A.-Pedersen, J. K. Nørskov, F.

Library and Intel® Math Kernel Library. We

Studt, ACS Catal. 4 (2014) 1226.

revealed that the stabilities of Cu atoms[2] A. Sato, G. Saito, K. Abe, Y. Kunisada, N.

embedded in light-element doped graphene

Sakaguchi, T. Akiyama, T. Nomura, J.

strongly depend on the coordinated atoms. In

Alloys Compd. 851 (2021) 156817.

the cases of large coordinated atoms, The Cu[3] S. Hasegawa, Y. Kunisada, N. Sakaguchi,

atoms protrude from graphene basal planes.

Vac. Surf. Sci. 63 (2020) 413.

We also investigated the catalytic activity[4] R. Sugimoto, Y. Segawa, A. Suzuta, Y.

using a theoretical volcano plot reported inKunisada, T. Uchida, K. Yamazaki, K.

the previous study.[1] From the adsorption

Gohara, J. Phys. Chem. C 125 (2021)

energy of intermediates, we estimated the

2900.

80

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ab initio analysis on the stability of magnetic ternary
alloysYasutomi TATETSU
Meio University, Biimata, Nago, Okinawa 905-8585
Adding a small amount of third elements in

For In-doped Fe–Pd ternary alloys, the In

binary systems not only stabilizes system but

sites were chosen by replacing Fe or Pd sites

also changes these physical properties. Recently,

with a special-quasirandom-structure method

a new ternary alloy was discovered by

implemented in the Alloy Theoretic Automate

introducing a third element of In into L12-FePd3

Toolkit [3]. The figure illustrates the formation

by Teranishi’s group in Kyoto University [1].

energies of L12-(Fe, In)Pd3 and Z3-Fe(Pd, In)3Other interesting example is Nd–Fe amorphouswhen the number of In in a system takes from 1

phases which can be crystalized after adding

to 6. By comparing these formation energies,

Ga in Nd–Fe–B sintered magnets. Although the

Z3-Fe(Pd, In)3 can be more stable than L12-(Fe,physical aspects of these added elements areIn)Pd3 only in a narrow range of the In content.

unclear and cannot be understood deeply onlyThis tendency can be seen in the experimental

through experiments.

results from XRD, EXAFS, and STEM-EDS

In this study, we conducted theoreticalanalyses.

analyses for the stability of an In-doped novel

In Ga-doped Nd–Fe ternary alloys, we

Fe–Pd and Ga-dope Nd–Fe ternary alloys using

found that Ga is a key not only to stabilizing

OpenMX. The model structures for thethe fluorite-type crystal structure but also to

calculations were based on the chemical

suppressing its Curie temperature, which might

composition ratio obtained from experiments.

be one of the reasons to explain why Ga-added
Nd–Fe–B0

Pd site in Z3
Fe site in L12

magnets

have

high

coercivity [4].

References−0.005
Eform (eV/atom)

sintered[1] K. Matsumoto, R. Sato, Y. Tatetsu, T.
−0.01

Teranishi, et al., submitted.
[2] http://www.openmx-square.org−0.015[3] A. van de Walle et al., Calphad Journal 42,
−0.02

1

2

3

4

5

13 (2013).

6

The number of In in a system

Figure: Formation energies for L12-(Fe, In)Pd3[4] Yuta Ainai et al., Jpn. J. Appl. Phys., 59,

and Z3-Fe(Pd, In)3.

06094 (2020)

81

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo!"#$%&'%(')%*+",-,$%&-.'*-,/0$-.'#)$/&)/'-&1'1-,-210$3/&'#)$/&)/'4$,5'*-##$3/.6'+-0-../.')%*+",-,$%&''!"#$%&'%()*&!!"#$%&'(#)'!*+!,$$-.#/!0%'1#(%'.23!%)/!4153.236!7*''*&.!8).9#&3.'56!
:;<=<!>*5%(%;0.)%(.6!7*''*&.!?@=;@AA=6!B%$%)C!"#$ %&#'#()$ %&*+#,)$ -.'$ ,.&&/#0$ *1)$ 2*&$&#N1/&#0$ 2*&$ )"#$ 0.).$ .(.4A'/'$ ;A$ ZL<S!$ .(0$'#3#&.4$ )*%/,'$ /($ )"#$ 21'/*($ *2$ ,*5%1).)/*(.4$-#$ 1'#0$ )"#$ '/514.)*&$ %&*J&.5$ ['/56)&"#%065.)#&/.4$',/#(,#$.(0$0.).60&/3#($',/#(,#$*($)"#$&"##0\$*&/J/(.44A$0#3#4*%#0$;A$!:$@.(.0.:$O]?QR:$

7889$ '1%#&,*5%1)#&:$ !"#$ 5./($ ,*44.;*&.)*&'$.&#$7:$<*,"/=1>/?$!:$@A*0*$BCDC67<88689EF?$!:$ @.(.0.$ B!*"*>1$ GF?$ C:$ @1>1'"/5.$ BG!*>A*F?$ C:$ H*'"/5/?$ H:$ <*)*A.5.$ B7889F?$ !:$E1+/).$B7<8F?$H:$H.5.5*)*$BGDIF?$H:$</A.).>#
BG:$!*>A*F:$!"#$ 2/&')$ )*%/,$ /'$ )"#$ 0#3#4*%5#()$ *2$ )"#$
0.).$ .(.4A'/'$ '*2)-.&#$ *2$ )*).46&#24#,)/*($ "/J"6#(#&JA$%*'/)&*($0/22&.,)/*($B!K@D9LF?$.$(*3#4$

Fig.1 (a) Schematic figure of TRHEPD
experiment. (b) The side view of 8/!T"U#$V$
Q@68/I$BWWWPF6B!X"!XF$KXW#B8/TUF$'1&2.,#$')&1,)1&#:$B,F$!K@D9L$0.).$.(.4A'/'$*2$)"#$8/TU$'1&2.,#$')&1,)1&#$OXR:$!"#$!6,**&0/(.)#$*2$)"#$'1&2.,#$.)*5$4.A#&'$/'$0#(*)#0$.'$!! " !" " # # # " !# #$!"#$,*4*&6,*0#0$/'*3.41#$%4*)'$*2$)"#$K62.,)*&?$)"#$&#'/01.4$21(,)/*($;#)-##($)"#$#M%#&/5#().4$.(0$,.4,14.)#0$0.).?$*($)"#$
4*,.4$J&/0$*2$)"#$!! $ % !" $%4.(#$$OXR:#M%#&/5#().4$ )#,"(/N1#$ 2*&$ '1&2.,#$ ')&1,)1&#$
0#)#&5/(.)/*($ OP6QR:$ DM%#&/5#()'$ .&#$ ;#/(J$,*(01,)#0$ /()#('/3#4A$ .)$ )"#$ 84*-$ 9*'/)&*($
E.,/4/)A?$7(')/)1)#$*2$<.)#&/.4'$8)&1,)1&#$8,/#(,#?$@/J"$

D(#&JA$S,,#4#&.)*&$

K#'#.&,"$

T&J.(/=.)/*(:$ E/J1&#$ P$ '"*-'$ )"#$ ')&1,)1&#$
0#)#&5/(.)/*($*2$)"#$8/!T"U#$V$Q@68/I$BWWWPF6!"#$'#,*(0$)*%/,$/'$)"#$5#)"*0$.(0$B!X"!XF$KXW#B8/TUF$'1&2.,#$')&1,)1&#$OXR:$.%%4/,.)/*($ *2$ 4.&J#6',.4#$ #4#,)&*(/,$ ')&1,)1&#$!"#$ '*2)-.&#$ 0#3#4*%5#()$ .,)/3/)A$ -.'$,.4,14.)/*('$2*&$*&J.(/,$.(0$*)"#&$5.)#&/.4'$O_6%&*5*)#0$ )*$ 9&*+#,)$ 2*&$ S03.(,#5#()$ *2$

PWR:$ !"#$ ')10A$ -.'$ ,.&&/#0$ *1)$ ;A$ *1&$ *&/J/(.4$8*2)-.&#$G'.;/4/)A$/($<.)#&/.4'$8,/#(,#$/($7889$,*0#$ D`8D8$ B$ "))%YVV---:#4'#':+%V$ F?$ .($ *&0#&6

B$ "))%'YVV---:%.'15':/''%:16)*>A*:.,:+%$ F$ /($!$ #4#,)&*(/,$ ').)#$ ,.4,14.)/*($ ,*0#$ -/)"$ .($ "#$EHZWZW$.(0$EHZWZP:$T1&$'*2)-.&#$-.'$,.44#0$%&%'%(6;.'#0$ )/J")6;/(0/(J$ 5#)"*0$ .(0$ .$[ZL<S!\$.(0$-.'$%1;4/'"#0$.'$.($*%#(6'*1&,#$

2&.J5#()65*4#,14.&6*&;/).46;.'#0$ 5#)"*0:$ 7($'*2)-.&#$ O]?^R:$ S$ !K@D9L$ '/514.)*&$ -.'$

82

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

particular,anexcited-state

theorywasconstructedfordisordered

Pentacene/C60[7]Computational

conductivity

study

properties

forelectricaloforganic

The third topic is thesemiconducting polymers and metal complex-

development of several fundamental numericalhost systems, M. Ishida, M. Arita, S. Nishino, T.

algorithms [11-12].

Hoshi, HPCI Research Report, to appear.

Interfaces [9-10].

[8] Recent progress in large-scale electronic

References

state calculations and data-driven sciences, T.

[1] Development of data-analysis software for

Hoshi, S. Ito in Handbook of Silicon Basedtotal-reflection high-energy positron diffraction

MEMS Materials and Technologies 3rd Ed.,

(TRHEPD), K. Tanaka, T. Hoshi, I. Mochizuki,

Elsevier, 2020.

T. Hanada, A. Ichimiya, T. Hyodo, Acta. Phys.

[9] Revisiting the Charge-Transfer States at

Pol. A 137, 188-192 (2020).

Pentacene/C60 Interfaces with the GW/Bethe–[2] Two-stage data-analysis method for total-

Salpeter Equation Approach, T. Fujita, Y.

reflection

Noguchi and T. Hoshi, Materials 13, 2728

high-energy

positrondiffraction(TRHEPD), K. Tanaka, I. Mochizuki, T.

(2020).

Hanada, A. Ichimiya, T. Hyodo, T. Hoshi, JJAP[10] FMO-based excited state dynamics inConf.

molecular aggregates, T. Fujita and T. Hoshi, inSeries,inpress;

Preprint:

https://arxiv.org/abs/2002.12165

Recent advances of the fragment molecular[3] Data-driven sensitivity analysis in a total-

orbital method Subtitle: Enhanced performancereflection

high-energy

positrondiffraction

and applicability, ed. Y. Mochizuki, S. Tanaka,(TRHEPD) experiment of the Si4O5N3 / 6H-SiC

and K. Fukuzawa, Springer, 2021.

(0001)-(√3×√3) R30° , T. Hoshi, D. Sakata,[11] Kω - Open-source library for the shifted

S. Oie, I. Mochizuki, S. Tanaka, T. Hyodo, K.

Krylov subspace method of the form (𝑧𝐼 −Hukushima,𝐻)𝑥 = 𝑏, T. Hoshi, M. Kawamura, K. Yoshimi,

Submitted;

Preprint:

https://arxiv.org/abs/2103.04875

Y. Motoyama, T. Misawa, Y. Yamaji, S. Todo,[4] T. Hoshi, Y. Motoyama, T. Hanada, Y.

N. Kawashima, T. Sogabe, Comp. Phys. Comm.

Konishi and K. Yoshimi, poster presentation,

258, 107536 (2021).

CCMS Workshop of the data science in[12]material science, online, 22-24. Feb. (2021).

integrator MB4 and its application to quantum-[5]

mechanical wavepacket dynamics, T. Sakai, S.

https://www.pasums.issp.u-

tokyo.ac.jp/2DMAT;

A

parallelizableenergy-preserving

Kudo, H. Imachi, Y. Miyatake, T. Hoshi, Y.

https://github.com/issp-

center-dev/2DMAT

Yamamoto, Japan J. Indust. Appl. Math. 38,[6] https://github.com/sim-trhepd-rheed/

105 (2020).

83

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Reduction of Rare Metals in Fuel Cell Catalysts
and Hydrogen Permeable Membrane
Norihito Sakaguchi
Center for Advanced Research of Energy and Materials, Faculty of Engineering,
Hokkaido University, Sapporo, Hokkaido 060-8628
We investigated the catalytic properties ofactivity of Pt1 more strongly depends on thePt sub-nano clusters on light-element doped

light-element dopants in graphene lattice thangraphene and hydrogen dissolution andthose of Pt2 and Pt3. Therefore, Pt single

diffusion properties in the interfaces ofatoms on light-element doped grapheneceramic materials, with the aid of the first-

support is a promising candidate for a newprinciples calculation based on the density

catalyst which is better than the current fuelfunctional theory (DFT).

cell catalyst, i.e., bulk Pt catalyst.

At first, we investigated the adsorption

We also investigated the chemical bonding

and catalytic properties of Pt single atoms andbetween N-doped graphene and Pt single

Pt sub-nano clusters on light-element doped

atoms

graphene. We performed the total energy andtransmission electron microscopy combining

electronic structure calculations using The

with electron energy loss spectroscopy, andVienna Ab initio simulation package (VASP).

the

We installed a parallelized VASP with Intel®

properties in the interfaces of TiN

MPI Library and Intel® Math Kernel Library.

residual impurity gasses.

In this study, we focused on oxygen reduction

References

reactions (ORR). In order to evaluate the[1] J. K. Nørskov, J. Rossmeisl, A. Logadottir,

catalytic properties, we calculated the energy

L. Lindqvist, J. R. Kitchin, T. Bligaard,

diagrams of whole ORR paths. We also madeH. Jónsson, J. Phys. Chem. B, 108

a volcano-plot to show relationship between(2004) 17886.

the adsorption energy of catalytic activities
andintermediate

speciesofusinghydrogenDFT

calculations

dissolution

and

and

diffusion
with[2] S. Hasegawa, Y. Kunisada, N. Sakaguchi,

chemicalVac. Surf. Sci. 63 (2020) 413.

reactions.[1] We found that ORR activity of[3] R. Sugimoto, Y. Segawa, A. Suzuta, Y.

Pt1 is higher than those of Pt2 and Pt3. From

Kunisada, T. Uchida, K. Yamazaki, K.

the viewpoint of a support effect caused byGohara, J. Phys. Chem. C 125 (2021)

light-element doped graphene, the catalytic

2900.

84

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles study on physics of gap-state control
at metal/semiconductor interfaces: II & III
Takashi NAKAYAMA

Department of Physics, Chiba University
1-33 Yayoi, Inage, Chiba 263-8522
Due to the break of atomic bonds and the lackof translational symmetry, gap states appear insemiconductor layers around metal/semiconductor
interfaces, which have the energy position in theband gap and are localized around the interface.
These states induce the electron transfer between
metal and semiconductor layers and determine avariety of physical properties at the interface, suchas Schottky barrier (SB) and carrier transport.
However, it is still unclear how to control thesegap states. In this works, we studied the SB andtunneling current at various interfaces and clarify
the origins of gap-state generation/annihilation anddeformation using the first- principles calculations.
First, we consider metal/Ge interfaces, whereFermi energies of most of simple metals arelocated around the valence-band top of Ge notdepending on the kinds of metals. This is called the
Fermi-level (FL) pinning and interrupts desirable
low-resistive metal/n-Ge contacts. Although the
breakdown of FL pinning was recently observed at
the Bi/Ge(001) interface, its origin has not beenclarified. To simulate the interfaces, we adopt (2×2)(Bi, Al)/Ge(001) repeated-slab models with various
interface structures and calculate their SBs using
local potential profiles.
Figure 1 shows calculated SBs for hole carriers
ate various interfaces. The SBs at (b) disordered
Bi/Ge and (c) plain Al/Ge interfaces are around
0.0eV corresponding to the FL pinning, while the
SB at (a) plain Bi/Ge interface has a large value
around above 0.3eV, which is in good agreementwith experiments. The origin of such SB variationis understood by observing the projected densitiesof states (PDOS) of interface Ge atoms, which are
shown in Fig.2. For (b) and (c) interfaces, theFig.1. Left: calculated Schottky barriers for holecarriers at various (Bi, Al)/Ge interfaces. Right:
schematic pictures of interface structures. (a):abrupt plain Bi/Ge interface, (b): disordered Bi/Ge
interface, and (c): plain Al/Ge interface.

continuous PDOS, thus the gap states, appear
around 0.0eV due to the orbital hybridization
between metal and Ge atoms, which induces theelectron transfer from metal to Ge and realizes theFL pinning. On the other hand, we can see thesuppression of gap states in the PDOS of interface
Ge for the (a) interface, which realizes the FLdepinning. This suppression occurs due to the weakcontact of Bi and Ge layers, which is caused by thelattice mismatch originating from the large atomic
radius of Bi and produces the Ge-Ge dimer bonds
at the interface as shown in the right of Fig. 1. In
this way, the interface Ge-Ge dimer bonds
annihilates the gap states in interface Ge layers andproduces the large change of the SB values.
Next, we consider how the gap states change inelectric fields. We consider the tunneling current at
indirect-band-gap Si and GaP, and direct-band-gap
GaAs and InP p/n junctions, in the cases without

85

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Fig.2. Calculated projected densities of statesof interface Ge atoms around (a) plain Bi/Ge,(b) disordered Bi/Ge, and (c) plain Al/Ge
interfaces, which respectively correspond tointerfaces shown in Fig.1. Orange boxes
indicate the band-gap region of Ge.

Fig.4. Calculated transmission spectra ofelectrons and local density of N-atom dopant
states at the Si p/n junction ((a) and (b)), and
the GaAs p/n junction ((c) and (d)). The casesof junctions without dopants are also shown by
red lines.

such resonance remarkably increases the tunnelingprobability across the junction as shown in Fig.4(a).
On the other hand, in the cases of direct band-gap
systems, as seen in Fig.3(b), there is no increase in
the current by the dopants. This is because thedopant gap state is strongly localized as in Fig.4(d)and the increase of tunneling is small as in Fig.4(c).
By analyzing electronic structures, we found thatthe difference in the dopant effects on tunnelingcurrents between indirect and direct band-gap
systems reflects the characters of conduction-bandstates in these systems.
All these calculations were performed using thexTAPP, VASP, and our original pspwf codes. In
order to realize the calculations for the presentinterface systems, because the system is made of alarge number of atoms (500-2000 atoms), theadvanced computing facility having multi-task andhigher-speed CPU (more than 1280 cores ×
2.0GHz), larger-size memory (around 256GB), andlarger-size strange (more than 2 TB) is
indispensable. These conditions are realized onlyby the present ISSP supercomputing systems.

Fig.3. Calculated tunneling currents at (a)indirect-band-gap Si and GaP, and (b)direct-band-gap GaAs and InP p/n junctions,as a function of electric field. The cases
without and with N-atom dopants areshown.

and with N-atom dopants. Figures 3(a) and 3(b)show calculated currents for these interfaces as afunction of applied electric field. It is clearly seenthat the current is much larger for the latter
junctions, which is because the latter system havedirect band gap and have larger interband tunnelingtransitions.
When N-atom dopants are embedded in p/njunctions, the current is markedly enhanced in thecases of indirect band-gap systems, i.e., Si and GaP.
This enhancement occurs because the dopant gap
state produces the resonance states with theconduction-band states of host Si layers around thejunction in electric field as shown in Fig.4(b), and86

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles Calculations on
Magnetism in 2D Magnetic Materials
Kunihiko Yamauchi
Institute of Scientific and Industrial Research (ISIR-SANKEN), Osaka University, 8-1
Mihogaoka, Ibaraki, Osaka 567-0047
We have studied the magnetism in 2D

the ISSP ohtaka supercomputer. VI3 is a Mott

magnetic materials and discussed our current

insulator with an energy band gap is 0.34 eV. In

understanding of the mechanisms using the first-

VI3,

principles density functional theory (DFT)with D3d point group, the t2g orbital state is split

calculations.

into a1g and eg’ states. The a1g orbital state plays

under

the

trigonal

crystalfield

First, we systematically investigated thean important role in inter-layer magnetic

magnetocrystalline anisotropy energy (MAE) of

exchange interaction in a bilayer structure. By

the Co-based transition-metal thin films using

using Wannier90 code that is interfaced with the

DFT

the

VASP code, we estimated the hopping integral

ISSP seikirei supercomputer. The results show

and discussed the inter-layer magnetic exchangethat the large perpendicular MAE can beinteraction

achieved by tuning atomic-layer stacking in Ni-

mechanism. In the bilayer VI3 case, we studied

Co thin film. The MAE is decomposed into

two structures corresponding to R3 and C2/c

single-layerinter-layer

phases in bulk VI3, namely AB and AB’ stacking.

contributions to reveal the fact that not only the

The application of electric field enables toon-site SOC of 3d elements but also the strong

switch the magnetic ordering from inter-layer

hybridization between these elements play an

AFM to FM in AB’ stacking. This finding may

important role to determine the MAE. The small

pave a way to the spintronics application witheffect of electric fields on the magnetocrystalline

2D materials [2].

anisotropy also has been found in Ni-Co thin

References

film, making this system becomes the potential[1] T. P. T. Nguyen, K. Yamauchi, K. Nakamura,for future spintronics applications [1].

T. Oguchi, Journal of the Physical Society of

HiLAPWcode

contributions

and

at

Secondly, we investigated the magnetic

based

on

the

virtual-hopping

Japan, 89, 114710 (2020).

stability in 2D magnetic material VI3 making a[2] T. P. T. Nguyen, K. Yamauchi, T. Oguchi, D.

comparison with CrI3 using the VASP code at

Amoroso, S. Picozzi, arXiv:2102.04173 (2021).

87

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Band structure calculation based on the group theory

Mineo SAITO
Institute of Science and Technology, Kanazawa University
Kakuma, Kanazawa, 920-1192 Japan

In the field of spintronics, the spin-

operation

orbit coupling (SOC) is considered togenerate new functions. One of the mostCm , respectively. kjisimportant phenomena is concerning

the Bloch function for the band
index j and the wavenumber k .

topological insulators.

emphasize

The wavefunction (does not ) belongthat the group theoretical analysis isto the IR of  when Q  = 1 (Q  = 0) .

necessary to deeply understand the SOC

In this report, we focus on our resultsWe

effect on electronic structures but theon group-IV two dimensional materials.

analysis has been insufficient so far. We

In the case of graphene, the Dirac

have developed a method to identify

cone is found to belong to the two-

irreducible representations (IR) for thedimensional IR of E” in the D3h

SOC bands which are obtained by usinggroup. The SOC is found to split thefirst-principles

base

doubly degenerated level into E1/2

calculations. The identification can be

and E3/2 levels. The former level isdone by using computers and thus mis-found to be higher than the latter

identification can be avoided.

level and we clarify the reason for

plane

wave

The IR of the band having the q-

this energetical order by using adegeneracy is determined by using thetight binding model. We evaluate

following expression：

thetopologicalconfirmQ =1 p + q −1 ljj
    (Cm )*  k | Cm | k 
l j = p m=1

invariantthat the values for bothbuckled and non-buckled structuresare 1, suggesting the possibility of
topological insulators.

Where l and (C m )andare theorder of the k group and thecharacter for the m − th symmetry

88

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Effects of solvents on properties of artificial-retina molecule:
ab initio molecular dynamics simulations
Satoshi OHMURA
Research Center for Condensed Matter Physics / Department of Environmental and Civil
Engineering
Hiroshima Institute of Technology, Saeki-ku, Hiroshima, 731-5143
Molecular dyes are attractive great attention

peak at visible light region. However, the excited

because of their application for various opticalcharge dynamics after light absorption isdevices such as solar cell and artificial retina. To

influenced a great deal by H2O. Without H2O,

improve functionality of the dye molecule, it is

the generated hole by light-absorption in NK-

used to control the band gap. Therefore,

5962 transfers to counter-ion cite at less than 100

theoretical studies based on the density

fs. On the other hand, in the case of the system

functional theory tried to understand thewith H2O, the hole stays in NK-5962 site. Our

structural and photoelectrical properties such as

simulation clarified that these effects areabsorption and emission properties in the gas

attributed to interaction between H2O andphase. However, the working conditions of suchcounterion of NK5962. In addition to retina

dye molecules in nature and in the industrial

molecule, we have investigated the dissociation

applications entail their solvation. We havemechanisms from highly charged bromophenol

systematically investigated the effects of solvent,(C6H5OHBr)n+ (n≤10) by ab initio MD

H2O,

and

simulations [1]. The charge state dependence ofchlorobenzene on light-absorption properties indissociation mechanisms is observed by thisa photoelectric dye (NK-5962) which is better

simulation.

candidate for retinal prostheses by means of ab

intramolecular charge transfer time by using

initioTo

nonadiabatic quantum-mechanical molecular-

calculate absorption spectra, we adopted the

dynamics with surface hopping approach. It is

Time-Dependent

found that the hole transfer from the Br site toacetonitrile,

tetrahydrofuran,molecular-dynamics

simulations.

Density-Functional

linear-We

also

investigatedtheResponse Theory (TDDFLRT), proposed andthe molecular counterpart in ~5 fs.

formulated by Casida. The simulation reveals

Referencesthat all solvents slightly affect the light-[1] S. Ohmura, K. Nagaya, F. Shimojo and M

absorption spectrum but all systems has a main

Yao ; Z. Phys. Chem. 2021; 235(1–2): 169–187

89

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Structural and transport properties of multi-component liquid
Fe mixtures under high pressure
Satoshi OHMURA
Research Center for Condensed Matter Physics / Department of Environmental and Civil
Engineering
Hiroshima Institute of Technology, Saeki-ku, Hiroshima, 731-5143
We have investigated the effects of lightternary systems. For the transport properties, LEelements (LE) such as H, C, O, Si, and S on thein the ternary systems decrease electric

structural and transport properties of liquid Fe

conductivity of liquid Fe as same as binary

under high pressure by ab initio molecularsystems. The decreasing rates are between thosedynamics (MD) simulations. It is believed thatof binary systems as shown in Fig. 1.

Earth’s outer core consists of liquid iron (orliquid-nickel alloy) with LE impurities. LE havea strong influence on structural and transport
properties of liquid iron under high pressure.
However, there are still many uncertainties
regarding the influence of LE. For Fe-LE binary
systems, we clarified the structural properties
and interactions between LE atoms at coremantle boundary condition [1]. The simulations
clarify that H, C, and O are incorporated into
liquid Fe interstitially while Si and S are

Fig. 1: Change of electrical conductivity of liquid Fe-“substitutional” type impurities. Under these

H-O as a function of concentration of LE. Bluecircumstances, in this study, we have studied

circles show ternary systems. Red and green squares

structural and transport properties of liquidshow binary system.

ternary system consisting of liquid Fe and two
types of LE by using ab initio MD simulations.

References

From our simulations, it is found that Si and S[1] S. Ohmura, T. Tsuchiya and F. Shimojo:

atoms show “substitutional” behavior while H

Physica Status Solidi B, 257, 2000098 (2020)

and O atoms show “interstitial” behavior even in90

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Impact of the molecular quadrupole moment in themolecularly mixed ﬁlm of organic semiconductors
Susumu Yanagisawa
Faculty of Science, Department of Physics and Earth Sciences, University of the Ryukyus
Nishihara, Okinawa, 903-0213

The energy levels of organic semiconductors
are primarily determined by the molecular orbital energies of constituent molecules. Recent
studies have, however, shown that the energy
levels can be changed by the mixing ratio of
two molecules which have diﬀerent permanent
quadrupole moments. From the good correlation between the magnitude of the mixed ﬁlm’s
energy shift and the constituent molecules’
permanent quadrupole moment, it was notedthat the molecular quadrupole plays an important role in the energy shift.
In this study, I theoretically examined themixed ﬁlms of zinc phthalocyanine (ZnPc) andperﬂuorinated ZnPc (F16 ZnPc), which havepermanent quadrupole moments with opposite
directions. Here, as was successfully applied toorganic semiconductor thin ﬁlms[1, 2], a combination of the GW approximation suitable ingeneral to solid or bulk systems and a periodic
slab approach at the DFT-GGA level was employed. From the theoretical electronic polarization energy D and electrostatic energy S asa function of mixing ratio, ionization energies
and electron aﬃnities were estimated.
I performed ﬁrst-principles electronic structure calculations with the STATE programcode to determine the optimized geometriesof the pristine crystals as well as 1:1 mixed
thin ﬁlms of ZnPc and F16 ZnPc. To checkthe convergence of the electrostatic energy on
the number of the layers in the simulation
cell, one, two, and three monolayers (1−3 ML)
ﬁlms were modeled by periodic slabs. For

the pristine crystals, I ﬁxed the lattice constants to experimental values of the monoclinic
and triclinic forms for ZnPc and F16 ZnPc, respectively. The two stable facets are denotedby ”edge-on” and ”face-on” for each of thecrystals, depending on the orientation of themolecules at the surface (see Fig. 1). Since theexperimental lattice constants were not available for the mixed ﬁlm, those of the pristine
crystals were used for the mixed ﬁlms.
The 1 ML slabs for the pristine ZnPc and
F16 ZnPc ﬁlms consisted of 2 molecules, and 4
molecules comprised the 1 ML mixed ﬁlm in
the ratio 1:1. The vacuum layer with a thickness of 2.0 nm was inserted. I optimized thegeometric structures of the standing 1−3 MLslabs by taking into account the van der Waals
forces within PBE-D2. To describe the orientation dependence of the electrostatic interaction, I took the diﬀerence in the HOMO or the
LUMO energy of ZnPc and F16 ZnPc between
the slab and an isolated gas-phase molecule.
The electronic polarization energy was described by the many-body perturbation theory,
within the G0 W0 approximation with the GW
space-time code. The fundamental gaps wereobtained as the diﬀerence between the highest
occupied and lowest unoccupied band energies
averaged over the Brillouin zone. The numbersof cores used in the calculations were 256∼512.
The gaps were determined to be 2.26 eV
and 2.19 eV for the monoclinic ZnPc and thetriclinic F16 ZnPc bulks, respectively. For thegas phase fundamental gap, I estimated the91

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

electron aﬃnity (Ag ) and the ionization energy (Ig ) at the HSE06/spaug-cc-pVTZ levelof theory with the delta self-consistent ﬁeld
approach using Gaussian16 Revision B.01 installed in my own computer resources. I did
not use the gas-phase fundamental gap at theG0 W0 level, since the G0 W0 treatment tends
to over-screen the injected charge in gas-phasemolecules[3]. The electrostatic energy S wasestimated as the diﬀerence in HOMO/LUMO
energy between the surface slab and the gas
phase estimated with the GGA-PBE level oftheory[1, 2]. Based on the bulk fundamental
gap obtained with G0 W0 and the theoreticalgas phase ionization energy Ig and electronaﬃnity Ag , the electronic polarization D was
obtained.

Figure 1: Theoretical polarization energy D
and electrostatic energy S as a function of molar mixing ratio of F16 ZnPc in the mixed ﬁlm.
The calculated results are displayed by dashedlines and the experimental values are by solidlines.

on” conﬁgurations. The result implies the nature of the electronic polarization originatingfrom the stabilized injected charge surroundedby the induced polarization clouds inside thebulk, and thus does not depend on the molecular orientation at the surface of the ﬁlms.
On the other hand, the electrostatic energy changes more rapidly as a function of
the mixing ratio in the ”edge-on” conﬁguration than in ”face-on”. The diﬀerent trend
comes from the diﬀerent orientation of themolecules at the surfaces of the mixed thinﬁlm: in the ”edge-on” conﬁguration in which
the constituent molecules are standing on thesurface of the ﬁlm, the orientation angle isvery sensitive to the mixing ratio, while in the”face-on” conﬁguration, the molecular planes
are parallel to the ﬁlm surface and the orientation angle does not change signiﬁcantly withrespect to change in the mixing ratio. Thechange in the electrostatic energy in the molecular crystal ﬁlm comprised of molecules withappreciable quadrupole moment such as ZnPc
and F16 ZnPc may be elucidated in terms of
the electrostatics[5]. The present ﬁnding maylead to the insight into tuning of the charge injection energy levels at the surfaces of organic
semiconductors.

References[1] S. Yanagisawa: Jpn. J. Appl. Phys. 59(2020) 031002.
[2] K. Yamada, S. Yanagisawa, T. Koganezawa, K. Mase, N. Sato and H.
Yoshida: Phys. Rev. B 97 (2018) 245206.

Figure 1 displays the calculated D and S,
along with the experimental values[4]. Overall, the theoretical polarization energies arein good agreement with experiments. In caseof the electrostatic energies, the qualitative
trend depending on the F16 ZnPc amount in
the mixed ﬁlm is similar.

[3] S. Rafaely-Abramson et al., Phys. Rev. B
88 (2013) 081204(R).
[4] Y. Uemura, S. A. Abd-Rahman, S. Yanagisawa and H. Yoshida: Phys. Rev. B 102(2020) 125302.
[5] B. J. Topham and Z. G. Soos, Phys. Rev.
B 84 (2011) 165405.

It is found that the polarization energies arealmost the same in the ”edge-on” and ”face-92

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First principles exploration of the metastable phasesof hydrides and their superconductivity
Ryosuke AKASHI
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

Superhydrides that crystallize under extremely high pressure have attracted lots ofinterest since the discovery of high temperature superconductivity in solid hydrogen sulﬁde [1]. Recently, the domain of searchingfor new hydrides that possibly exhibit higher
transition temperatures is getting broadened
to ternary hydrides ABHx , resulting in the discovery of superconductivity in a C-S-H systemwith record of Tc = 286 K [2].
We conducted exploration of the novel(meta)stable hydrides and calculations of superconducting properties of them. In particular, we contributed to an international
theoretical-experimental study of a La-Y-H
ternary hydride system. In their pure binary
compositions LaHx and YHx , LaH10 and YH6have been discovered to form under pressure,both of which exhibit diﬀerent forms hydrogencage structures. The inverse, YH10 and LaH6 ,are metastable according to simulations. Interestingly, it is predicted that their mixtures
LaYH20 and LaYH12 can become stable at certain conditions, the origin of which may be asynergetic eﬀect of La and Y. This prediction
was veriﬁed by the experimentally observed
diﬀraction patterns. We calculated their possible values of Tc , using the density functional
theory for superconductors (SCDFT) [3, 4]
to compare them with the experimentally observed Tc .
Here we append the the scheme of calculating Tc on the basis of SCDFT. First, the KohnSham electronic and phononic structure calcu-

lations were performed using an open sourcecode package quantum espresso [5]. The
generalized gradient approximation [6] for theexchange-correlation potential was employed.
The optimized norm-conserving Vanderbilt
pseudopotentials [7] was used for the calculations. Next, the dielectric matrix and matrix elements of the eﬀective electron-electron
Coulomb interaction were calculated with an
in-house code. Finally using those data, thesuperconducting transition temperature was
evaluated by solving the following SCDFT gap
equation[3, 4, 8]∆nk = −Znk ∆nktanh[(β/2)En′ k′ ]1∑
∆n′ k′(. 1)
Knkn′ k′−2 n′ k′En′ k′
β denotes the inverse temperature.
The
exchange-correlation kernels K and Z, which
represents the eﬀects of the electron-phononand electron-electron interactions, are formulated in terms of the Kohn-Sham electronic
and phononic properties.
Solutions of the Kohn-Sham equation wasparallelized by MPI as implemented in pw.x
code of Quantum Espresso. The in-housecode for calculating the dielectric matrix has
been thread-parallelized by openmp. The
SCDFT gap equation was solved without parallelization since it was less time-consuming.
Calculations were mainly performed in System
B.
Various synthesis protocols were executedfor the La-Y-H samples and maximum Tc of ∼93

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 1: Superconducting transition temperature Tc calculated with the SCDFT gap equation Eq. (1). Coupling constant λ and typicalfrequency ωln ([9]) of the electron-phonon coupling spectra are also presented.
LaYH12 LaYH20
Tc (SCDF T ) (K)
191
252
λ
2.82
3.87
ωln
847
868

orbitals. This dependence results in correct reproduction of the Tc relation in those systems(Fig.1). This result has been published as apaper [11].

References[1] A. P. Drozdov, M. I. Eremets, and I. A.
Troyan, V. Ksenofontov, and S. I. Shylin,
Nature (London) 525, 73 (2015)[2] E. Snider et al., Nature (London) 586,
373 (2020).

250 K was observed. The calculated superconducting transition temperatures, especially in
LYH20 , show good agreement with this experiment (Table 1). This shows that the phononmediated pairing mechanism explains the superconductivity in the current ternary system.
This result is to be published [10].

[3] M. Lüders, et al., Phys. Rev. B 72, 024545(2005).
[4] M. A. L. Marques, et al., Phys. Rev. B
72, 024546 (2005).
[5] P. Giannozzi et al, J. Phys.: Condens. Matter 29,
465901 (2017);
http://www.quantum-espresso.org/.
[6] J. P. Perdew, K. Burke, and M. Ernzerhof,
Phys. Rev. Lett. 77, 3865 (1996).
[7] D. R. Hamann, Phys. Rev. B 88, 085117(2013); 95, 239906 (2017).
[8] R. Akashi, M. Kawamura, S. Tsuneyuki,
Y. Nomura, and R. Arita, Phys. Rev. B
91, 224513 (2015).

Figure 1: Impacts of the charge (plasmon) andspin ﬂuctuations on superconducting Tc in V,
Nb, and Al, taken from Ref. [11].
We also developed an extension of the
SCDFT scheme to include the spin ﬂuctuationeﬀect, which is a continuous subject since a
ISSP project in the ﬁscal year of 2018 [Project
ID: H30-Ca-0046]. We examined the eﬀects ofthe spin ﬂuctuation and charge ﬂuctuation on
Tc in elemental metals, V and Nb. We foundthat the spin ﬂuctuation strongly suppresses
Tc . Experimentally observed Tc is smaller in V
than in Nb, whereas the degree of the suppression eﬀect depends on the character of atomic[9] P.B. Allen and R.C. Dynes, Phys. Rev. B
12, 905 (1975)[10] D. V. Semenok et al., arXiv:2012.04787;
Mater. Today, in press.
[11] K. Tsutsumi, Y. Hizume, M. Kawamura,
R. Akashi, and S. Tsuneyuki: Phys. Rev.
B 102 (2020) 214515.

94

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Helical channel at twin boundaryof a boron-nitride atomic layer
Tatsuya ISHIKAWA, Yoshiyuki EGAMI and Hiroshi AKERADivision of Applied Physics, Faculty of Engineering, Hokkaido University
Sapporo, Hokkaido, 060-8628

We have made a first-principles calculationof the energy band of helical channels formed
along BNaL twin boundaries (Fig. 1). We impose the periodic boundary condition perpendicular to channels so that the unit cell contains two twin boundaries. We have foundthat polarized and unpolarized twin boundaries have quite different helical channel bands:
the distance in k space between helical channels belonging to K and K’ valleys is much
shorter in the polarized BCCB-NCCN arrangement [Fig. 1(b)] compared to that in the unpolarized NCB arrangement [Fig. 1(a)]. This result suggests a possibility of largely modifying
transport properties through a helical channel by changing the atomic arrangement in thevicinity of the channel.

using the facilities (system B and C) of theSupercomputer Center, the Institute for Solid
State Physics, the University of Tokyo.
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Helical channels, which suffer little frombackscattering, have attracted much attention
in valleytronics and theoretically studied ingraphene on a boron nitride substrate [1, 2]
and in a boron-nitride atomic layer (BNaL)with a twin boundary [3]. We focus on the
BNaL twin boundary which can support a narrower helical channel. Twin boundaries of the
BNaL are classified into unpolarized and polarized boundaries such as shown in Fig. 1
in which carbon chains are inserted at eachtwin boundary to relax the repulsion between
cations and that between anions. In this work
we have studied differences in electronic properties of helical channels between polarized andunpolarized twin boundaries.

'#$

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2%!"#$)*$$$#$$)*$$&#$$)!$'"#$$)!$'+#$$)!$',#$$)!$''#$$)*$$!""""""""""""!#$"""""""""""!#%"""""""""""!#&"""""""""""!#'""""""""""(#!"""""!! !"#$"%

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Figure 1: Helical channels at twin boundaries
with (a) unpolarized NCB arrangement (b) polarized BCCB-NCCN arrangement. The periodic boundary condition is imposed in the y
direction with periodicity of one unit cell. The
zero of energy is taken at the Fermi energy.

References[1] G.W. Semenoff, V. Semenoff, and Fei
Zhou: Phys. Rev. Lett. 101 (2008)
087204.
[2] C. Hu, V. Michaud-Rioux, W. Yao, and
H. Guo: Phys. Rev. Lett. 121 (2018)
186403.
[3] J. Jung, Z. Qiao, Q. Niu, and A. H. MacDonald: Nano Lett. 12 (2012) 2936.

The computation in this work has been done95Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles study ofquantum transport in nanostructuresNOBUHIKO KOBAYASHI
Department of Applied Physics, University of Tsukuba
1-1-1 Tennodai Tsukuba Ibaraki 305-8573

Theoretical investigations on transport
properties are important not only for the fundamental research of science but also for theapplications of electronics. We have developed
the nonequilibrium Green’s function (NEGF)
method, and the O(N) time dependent wavepacket diﬀusion (TD-WPD) method on thebasis of the density functional theory (DFT).
By using these methods, we have investigatedcharge, head and spin transport properties ofmaterials. [1]We have developed a Simulation code for
Atomistic Kohn-sham Equation (SAKE) for
the ab-initio electron transport calculation
based on the DFT and NEGF formalism.
We have applied the method to analyses ofthermoelectricity of magnetic semiconductors
CuFeS2 . The electronic transport properties,
Seebeck coeﬃcient, and the figures of merit are
estimated. We theoretically demonstrate theenhancement in the figure of merit by doping,which is in agreement with experimental work,and design doped systems for higher performance. [2]Figure 1: Seebeck coeﬃcient of CuFeS2 as afunction of the chemical potential.
namical simulation method. It is shown thatthe proposed methodology is an eﬀective theoretical design technique for eﬃciently developing new high-performance organic semiconductors. [3]We developed the O(N) TD-WPD method
for the quantum transport calculation of hugesystems of up to 100 million atoms a decadeago. It is possible to calculate the conductivity and the mobility of the system withmicron-order lengths at room temperature
at the atomistic levels. We have proposeda prediction methodology to obtain chargetransport properties of organic single crystals from their structural formula using TDWPD method. We applied the method to C10 DNBDT molecule, and succeeded in quantitative evaluation of charge mobility of the single crystal using our quantum wave-packet dy-

References[1] N. Kobayashi, H. Ishii, K. Hirose, in 3D Local Structure and Functionality Design of Materials eds H. Daimon, Y. C. Sasaki (World
Scientific, 2018) p133.
[2] H.Takaki, N.Kobayashi, K.Hirose,
J. Phys.: Condens. Matter. 32 325901(2020)[3] H. Ishii, S. Obata, N. Niitsu, S. Watanabe, H.
Goto, K. Hirose, N. Kobayashi, T. Okamoto,and J. Takeya,
Sci. Rep. 10, 2524 (2020)

96

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Magnetocaloric Eﬀect of Transition-Metal Alloys
Hung Ba TRAN, Hiroyoshi MOMIDA, and Tamio OGUCHI
Institute of Scientiﬁc and Industrial Research, Osaka University,
8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan(a)45

MnCoGeMn0.89Cu0.11CoGe
Mn0.85Cu0.15CoGe

40
35−∆SM (J/kg.K)

We study the magnetocaloric eﬀect oftransition-metal alloys by combining ﬁrstprinciples calculations and Monte-Carlo simulations. The parameters of the Monte-Carlosimulation are estimated from ﬁrst-principles
calculations. Several types of the magnetocaloric eﬀect such as conventional (direct)
magnetocaloric eﬀect, giant magnetocaloric effect, anisotropic magnetocaloric eﬀect, andinverse magnetocaloric eﬀect can be considered by using our original program[1, 2, 3, 4].
The isothermal magnetic entropy change of
Mn1−x Cux CoGe alloy is shown in Fig. 1(a). Stoichiometric MnCoGe has two phases,
the low-temperature phase is orthorhombic
while the high-temperature phase is hexagonal.
Both the phases are ferromagnetic below diﬀerent Curie temperatures. When there is a structural coupling between magnetic and structure
part, the isothermal magnetic entropy change
becomes gigantic as the Mn0.89 Cu0.11 CoGecase. We also perform speed-up tests for our
massively parallel Monte-Carlo program withhybrid MPI and OpenMP in new System B as
shown in Fig. 1 (b) and (c). We obtain a goodscaling in the tests of OpenMP and MPI, thatis quite important for further study such as
virtual screening of magnetocaloric materials.

30
25
20
15
10
5
0
100

(b)

200

300

400

500 600
T (K)

700

800

900

(c)

Figure 1: (a) Isothermal magnetic entropy changeof Mn1−x Cux CoGe (x = 0.00, 0.11, 0.15) [1]. (b)and (c) Speed-up tests of our Monte-Carlo programin the new System B (Ohtaka).
and T. Oguchi, Solid State Commun. 323,
114077 (2021).
[3] H. B. Tran, T. Fukushima, H. Momida, K.
Sato, Y. Makino, and T. Oguchi, Comput.
Mater. Sci. 188, 110227 (2021).

References[4] H. B. Tran, T. Fukushima, H. Momida,
K. Sato, Y. Makino, and T. Oguchi, Direct and Inverse Magnetocaloric Eﬀects
in FeRh Alloy: A Theoretical Study,
http://dx.doi.org/10.2139/ssrn.3799705.

[1] H. B. Tran, T. Fukushima, K. Sato, Y.
Makino, and T. Oguchi, J. Alloys Compd.
854, 157063 (2021).
[2] H. B. Tran, T. Fukushima, Y. Makino,

97

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical analysis of molecular motions in protonconducting organic materials
Yuta HORI
Center for Computational Sciences,
University of Tsukuba, Tennodai, Tsukuba, Ibaraki 305-8577
Anhydrous proton conduction materials

imidazole system. The diffusion coefficients ofhave been investigated for use in electrolytes inimidazoleium cation and PVPA oligomer infuel cells. The composite materials including

PVPA-2Im further decreased and were similar

imidazolemuch

values each other. Therefore, we find that theattention because of the lack of humidity.

imidazolium cation motion was interlocked byPoly(vinylphosphonic acid)-imidazole (PVPA-

PVPA because of the strong hydron bondxIm) has shown the increase of protoninteraction between imidazolium cation andconductivity with x [1].

phosphonic acid in PVPA.

have

especiallygainedUnderstanding theproton conduction mechanism leads to theWe estimated the rotational correlation time

improvement of proton conduction materials.

of imidazole and imidazolium cation to

In this study, we discussed the proton

investigate their internal motions. The obtained

conduction mechanism in PVPA-xIm in terms

results showed the similar dynamical behaviorof the microscopic characters of the hydrogenof the translational diffusions. We compared thebond and imidazole motions as investigated by

activation

molecularTherotational motions of imidazole. The calculated

simulations were performed by the GROMACS

energies of rotational motions were lower thanpackage.

those of translational motions. Therefore, it is

dynamics

simulations.

We calculated the translational diffusion

expectedenergies

thatofprotontransrational

conduction

and

obeys

coefficients of imidazole, imidazolium cation,

Grotthuss-type mechanism.

and PVPA oligomer in PVPA-xIm to investigate

References

their[1] M. Yamada, I. Honma, Polymer, 46, 2986

translationalmotion.

Alldiffusioncoefficients increased with temperature. The(2005).

intercalation of imidazole into PVPA reduces[2] Y. Hori, et al., ACS Appl. Polym. Mater. 2,

the imidazole diffusion, because the diffusion

1561 (2020).

coefficient of imidazole significantly decreased[3] Y. Hori, et al., Chemistry Letters 50, 17

in PVPA-2Im compared to that in pure(2021).

98

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of molecular crystal structure
prediction methods
Tomoki YAMASHITATop Runner Incubation Center for Academia-Industry Fusion,
Nagaoka University of Technology
1603-1 Kamitomioka-machi, Nagaoka, Niigata, 940-2188

We have developed a crystal structure prediction tool, CrySPY as an open source
software [1].
CrySPY is interfaced with
VASP[2], Quantum ESPRESSO[3], soiap[4],and LAMMPS code for structure optimization.
Several searching algorithms are available in
CrySPY, such as random search (RS), evolutionary algorithm (EA), Bayesian optimization(BO), and LAQA. RS is a basic algorithm andwidely used. EA[5, 6, 7] is currently very popular. Previously we have developed selectiontype algorithms with machine learning. BO
can efficiently select potential candidates froma large number of candidate structures by machine learning[8]. LAQA is one of the refinforcement learning, which can reduce the computation time[9]. CrySPY enables us to findstable structures for bulk systems. However,
CrySPY did not support molecular crystal,surface and interface structures. The original plan was to develop a method for surface
structure prediction, but we changed the planand developed a method for molecular crystal
structure prediction.
We employed the PyXtal library [10] to generate molecular crystal structure generation,and developed the interface between CrySPY
and PyXtal. We tested molecular crystal
structure prediction for Li3 PS4 using CrySPY.
The most stable structure of Li3 PS4 is knownas γ−Li3 PS4 [11], which is composed of six Li
atoms and two PS4 molecules shown in Fig.
1. Fifty molecular crystal structures of two

Figure 1: Crystal structure prediction of
Li3 PS4 . The stable structure is γ−Li3 PS4 .

formula units of Li3 PS4 were randomly generated. Structure optimizations were performed
using the density functional theory with the
projector-augmented wave [12] method as implemented in the VASP code [2]. The generalized gradient approximation by Perdew,
Burke, and Ernzerhof [13] was employed forexchange-correlation functional. A cutoff energy of 625 eV for the plane-wave expansion of
the wave function and k-point mesh density of
80 Å−3 were used.
Crystal parameters of the lowest-energy
structure perfectly agree with the experimental
ones of γ−Li3 PS4 except for the tiny amount ofdifferences in lattice constants and atomic positions. These results indicate that the molecular structure generation method is quite use-99

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

ful for stable structure predictions of molecular
crystals.

References[1] https://github.com/TomokiYAMASHITA/CrySPY.
[2] G. Kresse and J. Furthmüller, Phys. Rev.
B 54, 11169 (1996).
[3] P.
Giannozzi
J.Phys.:Condens.Matter(2009).

et
21,

al.,
395502[4] https://github.com/nbsato/soiap.
[5] A. R. Oganov and C. W. Glass, J. Chem.
Phys. 124, art. 244704 (2006).
[6] A. R. Oganov, A. O. Lyakhov and M.
Valle, Acc. Chem. Res. 44, 227 (2011).
[7] A. O. Lyakhov, A. R. Oganov, H. T.
Stokes, and Q. Zhu, Comp. Phys. Comm.
184, 1172 (2013).
[8] T. Yamashita, N. Sato, H. Kino, T.
Miyake, K. Tsuda, and T. Oguchi, Phys.
Rev. Materials 2, 013803 (2018).
[9] K. Terayama, T. Yamashita, T. Oguchi,
and K. Tsuda, Npj Comput. Mater. 4, 32(2018).
[10] S. Fredericksa, D. Sayrea, and Q. Zhua,
Comput Phys Commun. 261, 107810(2021).
[11] K. Homma et al., Solid State Ionics 182,
53 (2011).
[12] P. E. Blöchl, Phys. Rev. B 50, 17953(1994).
[13] J. P. Perdew, K. Burke, and M. Ernzerhof,
Phys Rev Lett. 77, 3865 (1996).

100

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102

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104

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Improvement and application of
all-electron mixed basis program
Kaoru OHNO
Faculty of Engineering Science, Yokohama National University79-5 Tokiwadai, Hodogaya-ku, Yokohama 240-8501
Using the all-electron mixed basis programusing TOMBO, and found out that all these

TOMBO, we performed first-principles moleculareffects are to decrease the energy gap. According

dynamics simulations of Mo and Au atom verticalto our results, the scLGW method can improvebombardments at the center of a six-membered

the one-shot G0W0 results in many cases. Thus,ring of C60 to create endohedral fullerenes. With

linearization is very powerful and effective. The

the kinetic energies of 40 eV and 80 eV, Mo andresult will be submitted soon.

Au atoms successfully penetrated inside the C60,

Lastly, we have applied our first-principle

and the endohedral fullerenes, M@C60 (M=Mo,

phase field method to Ti64 ternary alloys [2] andAu), were created. We confirmed that the createdto Ni-Ti binary alloys [3], and succeeded in

M@C60 continues to exist stably without breaking.

reproducing

This result is currently being submitted.

without introducing any empirical thermodynamic

theexperimental

microstructure

On the other hand, in the Green’s function

parameter. In the simulation of Ni-Ti alloys, we

method in many-body perturbation theory, all thenoticed an important tolerance behavior that theeffects of the Coulomb interaction between

result does not depend on the assumed atomic

electrons are incorporated in the self-energyalignment at all and found that the result does not

function. However, since the self-energy functionchange even if we used NiTi3 instead of NiTi2.

depends on the energy, the quasiparticle wave
functions,

i.e.,

the

basis functions,

Referenceswhich

diagonalize the Green’s function, are not only

[1] R. Kuwahara and K. Ohno, Phys. Rev. A 90,

effect032506;1-9 (2014).

ofrenormalization

of

the

energydependence of the self-energy has not been

[2] T. N. Pham, K. Ohno, R. Kuwahara, and S.

discussed much so far in the one-shot G0W0

Bhattacharyya, J. Phys.: Cond. Mat., 32,

approximation. Therefore, we discussed the effect

264001;1-9 (2020).

of

G0W0

[3] K. Ohno, M. Tsuchiya, R. Kuwahara, R.

approximation and the effect of linearization in

Sahara, S. Bhattacharyya, and T. N. Pham,the scGW approach (the scLGW method [1]) by

Comp. Mat. Sci. 191, 110284 (2021).

renormalization

in

the

one-shot105

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study of Efficient Training Data Generation Method forConstructing Artificial Neural Network Force Field I-II
Kohei Shimamura
Department of Physics,
Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555
Interatomic potential using an artificial

important for MD simulations (e.g. simulations

neural network (ANN potential) can not only

under NPT ensemble), we believe that training

provide high accuracy results by training first-of pressure is indispensable and uncertainty ofprinciples molecular dynamics (FPMD) datapressure should also be added to the indicator.

but also have low computational cost, which

We recently revealed that the pressure training

allows for large scale and long-term MD

is necessary to accurately calculate thermal

simulations. In this study, we aim to finding

conductivity, which is a fundamental physicalhow to efficiently generate the training data

quantity that characterize the thermal properties

required to construct the ANN potential. Activeof materials [1]. There is a well-known method

Learning (AL) is one of the promising

using long-term equilibrium MD data andgeneration methods that we are paying attention

Green-Kubo

to. In AL, firstly, several ANN potentials with

conductivity is calculated from the timedifferent initial values of weight parameters arecorrelation function of heat flux. It was also

constructed by training with the same data.

found that a clear relation holds between the

Since an output uncertainty (e.g. standard

heat flux formula and the pressure one derived

deviation) can be defined using the ANN

from the virial theorem [1]. Since the current

potentials, the magnitude of the uncertainty

standard training method mentioned above does

provides us an indicator to identify thenotcandidate data to be trained. However, there ispotentials with inadequate pressure accuracy

still

specific

are likely to show poor thermal conductivity.

indicators. The indicators currently employedThis result further emphasizes the importancefor AL are the uncertainty of potential energy

of pressure training. We are exploring betterand atomic force. This reflects the current

indicators of AL including pressure uncertainty.

room

standardfortraining

consideration

method,ofwhereformula,guarantee

wherepressure

theaccuracy,

thermalANN

ANN

potentials learn the potential energy and force

Reference

obtained from the FPMD.

[1] K. Shimamura, et al.: J. Chem. Phys. 153,

Considering that accurate pressure is also

234301 (2020).

106

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Refined Metadynamics and Elucidation of Reaction Mechanism of Polyalcohol
Dehydration in Hot Acidic Water
Tomomi Kondo1,2， Takehiko Sasaki1，Motoyuki Shiga2
1 Department of Complexity Science and Engineering, Graduate School of Frontier

Sciences, The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8561
2 Center for Computational Science and E-Systems, Japan Atomic Energy Agency

148-4 Kashiwanoha Campus, 178-4 Wakashiba, Kashiwa, Chiba, 277-0871

Subcritical water has high solubility offrom the difference (the point where the reaction

organic molecules and is expected to be applied

occurred). However, the height of the bias

as a reaction medium. Cyclization dehydration

potential represented by the Gaussian function

reaction of polyalcohol in hot water has been

and the frequency of addition are finite, and anproven to be efficient method for utilization oferror of several kBT occurs in the free energy

biomass materials [1]. In this study we proposed

surface. Whena new method of refinement (improved

different environmental conditions such as

metadynamics method: Refined MTD),

andpressure and temperature, or when there areapplied it to cyclization dehydration of 2,5-competitive reactions, it is necessary to estimate

Hexanediol (HDO) [2].

the accurate free energy surface with an error ofcomparing

reactionswithseveral kBT or less. In this study, we used
Refined MTD, which is a method to further
refine the free energy surface obtained by MTD
Fig. 1 Reaction for 2,5-Hexanediol (HDO)

calculation. First, the W(q) deposited from theIn the metadynamics method, by adding thereactant to the product by metadynamics

bias potential according to the frequency of

calculation is added to the potential of theappearance

surfacesystem as a time-independent bias potential.

characterized by the reaction coordinates (CV),

Then, the canonical distribution ρW(q) isa chemical reaction that does not occur on thegenerated by sufficiently sampling the system bytime scale of the usual molecular dynamics

molecular dynamics calculation biased by W (q).

method is induced. From the deposited bias

A(q) can be corrected using ρW(q) as shown inpotential W(q), the free energy surface A(q) = –

the

on

the

free

energyW (q) + const is obtained, and the minimum andsaddle points of A(q) are obtained.
The activation barrier ∆A can be obtained

107

following

equation[2].

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Sampling of the biased system must bemolecules (Fig. 3). For the higher acidic system

performed sufficiently until the entire freesuch as a system containing H2SO4, metastableenergy surface in the CV space is sampled, andstructure was found in the region where protons

especially when the activation barrier is to be

are added. In addition, the proton coordination

obtained, sampling not only near the minimum

number in the transition state was n ≈ 2.0 in thereaction energy point but also near the transition

system containing acidic molecules, whereas it

state is required.

was n ≈ 1.4 in the pure water system, indicating

Calculations were conducted using softwarethat the reaction process differs depending on the

PIMD [3] working with DFTB or VASP. The

acidity. The activation barrier ∆A (kcal/mol)

calculation system consists of 1 HDO molecule,were obtained as 50.6 (pure water), 39.6

30 water molecules, and acidic molecules such

(H2CO3), 35.4 (HCl), 26.3 (H2SO4).

as HCl added under the same thermodynamic
conditions as in Experiment [1] (20 MPa, 523 K).
CV is assumed for each product. The dihedral
angle φ between the hydroxyl group and themain chain, the difference d in the O-C distancesof leaving and bonding, and the proton
coordination number n of the hydroxyl groupwere set according to the reaction path.
By using Refined MTD for the HDO system,
the free energy surface of the system containing
Fig. 2 Free energy surfaces obtained for HDO
dehydration reaction obtained by Refined MTD.
(a) HCl aqueous solution, (b) pure water.

each acidic molecule was obtained. When the
difference was taken before and after thecorrection for the minimum free energy surface

Referencesof the system containing H2CO3, the maximum[1] A. Yamaguchi et al., Green Chem., 13,

was 7.3 kcal/mol, and the average was 1.6

873 (2011).

kcal/mol (RMSE). As a result of DFTB

[2] T. Kondo et al., J. Comput. Chem., 42, 156

calculation using Refined MTD, it was(2020).

confirmed that the free energy surface of the[3]http://ccse.jaea.go.jp/ja/download/pimd/in

cyclization-dehydration reaction of HDO differsdex.jp.html.

depending on the presence and type of acidic

108

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ultimate impedance of coherent heat conduction in van der
Waals graphene-MoS2 heterostructures
Hu Shiqian
Department of Mechanical Engineering,
The University of Tokyo, Hongo, Bunkyo City, Tokyo 113-8654
Toward the ultimate goal of designing small
thermal-conductivity

materials

temperature,wehereinat

Waals (vdW) heterostructure provide an idealroom

platform for the coherent phonon transport

themanipulation. Thus, in the current work, using

investigate

controllability of coherent phonon transport inthenon-equilibrium

van der Waals graphene-MoS2 heterostructures

simulations,with different stacking orders using non-phonon transport in vdW graphene-MoS2

equilibrium molecular dynamics simulations.

heterostructure with different stacking order.

wemolecular

investigatethedynamics
coherent

Using Bayesian optimization–based materials
informatics, the optimal stacking order ofgraphene and MoS2 is efficiently identified
from tens of thousands of candidates withvarying degrees of phonon localization. The
obtained thermal conductivity of the optimized
heterostructure (0.026 W/m-K) is significantly
lower than that of its building blocks, pristine
Figure. Schematics of the machine-learning

MoS2 and graphene.

method to combine the molecular dynamics (MD)There are growing efforts to control

and Bayesian optimization.

thermal transport via coherent phonons in the
one-dimensional

superlattice.

However,Theinhistogramofthephonongeneral, the difference in the intrinsic latticetransmissions in different disordered structure

structuresmaterials

exhibits a log-normal distribution, which

inevitably generate interface disorder during

reveals the localization of the coherent phonons.

the fabrication process, greatly limiting direct

Furthermore, the optimal stacking order of theexperimental observation of the coherent

graphene and MoS2 is efficiently identified

phonon transport. The flexible integration andfrom tens of thousands of candidates byatomistic interlayer smoothness of van dermachine learning. The significantly suppressed

of

the

constituent

109

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyoof the phonon transmission in the low
frequency (<5THz) phonons of the optimized
structure lead to a significant reduction of thethermalconductancecompared

with

the

pristine graphite. Finally, the effects of thedefect effect on the thermal conductivity ofgraphite and optimized structures are also
discussed. Our work provides a deep insight
into the coherent phonons transport behavior in
the atomistically smooth vdW structure, which
is beneficial for further development ofphononics.

References[1] S. Hu, S. Ju, C. Shao, J. Guo, B. Xu, M.
Ohnishi and J. Shiomi, Mater. Today Phys. 16,
100324 (2021)

110

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development and applications of ﬁrst principles
method for light-matter interactions beyond thedipole approximation
Takeshi IWASA
Faculty of Science, Hokkaido University
N10W8, Sapporo, Hokkaido 060-0810

Near ﬁeld refers to a non-propagating lightﬁeld. The interaction between the near-ﬁeld
and molecules can overcome the diﬀraction
limit and can induce non-dipolar excitations,oﬀering a unique platform for nanoscale spectroscopy and microscopy [1], as well as photochemistry [2]. Due to the localization of thenear-ﬁeld, theoretical framework beyond thedipole approximation is required. Thus, wehave developed a ﬁrst principles method basedon the multipolar Hamiltonian, in which, theinteraction is described by coupling the electric ﬁeld and the molecular polarization ﬁeld
integrating over the space. The method has
been used to study near-ﬁeld electronic excitations [3] and vibrational excitations, i.e., thenear-ﬁeld IR combined with electrodynamics
computations [4].
In this ﬁscal year, we have developed amethod for near-ﬁeld Raman [5]. The theoretical framework we established for near-ﬁeld Raman is as follows. First, the multipolar Hamiltonian is implemented into a real-time timedependent density functional code, namely,
Octopus 9.2 [6] and calculate the near-ﬁeld excited electron dynamics to obtain the induced
dipole moment of a molecule in the time domain, which is later Fourier transformed into
the frequency domain. The induced dipole moments are calculated 6N times (N is the number of atom in a molecule) for distorted geometries where one of the x, y, and z coordinatesof an atom is shifted slightly in either the pos-

itive and negative direction to obtain a derivative of the induced dipole moment with respect
to the atomic Cartesian coordinate, which isthen transformed into the normal coordinate
derivative using the transformation matrix obtained by a normal mode analysis, performed
separately. Finally, the Raman spectrum is obtained from the square of the absolute value ofthe normal coordinate derivatives.
As a demonstration, on- and oﬀ-resonancenear-ﬁeld Raman of benzene is studied. We
showed that the obtained Raman spectra are
well understood by considering both the spatial structure of the near ﬁeld and the molecular vibration in the oﬀ-resonance condition.
For the on-resonance condition, the Raman
spectra are governed by the transition moment, in addition to the selection rule of oﬀresonance Raman. Interestingly, on-resonanceRaman can be activated even when the nearﬁeld forbids the π−π ∗ transition at equilibriumgeometry due to vibronic couplings originatingfrom structural distortions.
References [1] R. B. Jaculbia, et al., Nat.
Nanotechnol. 15, 105 (2020). [2] E. Kazuma etal., Science, 360, 521 (2018). [3] T. Iwasa and
K. Nobusada, Phys. Rev. A, 80, 043409 (2009)
and 82, 043411 (2010). [4] T. Iwasa, et al.,J. Chem. Phys., 144, 124116 (2016) and 152,
164103 (2020). [6] M. Takenaka, T. Taketsugu,
T. Iwasa, J. Chem. Phys., 154, 024104 (2021).
[5] X. Andrade, et al., Phys. Chem. Chem.
Phys. 17, 31371 (2015).

111

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical analysis of inﬂuences of phonons onmagnetism
Yoshihiro GOHDA
Department of Materials Science and Engineering, Tokyo Institute of Technology
J1-3, Nagatsuta-cho 4259, Midori-ku, Yokohama 226-8502, Japan

In addition, ﬁrst-principles computations
are performed for magnetic materials including
permanent magnets [6] and multiferroic materials [7]. We also improved formulations to
calculate Jij in OpenMX [8] by introducing theorthogonalization of localized basis sets.
Tc
959 K

−20

Tc
1522 K
1.2

−40
−60
−80

563 K

argmin[Gmag + Gph]

−100

Cmag (meV/(K・atom))eqEmag (meV/atom)

It is extremely challenging to describe
magnetism at ﬁnite temperatures by ﬁrstprinciples electron theory. There are at least
two main contributions to excitation: magnons
and phonons. Even though there are attempts to include ﬁnite tempearture eﬀects
through exchange-coupling constants Jij inthe Heisenberg model by ﬁrst-principles calculations, dependences of phonons on magnetic states has been neglected. Such an approach is also computationally challenging, because ﬁrst-principles phonon calculations andMonte Carlo simulations are required for precise evaluations in addition to the standard
total-energy minimization.

1.0
0.8

argmin[Gmag]

0.6

−120

0.4

−140

0.2

−160
0

250 500 750 1000 1250 1500 1750

0Temperature (K)In this project, we propose a new ﬁrstprinciples scheme to evaluate the Curie temperature taking the magnetism-dependent
phonons and their feedback eﬀect to magnetism into account, and apply the scheme tobcc Fe [1] and some B2 and L10 compounds [2]as examples. In our framework, we minimize the total free energy in the explicit consideration of temperature eﬀects, because themagnetic and vibrational free energies correlate with each other. Both the inﬂuences ofmagnetism on phonons and the feedback effect from phonons to magnetism are taken into
account using phonon calculations by ALAMODE [3]. The feedback eﬀect reduced theCurie temperature of bcc Fe signiﬁcantly as
shown in Fig. 1, where the magnetic energy is
calculated by the ALPS code [4] with Jij obtained by Akai-KKR [5].

112

Figure 1: The equilibrium magnetic energy (solidlines) and the magnetic speciﬁc heat (dashed lines)of bcc Fe as a function of temperature obtained by
the minimization of the total free energy and by
the minimization of the magnetic free energy [1].
[1] T. Tanaka and Y. Gohda, npj Comput. Mater.
6, 184 (2020).
[2] T. Tanaka and Y. Gohda, J. Phys. Soc. Jpn.
89, 093705 (2020).
[3] T. Tadano, Y. Gohda, and S. Tsuneyuki, J.
Phys.: Condens. Matter 26, 225402 (2014).
[4] B. Bauer, S. Todo, et al., J. Stat. Mech. 2011,
P05001 (2011).
[5] H. Akai, J. Phys.: Condens. Matter 1, 8045
(1989).
[6] Y. Ainai, S. Kou, Y. Tatetsu, and Y. Gohda,
Jpn. J. Appl. Phys. 59, 060904 (2020).
[7] R. Costa–Amaral and Y. Gohda, J. Chem.
Phys. 152, 204701 (2020).
[8] T. Ozaki, Phys. Rev. B. 67, 155108 (2003).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Microscopic simulation for ultrafast electronic and atomic
response driven by strong and short laser pulses
Yasushi Shinohara1,2, Mizuki Tani2
1

Photon Science Center,

The University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-86562
2

Department of Nuclear Engineering and Management

The University of Tokyo, Hongo, Bunkyo-ku, Tokyo 113-8656

The development of coherent light sourcesin time-resolved reflectivity measurement [4].

allows us to realize various nonequilibrium

The semimetallic phase of TNS is realized above

material dynamics. Such processes are initiated328 K accompanied by structural phaseby electron excitation then undergoing atomic

transition. Our coauthors conduct experiments

motion via the electron-phonon interaction. A

to discover TrARPES with fine enough temporal

theoretical description of the nonequilibrium

resolution to disentangle different frequencies ofdynamics for the whole system composed ofcoherent phonon modes. By taking the Fourier

electrons and the nucleus is one of the mosttransform

challenging systems. We have investigated

FDARPES in which ARPES with a phonon

nonequilibrium

systems

frequency

directions,electron-phonon

a)

along

with

two

interaction

of

the

shows

TrARPES,electronic

weobtainstructuremodulation by the corresponding phonon. The

computation to understand the frequency-

metallic

domainphotoemission

structures coincide with 2 and 3 THz coherent

spectroscopy (FDARPES) under collaboration

phonons. To assign phonon modes to thewith experimentalists [1], and b) development of

frequencies, we perform density-functionalasemiclassicalperturbation theory (DFPT) calculation of themodeling of the optical response for simple

FDARPES. We reveal 2 THz phonon modes aremetals [2].

a motion connecting the two, semiconducting

angle-resolved

theoreticalframework of

In Ta2NiSe5 (TNS), it is reported that theandsemiconducting

electronicand semimetallic, structures.

coexistence of insulator and semimetallic

A mean-field type quantum theory hardly

electronic structures in time-resolved angle-

captures the colliding process leading toresolved

spectroscopy

relaxation or equilibrium among the electron(TrARPES) [3] and Coherent phonon generation

subsystem. A numerically efficient scheme tophotoemission

113

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

describe electron scattering is a semiclassical

TDDFT cost. We also perform systematic

equation of motion that the collision integral

benchmarking for nonlinear optical responses

added to the Vlasov equation. The Vlasov

compared with TDDFT. We are preparing theequation can be constructed from a quantum

manuscript for this work.

mechanical equation of motion, such as timedependent density-functional theory (TDDFT),by the Wigner transformation [5]. The Vlasov
equation is solved by the pseudo-particle methodthat the distribution function is described by asum of classical particles having finite spatial
and momentum width [5].

We develop atheoretical framework for a spatially periodic

References

system based on the Vlasov equation with the[1] Takeshi Suzuki, Yasushi Shinohara, et al.,pseudo-particle method and density-dependent

Phys. Rev. B 103 (2021) L121105.

functional taken from TDDFT, called Vlasov-[2] M. Tani, T. Otobe, Y. Shinohara, K.L.

LDA hereafter. A striking advantage of Vlasov-Ishikawa, in preparation.

LDA is the much lighter computational cost[3] K. Okazaki, Nature Communications volume

compared to typical time-dependent quantum

9 (2018) 4322.

mechanical simulations. We apply Vlasov-LDA[4] S. Y. Kim, et al., ACS Nano 10, 8888 (2016),

to crystalline Al and compare its results with

S. Mor, et al., Phys. Rev. B 97, 115154 (2018).

TDDFT. Optical conductivity from Vlasov-LDA[5] T. Fennel, et al., Eur. Phys. J. D 29, 367–378

perfectly(2004).

coincides

with

TDDFT,

while

computational is typically 50 times lighter than114

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ab initio Molecular Dynamics Study on Static Structure of
Glass Materials
Akihide KOURA
Technical Division,
Kumamoto University, Kurokami, Chuo-ku, Kumamoto, 860-8555
We have studied condensed matter systems,

are suitable for such test because Na has only

which are crystal, liquid, and amorphous

one valence electron and Ag2Se has manysystems. In this project, we aimed to clarify theelectrons. The calculation cost of the former isstatic structure of glass V2O5 under pressure

low, therefore, it is easy to compare the result

using our original QXMD code, which is

by ANN-MD with that by AIMD. While, theapplicable to perform ab initio molecular

cost of the latter is high, hence, the efficacy ofdynamics (AIMD) and empirical molecular

acceleration using ANN potential is checked.

dynamics (MD) simulations [1].

In this study, it was found that an optimizing

In order to investigate the static andequation including the force and virial terms,

dynamic properties of disordered materials, we

which were often ignored, was needed for theemployed one of the machine learning method,phase transition [3,4].

the artificial neural network (ANN) technic [2].
This method enables us to perform MD

References

simulations of the large scaled system with

[1] F. Shimojo, S. Fukushima, H. Kumazoe, M.

reasonably low calculation cost. However, theMisawa, S. Ohmura, P. Rajak, K. Shimamura, L.

best method to construct the interatomic

Bassman, S. Tiwari, R. K. Kalia, A. Nakano,potential of high transferability for any

and P. Vashishta: SoftwareX 10 (2019) 100307.

calculation conditions is not established. That is,[2] N. Artrith and A. Urban: Comput. Mater.

our priority mission is the establishment of

Sci. 114 (2016) 135.

construction of the ANN potential applicable[3] K. Shimamura, S. Fukushima, A. Koura, F.

for the wide range conditions based on the

Shimojo, M. Misawa, R. K. Kalia, A. Nakano, P.

result of AIMD simulations. For this purpose,

Vashishta et al. J. Chem. Phys. 151, 124303

we try to construct new ANN potentials for(2019).

different targets, liquid and crystal Na, and α-[4] A. Irie, S. Fukushima, A. Koura, K.

and β-phases of Ag2Se crystals. These targets

Shimamura, and F. Shimojo, in preparation.

115

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ab initio calculation for thermodynamic phase
diagram
Kazuma NAKAMURA
Quantum Physics Section, Kyushu Institute of Technology
1-1 Sensui-cho, Tobata, Kitakyushu, Fukuoka, 804-8550

For the purpose of ab initio quantitativeevaluation of thermodynamic physical properties of materials, thermodynamic phase diagrams based on first-principles calculations arecalculated. Focusing on metal hydrides, which
are important as hydrogen storage alloys, wewill evaluate their phase diagram and pressurecomposition-temperature curves. The free energy model under the regular solid solution
approximation is determined from the firstprinciples calculation, and the phase diagramof this model is obtained with the CALPHAD
method.
As the benchmark, the phase diagram ofthe metal hydride Ti-H sysmtem is calculated. The calculation flow is as follows: The
starting point is the Gibbs free energy calculation. The free energy consists of threeterms, the enthalpy term, the phonon term,
and the solid-solution entropy term, all ofwhich are evaluated by first-principles calculation. The enthalpy term is evaluated fromthe density-functional calculation for pureTi and TiH systems (using xTAPP [1] andVASP [2]). The phonon term is also evaluated from the first-principles phonon calculation for Ti and TiH (using PHONOPY [3]).
The solid-solution entropy term is evaluatedusing cluster-expansion and cluster-variational
methods [4]. For these calculations, a large
amount of structural data created by inserting hydrogen or voids into the tetrahedralinterstitial site is generated, where we consider a metal having a face-centered cubic (fcc)

structure and the resulting structural data series is written as fcc-tetrahedron series. This
structural series is generated using the software ATAT [5]. In this fcc-tetrahedron series, the total number of generated structural samples was 132. In addition to the
fcc-tetrahedron series, fcc-octahedron series,
body-centered-cubic (bcc)-tetrahedron series,
bcc-octahedron series, hexagonal close-packed(hcp)-tetrahedral series, hcp-octahedron series, etc. are generated. First-principles calculations are performed for each structural series
to obtain structural and energy data.
Next, we determine parameters of the effective model based on the regular solution approximation by fitting to the above obtained
first-principles calculation data. In the firststep, we use the cluster expansion method forthe ab initio data to obtain expansion coefficients of cluster model, and then, to evaluate
temperature dependence of the cluster model,
cluster-variational method is performed for thecluster-expansion function of each structuralseries, which give the first-principles free energy surface. Finally, for the resulting free energy surface, the parameters of the regular solution model are obtained by fitting:F(x, T ) = xGTiH (T ) + (1 − x)GTi (T )+ RT [x ln x + (1 − x) ln(1 − x)]+ x(1 − x)[(1 − x) − x]0 (L0 + L00 T )+ x(1 − x)[(1 − x) − x]1 (L1 + L01 T )+ x(1 − x)[(1 − x) − x]2 (L2 + L02 T ),
(1)

116

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

where GTiH (T ) and GTi (T ) are the free energies of TiH and Ti, respectively, and x or 1 − x
is fraction of vacancy or hydrogen in Ti. The
free energy is modeled with the following function as

density-functional calculation, (ii) the phonon
anharmonicity can affect the quantitative accuracy of the phase diagram boundary, and(iii) the quantitative accuracy of the interaction term depends highly on details of the cluster expansion (the cluster shape and expansion
Gα (T ) = aα +bα T +cα T ln T +dα T 2 +eα T −1 , (2) order, etc.) for the structure and energy data.
where the subscript α specifies TiH or Ti, andaα , bα , cα , dα , eα in Eq. (2) are determined byfitting to the ab initio phonon free energy data.
The third term in Eq. (1) is the mixing entropy
term in the binary alloy system. The remaining terms in Eq. (1) are the interaction termand L0 , L00 , L1 , L01 , L2 , and L02 parameters are
determined by fitting to the ab initio cluster
variational data. Table 1 lists our determinedparameters in Eqs. (1) and (2).
Table 1: Determined parameters in Eqs. (1)and (2).

bcc-tetra

fcc-tetra

Ti

Ti

TiH6

hcp-tetra
TiH2

Ti2

Ti2 H4abcde

6413.24 60753.56
71.0177.801−14.262−1.308−0.005−0.0090.001
0.000

1978.90 −27924.55
93.111−23.512−18.495
4.362−0.007−0.0240.001
0.000−1944.38 −15163.09
87.479−18.794−16.9213.644−0.009−0.024
0.001
0.000

L0
L0 ’
L1
L1 ’
L2
L2 ’

−105733.39−2.3605−24563.95−1.0794−99788.53
0.078713618.96−0.267−9933.31
0.1296−5491.55−0.43764345.96−1.7241−11022.69−1.5862−12354.91
2.8456

From the free energy curve of the regular solution model [Eq. (1)] obtained above, a phase
diagram based on the CALPHAD method was
calculated by using the software PANDAT [6].
Figure 1 (a) shows our calculated phase diagram of Ti-H sysmtem. The panel (b) also
shows experimental phase diagram [7]. Fromthe comparison between the two, we found that
our result reasonably reproduces the experimental result. A Python Script was developed
to generate PANDAT inputs from the results ofthe present regular solution models. We foundthat (i) the entropy term can be sensitive tothe exchange-correlation functional used in the

Figure 1: Thermodynamic phase diagram of
TiH: (a) simulation and (b) experiment [7].

References[1] http://xtapp.cp.is.s.u-tokyo.ac.jp[2] https://www.vasp.at[3] https://atztogo.github.io/phonopy[4] M. Sluiter, D. de Fontaine, X. Q. Guo, R.
Podloucky, and A.J.Freeman, Phys. Rev.
B 16, 42 10460 (1990).
[5] https://www.brown.edu/Departments/
Engineering/Labs/avdw/atat/[6] https://computherm.com/[7] A. San-Martin, F.D. Manchester, Bulletinof Alloy Phase Diagrams 8, 30–42 (1987).

117

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Oxygen vacancy formation in metal-doped CeO2
nanocrystals
1

Akira YOKO1 , Kazutoshi INOUE1 , Mitsuhiro SAITO2 , and Yuichi IKUHARA1,2,∗
Advanced Institute for Materials Research, Tohoku University, Sendai, Miyagi, 980-8577
2
Institute of Engineering Innovation, The University of Tokyo, Yayoi, Tokyo, 113-8656

We studied Cr-doped cubic {100}-faceted
CeO2 nanocrystals (NCs) with an average sizeof 7.8 nm fabricated by a supercritical water reaction. A considerably large amountof Ce3+ ions was detected in the Cr-doped
CeO2 NCs by scanning transmission electron
microscopy combined with electron energy loss
spectroscopy (EELS). The Cr dopants substituted the Ce sites in the amount of approximately 3 mol%. We experimentally observedthat the oxygen-storage capacity (OSC) was
substantially improved by a low amount of Cr
doping, which can be attributed to the low oxygen vacancy formation energy and high mobility of oxygen atoms by doping Cr in CeO2 .
Plane-wave basis density functional theory(DFT) simulations were performed by using
the VASP code to understand the eﬀects of
the Cr dopant on oxygen vacancy (Vo) formation. A Ce atom was substituted by one
Cr atom in the 96-atom 2 × 2 × 2 supercellof CeO2 (Ce32 O64 ) with a Monkhorst–Pack kpoint mesh of 4 × 4 × 4, which is equivalent
to the loading amount of Cr at 3 mol%. The
incorporation of Cr in 3+ charge state canbe compensated by the formation of an extra Vo (per two Cr3+ ions) or a Vo and a
Ce3+ ion while the oxidation of Cr-doped CeO2
NCs should create Cr4+ ions. Two Ce3+ ionswere located in the next nearest neighbor positions with respect to the Vo, consistent withprevious studies of CeO2 with DFT+U. The
Bader charge of the Ce3+ and Ce4+ ions was
set +2.11|e| and +2.44|e|, respectively. The
Vo formation energy (E(Vo)) in the Cr-doped
CeO2 was calculated as 0.99 eV, which wassubstantially decreased from 2.00 eV in the
non-doped case. The high OSC performancecan be attributed to the contribution of the valence change of Cr to E(Vo), and the structuraleﬀect of Cr doping on E(Vo). Only 3 mol%doping improved the OSC, suggesting that Cr
doping aﬀects the structure of CeO2 significantly. The results of layer-by-layer EELS
analysis indicated a signiﬁcant increase in theamount of Ce3+ by Cr doping particularly in
the internal atomic layers, which is more thanthe mere compensation of Cr3+ with Vos. The
low E(Vo) of Cr-doped CeO2 NCs can lead toa signiﬁcant increase of Ce3+ ions even with a
low amount of Cr doping, as observed in theexperiments.
In summary, DFT calculations demonstrated
that the Cr dopant reduces the E(Vo), resulting in the increase of the mobility of oxygen
atoms in the nano-sized CeO2 . The high concentration of Vos as well as the high oxygen
diﬀusivity improve the OSC performance of
Cr-doped CeO2 NCs, compared with the nondoped CeO2 NCs. These eﬀects provides a fundamental understanding of the role of dopantsin formation and distribution of Vos in themetal-doped CeO2 NCs [1].

References[1] X. Hao, A. Yoko, K. Inoue, Y. Xu, M.
Saito, C. Chen, G. Seong, T. Tomai, S.
Takami, A.L. Shluger, B. Xu, T. Adschiri,
Y. Ikuhara: Acta Mater. 203, 116473(2021).

118

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Oxygen vacancy formation in metal-doped CeO2
nanocrystals
1

Akira YOKO1 , Kazutoshi INOUE1 , Mitsuhiro SAITO2 , and Yuichi IKUHARA1,2,∗
Advanced Institute for Materials Research, Tohoku University, Sendai, Miyagi, 980-8577
2
Institute of Engineering Innovation, The University of Tokyo, Yayoi, Tokyo, 113-8656

We studied Cr-doped cubic {100}-faceted
CeO2 nanocrystals (NCs) with an average sizeof 7.8 nm fabricated by a supercritical water reaction. A considerably large amountof Ce3+ ions was detected in the Cr-doped
CeO2 NCs by scanning transmission electron
microscopy combined with electron energy loss
spectroscopy (EELS). The Cr dopants substituted the Ce sites in the amount of approximately 3 mol%. We experimentally observedthat the oxygen-storage capacity (OSC) was
substantially improved by a low amount of Cr
doping, which can be attributed to the low oxygen vacancy formation energy and high mobility of oxygen atoms by doping Cr in CeO2 .
Plane-wave basis density functional theory(DFT) simulations were performed by using
the VASP code to understand the eﬀects of
the Cr dopant on oxygen vacancy (Vo) formation. A Ce atom was substituted by one
Cr atom in the 96-atom 2 × 2 × 2 supercellof CeO2 (Ce32 O64 ) with a Monkhorst–Pack kpoint mesh of 4 × 4 × 4, which is equivalent
to the loading amount of Cr at 3 mol%. The
incorporation of Cr in 3+ charge state canbe compensated by the formation of an extra Vo (per two Cr3+ ions) or a Vo and a
Ce3+ ion while the oxidation of Cr-doped CeO2
NCs should create Cr4+ ions. Two Ce3+ ionswere located in the next nearest neighbor positions with respect to the Vo, consistent withprevious studies of CeO2 with DFT+U. The
Bader charge of the Ce3+ and Ce4+ ions was
set +2.11|e| and +2.44|e|, respectively. The
Vo formation energy (E(Vo)) in the Cr-doped
CeO2 was calculated as 0.99 eV, which wassubstantially decreased from 2.00 eV in the
non-doped case. The high OSC performancecan be attributed to the contribution of the valence change of Cr to E(Vo), and the structuraleﬀect of Cr doping on E(Vo). Only 3 mol%doping improved the OSC, suggesting that Cr
doping aﬀects the structure of CeO2 significantly. The results of layer-by-layer EELS
analysis indicated a signiﬁcant increase in theamount of Ce3+ by Cr doping particularly in
the internal atomic layers, which is more thanthe mere compensation of Cr3+ with Vos. The
low E(Vo) of Cr-doped CeO2 NCs can lead toa signiﬁcant increase of Ce3+ ions even with a
low amount of Cr doping, as observed in theexperiments.
In summary, DFT calculations demonstrated
that the Cr dopant reduces the E(Vo), resulting in the increase of the mobility of oxygen
atoms in the nano-sized CeO2 . The high concentration of Vos as well as the high oxygen
diﬀusivity improve the OSC performance of
Cr-doped CeO2 NCs, compared with the nondoped CeO2 NCs. These eﬀects provides a fundamental understanding of the role of dopantsin formation and distribution of Vos in themetal-doped CeO2 NCs [1].

References[1] X. Hao, A. Yoko, K. Inoue, Y. Xu, M.
Saito, C. Chen, G. Seong, T. Tomai, S.
Takami, A.L. Shluger, B. Xu, T. Adschiri,
Y. Ikuhara: Acta Mater. 203, 116473(2021).

119

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyovan der Waals density functional study of Cu phthalocyanine
adsorbed on the Au(110) surface
Yuji HAMAMOTO
Department of Precision Engineering, Graduate School of Engineering,Osaka University, Yamada-oka, Suita, Osaka 565-0871
The lowest molecular orbital (LUMO) plays

STM measurements [1]. The van der Waals

an essential role in the electronic transport(vdW) interaction between CuPc and Au(110) is

across a metal-organic interface. Since surface

taken account of by the vdW-DF method [2].

adsorption distorts the molecular structure,

Our calculated results indicate that CuPc

influencing the properties of LUMO, it is ofprefers to adsorb on the center of the Au adatoms

particular importance to understand the interface

with an in-plane rotation as shown in Fig. 1,

structure microscopically. Here we investigate

irrespective of the number of adatoms. The

the geometric and electronic structures at a

projected density of states (PDOS) onto themetal-organic interface of Cu phthalocyanine

doubly degenerate LUMO, labeled as eg(1) and(CuPc) on the Au(110) surface [1]. The (1! 2)

eg(2), of CuPc is plotted as a function of energy*+,-!.!/0ï#

missing-row reconstructed surface of Au(110) is
modeled by removing Au atomic rows from aperiodically repeated 6! 4 unit cell of the*+,-!.!/0ï#Au(110) slab composed of six atomic layers. A
CuPc molecule is adsorbed on a missing row, inwhich n Au atoms with n = 0, 2, 4, and 6 are*+,-!.!/0ï#*+,-!.!/0

ï#

added below CuPc to reproduce the finding ofFig. 1: Schematic views of CuPc on the missingrow reconstructed Au(110) surface with n = 4.

!(
!'
!&
!%
!$
!#
!"
!( !
!'
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!'
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!$
!#
!"
ï"4&

/12#3
/12$3

n!)!"

!

!

!

!

!

!

!

n!)!$

!
n!)!&

!
n!)!(

ï"4$

"4"

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!

!

!

!

!

!

"4(

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#4"

"4$
"4&
E!ï!E6!.!/0

The blue (red) balloons show the isosurfaces ofFig. 2: Density of states projected onto the eg(1)absolute square of eg(1) [eg(2)].

[eg(2)] orbitals of CuPc.

120

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

in Fig. 2, where the center of the peaks for thestates is enhanced for large n. Our results reveal

LUMO-derived states is lowered roughlythat the LUMO of CuPc is sensitive to themonotonically as n is increased, in gooddetailed structures of the reconstructed Au(110)agreement with the results of STS measurements.

surfaces.

The lowering of the peaks is qualitatively

References

consistent with lowering of the effective[1] H. Koshida, H. Okuyama, S. Hatta, T.

potential of the bare surfaces as a function of n.

Aruga, Y. Hamamoto, I. Hamada, and Y.

The splitting of the peaks suggests that the

Morikawa, J. Phys. Chem. C 124, 17696

hybridization between CuPc LUMO and surface(2020).

[2] M. Dion, H. Rydberg, E. Schröder, D. C.
Langreth, and B. I. Lundqvist, Phys.
Rev. Lett. 92, 246401 (2004).

121

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles study of molecule/metal interfaces
Ikutaro Hamada
Department of Precision Science and Technology, Graduate School of Engineering,Osaka University, 2-1 Yamada-Oka, Suita, Osaka 565-0871
Carbon-basedasExperimentally, the DAPh molecule isgraphene and nanographene have attracted

thermally reacted into a cyclodehydrogenatedenormous attention, owing to their fascinating

diazulenopyrene (DAPy), but the reaction

electronic, optical, and magnetic properties. Forintermediate has not been determined. We

precise fabrication of nanographene, on-surface

performed extensive DFT calculations andsynthesis has been developed, in which

successfully identified the intermediate asprecursor molecules are thermally induced tohydro-diazulenopyrenyl (hDAPyr). By using areact on a surface, and the technique has been

Cu-terminal

proven to be powerful to fabricate graphene

cyclodehydrogenation of hDAPyr to form

based nanostructures. In this work, we propose

DAPyr. To understand the reaction mechanism,

an alternative method, in which a tip of scanning

we used a 10-atom pyramidal model Cu tip overtunneling microscopy/non-contact-atomic-force

hDAPyr and could reproduce the tip-induced

microscopy is utilized as a manipulable metal

cyclodehydrogenation reaction. Furthermore,catalyst, which activates cyclodehydrogenation

we clarified the detailed potential energy surfaceof hydrocarbons [1].

and by the electronic structure analysis, we

we

used

nanomaterials,

suchdiazuleno[1,2-c:2′,1′-

tip,

we

inducedtherevealed the electronic origin of the tip-inducedg]phenanthrene (DAPh), as well as 10,10′-

catalytic dehydrogenation reaction.

dibromo-9,9′-bianthracene (DBBA) adsorbed

References

on a Cu(100) surface, to demonstrate the tip-

[1] A. Shiotari et al: Nano Lett 20 (2020) 8339.

induced cyclodehydrogenation reaction. To[2] M. Dion et al.: Phys. Rev Lett. 92 (2014)

investigate the mechanism of the tip-induced

246401.

reaction, we performed atomistic simulations[3] https://statedoc.readthedocs.io/

based on density functional theory (DFT) with

[4] J. Wu and F. Gygi: J. Chem. Phys 136 (2012)

the van der Waals (vdW) density functional

224107.

(vdW-DF) [2] as implemented in our in-house[5] Y. Hamamoto, I. Hamada, K. Inagaki, and Y.

DFT code STATE [3-6], to describe theMorikawa: Phys. Rev. B 93 (2016) 245440.

interaction between organic molecule and metal[6] I. Hamada: Phys. Rev. B 89 (2014)

accurately.

121103(R).

122

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical study of oxygen-redox chemistry in spinel oxides
Atsuo YAMADA
Department of Chemical System Engineering,
The University of Tokyo, Bunkyo-ku, Hongo, Tokyo 113-8656
Oxygen-redox chemistry has recently paved

program and molecular orbitals were built witha path to develop large-capacity cathodemaximally localized Wannier functions usingmaterials for rechargeable batteries. Despite

Wannier90 code.

oxygen-redox

The presence of ionic Mg2+ in spinelcathodes, few studies have been reported for

LiMg0.5Mn1.5O4 brings labile O 2p states forthe oxygen-redox reaction in spinel oxides. In

oxygen-redox activity. However, in contrast

this work, we theoretically uncover the oxygen-with the dominant Mn-O interactions that could

redox behavior in the stable spinel framework

stabilize oxidized oxide ions in a typicalusing the density functional theory calculations.

lithium-rich layered oxide Li2MnO3, the spinel

We performed all calculations using Vienna

structure is dominated by O-O interactions near

Ab-initio Simulation Package. The projector-

the Fermi level, which are less able to stabilize

augmented wave method with a plane-wave

holes. Consequently, the spinel oxide isbasis set was used. We applied the U values ofpredicted to undergo structural degradation

4.84 eV and 3.90 eV for Mn in the spinel andmore easily during the oxygen-redox reactions.

vasteffortson

exploringlayered structures, respectively. The HSE06
hybrid functional was employed for calculating

References

electronic structures. The crystal orbital overlap[1] X.-M. Shi, E. Watanabe, M. Okubo, A.

population was computed with the Lobster

Yamada, Chem. Mater., 32 (2020) 7181.

Fig. 1 (a) Spinel LiMg0.5Mn1.5O4. Electronic structures of (b) spinel and (c) layered oxides.

123Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Order-disorder transition in ultrahigh-pressure phase of the
Na-Mg-F system
Koichiro Umemoto
Earth-Life Science Institute,Tokyo Institute of Technology, 2-12-1 Meguro-ku, Ookayama, Tokyo 152-8550
MgSiO3 bridgmanite with the orthorhombic

order-disorder transition has been predicted in I-

perovskite structure is a major constituent of the

42d-type Mg2GeO4 [6], a low-pressure analog oflower mantle of the Earth. It takes the post-

Mg2SiO4.

perovskite (PPV) structure near the core-mantle

In this study, we investigated the order-

boundary pressure (~125 GPa). The PPV phase

disorder transition in NaMg2F5 by firstis the final form of MgSiO3 in the Earth.

principles [7]. To deal with the order-disorder

However, at much higher pressures in “super-transition, we prepared as many configurations

Earths” which are exoplanets expected to be

as possible in a supercell of 64 atoms andterrestrial with masses much larger than thecalculated a partition function. Then, the order-

Earth, MgSiO3 PPV should undergo “post-PPV”

disorder transition temperature (Tc) can betransitions. So far, first principles studies haveobtained by locating the peak temperature ofpredicted the three-stage dissociation of MgSiO3

heat capacity calculated from the partition

PPV: MgSiO3 PPV → I-42d-type Mg2SiO4 +function. Our calculations showed that Tc is

P21/c-type MgSi2O5 → Mg2SiO4 + Fe2P-type

1500~2000 K over 20~100 GPa. The order-

SiO2 → CsCl-type MgO + SiO2 [1-3].

disorder transition was not taken into account in

NaMg2F5 is a low-pressure analog ofthe experiment [5]. We expect the disordered

MgSi2O5. Theoretically NaMgF3 PPV wasphase may show a better explanation of the XRD

predicted to dissociate into NaF and NaMg2F5

pattern in the experiment.

[4] and this prediction has been confirmed by aSince NaMg2F5 is the low-pressure analog ofrecent experiment [5]. There are two kinds of the

MgSi2O5, the order-disorder transition predicted

Mg sites. One of them is very similar to the Na

in this study is expected to occur also insite; both Na and Mg atoms are surrounded by 9

MgSi2O5 and will play an important role in

F atoms which form tricapped triangular prisms.

modeling interiors of super-Earths.

This similarity leads us to an idea of order-

The first principles calculations in this study

disorder transition at high temperature over thewere performed using the Quantum-Espresso

cation sublattice of Na and Mg atoms. A similar

package on the supercomputer (system B) at the124

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Umemoto and R. M. Wentzcovitch, JPS Conf.

Institute for Solid State Physics.

Proc. 4, 011002 (2015).

References[5] R. Dutta, et al.: Proc. Nat. Acad. Sci, 116,

[1] S. Q. Wu, et al.: J. Phys.: Condens. Matter 26

19324 (2019).

(2014) 035402.

[6] K. Umemoto and R. M. Wentzcovtich:[2] H. Niu et al.: Sci. Rep. 5 (2015) 18347.

arXiv:2012.08056.

[3] K. Umemoto et al.: Earth Planet. Sci. Lett.

[7] K. Umemoto and R. M. Wentzcovitch, in

478 (2017) 40.

preparation.

[4] K. Umemoto and R. M. Wentzcovitch: K.

125

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First principles study of effect of Al impurity on the post-postperovskite transitions
Koichiro Umemoto
Earth-Life Science Institute,Tokyo Institute of Technology, 2-12-1 Meguro-ku, Ookayama, Tokyo 152-8550
MgSiO3 bridgmanite with the orthorhombic

The presence of Al atoms decreases theperovskite structure is a major constituent oftransition pressure of the first dissociation.

the lower mantle of the Earth. It takes the post-

Considering effects of configuration entropy atperovskite (PPV) structure near the core-mantle

high temperature, Al atoms start to exist also inboundary pressure (~125 GPa). The PPV phase

MgSi2O5.

is the final form of MgSiO3 in the Earth.

Recently, we predicted a new temperature-

However, at much higher pressures in “super-induced order-disorder transition in I-42d-type

Earths” which are exoplanets expected to be

Mg2GeO4, a low-pressure analog of Mg2SiO4terrestrial with masses much larger than the[4]. The knowledge obtained in this study will

Earth, MgSiO3 PPV should undergo “post-PPV”

be utilized for the study in the post-PPVtransitions. So far, first principles studies havetransition at high temperature, which ispredicted

expected to occur in super-Earths.

thethree-stage

dissociationof

MgSiO3 PPV: MgSiO3 PPV → I-42d-type

The first principles calculations in this study

Mg2SiO4 + P21/c-type MgSi2O5 → Mg2SiO4 +were performed using the Quantum-Espresso

Fe2P-type SiO2 → CsCl-type MgO + SiO2 [1-3].

package on the supercomputer (system B) at

In real super-Earths, impurities may play animportant

role

in

the

above

the Institute for Solid State Physics.

post-PPVtransitions. In this study, we investigated theReferences

effect of Al atoms, one of major candidates of[1] S. Q. Wu, et al.: J. Phys.: Condens. Matter

impurities, on the post-PPV transitions. To do it,

26 (2014) 035402.

we prepared supercells of (Mg1-xAlx)(Si1-[2] H. Niu et al.: Sci. Rep. 5 (2015) 18347.

xAlx)O3,[3] K. Umemoto et al.: Earth Planet. Sci. Lett.

(Mg2-xAlx)(Si1-xAlx)O4, and (Mg1-

xAlx)(Si2-xAlx)O5, for x=0.25, 0.125, and 0.0625.

478 (2017) 40.

We found that Al atoms prefer to exist in[4] K. Umemoto and R. M. Wentzcovtich:

Mg2SiO4 after the fist post-PPV dissociation.

arXiv:2012.08056.

126

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles molecular dynamics study of water/TiO2
interfaces using hybrid functionals
Tatsuhiko OHTO
Graduate School of Engineering Science,
Osaka University, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531
Density functional theory-based molecular

We employed the CP2K code [2], which is

dynamics simulations are increasingly being

based on the mixed Gaussian and plane wave

usedbasis sets. The simulation of the water/TiO2

forsimulating

aqueousinterfaces.

Nonetheless, the choice of the appropriate

interface is on-going.

density functional, critically affecting theoutcome of the simulation, has remained
arbitrary. Here, we assess the performance ofvarious exchange-correlation (XC) functionals,
based on the metrics relevant to sum-frequency
generation spectroscopy. The structure anddynamics of water at the water-air interface aregoverned by heterogeneous intermolecularinteractions, therefore providing a criticalbenchmark for XC functionals. We find that the
revPBE and revPBE0 with the dispersion

Fig. 1: The ability of different functionals tocorrection show excellent performance. The

accurately predict water properties is directly

poor performance of the empirically optimized

compared. The smaller (larger) score 𝜅density-functionalcorresponds to better (worse) predictive power(M06-L)

manifests

theimportance of satisfying exact functionalof the functional [1].

condition. Understanding the performance ofdifferent XC functionals can aid resolving theReferences

controversial interpretation of the interfacial[1] T. Ohto et al. J. Phys. Chem. Lett. 10, 4914

water structure and direct the design of novel,(2019).

improved XC functionals better suited to[2]

describe the heterogeneous interactions in

http://cp2k.berlios.de/condensed phases. [1]

127

The

CP2K

developersgroup,

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ab Initio Band Structure Calculation of InAsSb
Using VASP Based on Hybrid Density Functional Theory
Hiroki I. FUJISHIRO, Yoshitaka MATSUMOTO, and Akira ENDOH
Department of Applied Electronics,
Tokyo University of Science, Niijuku, Katsushika, Tokyo 125-8585
In 2019, we carried out ab initio band

The terahertz band (0.1 to 10 THz) is the

structure

capacity communications and sensing systems.

compressively strained InSb using Vienna Ab

Sb-based high electron mobility transistors

initio Simulation Package (VASP) based on the(HEMTs) are one of the most promising

method in the local density approximation todevices that can operate in the terahertz band.

obtain band parameters [5]. We used the hybrid

In our previous works, we developed InSb [1,coefficient of the density functional [6]. The

2] and GaInSb [3] channel HEMTs. In order tohybridachieve higher speed operation of HEMTs, it ismodification

desirable that the electron effective mass in the

Ernzerhof 0). The functional is constructed bychannel semiconductor is lighter and thethe mixing of a fraction 𝛼 of the Fock exchange

electron concentration in the channel layer iswith a fraction 1 − 𝛼 of the PBE exchange. The

higher. InAsSb is a semiconductor that satisfies

exchange-correlation

the above conditions [4].

expressed by the following equation:

Bandgap energy, Eg [eV]main radio resource for future high-speed large-

calculations

functional
of

of

used

unstrained

in

PBE0

energy0.4
Eg = 0.7191x2 - 0.5257x + 0.159

0.3
0.2
0.1
0.0
0.0

0.2

0.4
0.6
InAs content, x

0.8

Fig. 1: InAs content x dependence of bandgap energy 𝐸 .

128

1.0

[6]

was

and

a

(Perdew-Burke-

𝐸

can

be

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo(1)

mass in the  valley 𝑚∗. The x-dependence ofis the𝑚∗shows a tendency similar to that of 𝐸 . The

PBE𝑚∗ values of InAsxSb1-x at x = 0.25 and 0.50 are

correlation [6]. We obtained the bandgap

lighter than that of InSb. It is well known thatenergy 𝐸 closest to the literature value by

the 𝑚∗ in InSb is the lightest among group III-using 𝛼 = 0.21 for InSb. In this work, we

V compound semiconductors. According to theapplied this method to InAsSb to explore thecalculations in this study, the 𝑚∗ in InAsSb ispotential of InAsSb channel HEMTs.

lighter than that in InSb depending on the InAs

𝐸

= 𝛼𝐸 + (1 − 𝛼)𝐸+𝐸

where 𝐸 is the Fock exchange, 𝐸
PBE

exchange,

and 𝐸

is

the

First, we applied this method to InAs. We

content. Therefore, InAsSb channel HEMTs

obtained the 𝐸 closest to the literature one byhave a potential to be the fastest of all HEMTs

using 𝛼 = 0.24 . We carried out the bandusing group III-V compound semiconductors.

structure calculations of InAsxSb1-x at x = 0.25,

Referencesused linearly interpolated values. Figure 1[1] K. Isono et al.: Proc. CSW2016, WeD1-5.

shows the InAs content x dependence of[2] N. Oka et al.: Abst. TWHM2017, p. 83.

bandgap energy 𝐸 . The x-dependence of 𝐸 is[3] K. Osawa et al.: Abst. TWHM2019, p. 53.

not linear and shows a downwardly convex[4] O. Berolo et al.: Phys. Rev. B 8 (1973) 3794.

dependency. We obtained the electron effective[5] H. I. Fujishiro et al.: Activity Report 2019,

masses 𝑚∗’s in the  valley of InAsSb from thep. 153.

calculated band structures. Figure 2 shows the[6] T. Garwood et al.: Infrared Physics &InAs content x dependence of electron effective

Technology, 2017.

Electron effective mass,
m*/m00.50, and 0.75. For the 𝛼 values of InAsSb, we

0.020
m* = 0.0309x2 - 0.0217x + 0.0091

0.015
0.010
0.005
0.000
0.0

0.2

0.4
0.6
InAs content, x

0.8

1.0

Fig. 2: InAs content x dependence of electron effective mass in  valley 𝑚∗. 𝑚 is electron rest
mass.

129

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

DFT calculation of atomic displacement captured by energy
dissipation channel of noncontact atomic force microscope
Toyoko ARAI1, Takahiro Kato1, Jun-Ichi Iwata2, Atsushi Oshiyama3
1

Graduate school of Natural Science and Technology, Kanazawa University, Kanazawa,
Ishikawa, 920-1192
2
3AdvanceSoft Corporation, Tokyo 101-0062

IMaSS, Nagoya University, Nagoya, Aichi 464-8601

In the last two decades the conservative andbond formation in an alternative atomic

non-conservative (dissipative) force interactions

configuration of the Si surface atoms, including

between a tip and a sample in proximity have

the Si atom at the apex of AFM tip. In this study,

been intensively examined by non-contact

to elucidate the phenomena, the surface

atomicIndiffusion potentials of a Si adatom wereparticular, the channel of nc-AFM to measurecalculated using real-space density functional

the energy dissipation through the non-theory (RSDFT) [2] when the Si tip was brought

conservative

beencloser to the Si(111)-(7×7) surface. RSDFT is aregarded to have great potential to explore nano-first-principles program developed by Oshiyama

mechanical phenomena; the dissipation channel

and Iwata, which uses a real-space difference

gives the change in the amount of mechanicalmethod and a pseudopotential method.

force

microscopy

force(nc-AFM).

interactions

hasenergy to maintain the constant oscillation

First, we optimized the structures of aamplitude of an AFM cantilever. We had

Si(111)-(7×7) reconstructed surface consisting

experimentally found that, when the nc-AFM

of 298 Si atoms and 49 H atoms and a [001]image showed the high resolution for theoriented Si tip by RSDFT. Then, while the tip

individual adatoms on a Si(111)-(7×7) surface,

was placed over the hollow site and brought

the simultaneously obtained energy dissipation

closer from 5.0 Å to 3.0 Å, the surface diffusion

signal increased in close proximity over the

potentials for a corner Si adatom were calculated

hollow sites surrounded by a Si adatom and a Si

from the original position of the Si adaom to therest atom with a dangling bond per each [1].

neighboring hollow site. It is known that theBased on the experimental results, the dynamic

hollow site is a meta stable site for the adatom,

atomic processes responsible for the dissipationand there is a diffusion barrier between the

had been discussed in regard to breaking of theoriginal adatom site and the hollow site. Our

backbonds of the Si adatom and subsequentcalculations indicated that the diffusion barrier

130

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyoheight was lowered as the tip was approached.
However, we did not obtain the evidence forpromotion of the adatom diffusion from theadatom site to the hollow site only by bringing
the tip closer. Next, we calculated the structurechanges and the forces for two cases: the Si atomon the original adatom site or on the hollow sitewith the tip approaching over the hollow site, as
shown in Fig. 1. Even for the Si atom on the moststable adatom site, when the tip approaches thehollow site, the Si atom was lifted up (Fig. 1(a–e)). But the Si atom did not move to the hollow
site even when the tip was closer from a heightof 3.0 Å (Fig. 1(e)). For the Si atom on thehollow site, it was found that the strong force
acted between the tip Si atom and the Si atom on
the hollow site (Fig. 1(f–j)), as a result ofbonding formation between them. The paper ofthis study is under preparation.
Fig. 1 Calculated structures of Si(111)-(7×7)
reconstructed surface and [001] oriented Si
tip. (a–e) For the Si on the adatom site,
denoted by the red circles. (f–j) For the Si on
the hollow site. The number shown with theunit of Å shows the vertical separation
between the tip atom and the Si atom on thesite.

References[1] T. Arai, R. Inamura, D. Kura, and M.
Tomitori, Phys. Rev. B 97, 115428 (2018).
[2] J.-I. Iwata, D. Takahashi, A. Oshiyama et al.,J. Comput. Phys. 229, 2339 (2010).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Construction of magnetic materials database by
KKR Green’s function method
Tetsuya FUKUSHIMA
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

We have developed an automatic exhaustive calculation tool which is based on the
Korriga-Kohn-Rostoker coherent potential approximation (KKR-CPA) method. Our tool
can explore the huge materials space consisting of disordered systems and construct largescale materials databases. In this year, we implemented a new feature in our tool, where
electronic structures, magnetic properties, andtransport properties at finite temperature canbe calculated [1].
In order to calculate electronic structuresat finite temperature, we incorporate the effects of local phonon excitations and spin-wave(magnon) excitations in the framework of the
KKR-CPA method. In the KKR Green’s function method, the single-site t-matrix is the sumof the coefficients of partial wave expansion ateach atomic position and contains informationof the single-site scattering effect. We can thus
replace the multiple scattering effect by an effective medium potential using CPA. We treat
local phonon excitation and magnon excitation
as the configuration average with respect to the
local phonon displacements and local moment
disorder (LMD) states, respectively.
For CPA calculation of the local phonon excitation, the probabilities of the atomic displacements must be known. Here, we employ an alloy-analogy model. The single-sitet-matrix changes responding to the atomic displacements and has to be determined selfconsistently. In this case, it is convenient toexpand each single-site t-matrix centered on

the displaced position for self-consistent calculation. However, later, we must re-expand thedisplaced single-site t-matrix to partial waves
centered on the undisplaced atomic position,and transform the scattering matrix for the
displaced potential into that defined with respect to the regular lattice position. Thisis possible because the effect of atomic displacement on the electronic structure is local.
Accordingly, the backscattering term of theGreen’s function referring to the regular latticeis also obtained. In the present calculations,
we take six directions (i.e., {0,0,1} cubic directions) into consideration for the local phonon
displacements of each atom.
To handle the magnon excitation, we use the
LMD model. When the temperature increases,
the spin tilts slightly away from the directionof the magnetization, and its effect propagatesto surrounding spins, namely, spin-wave excitation. We consider the configuration average of the linear combination of the spin flips
at every site. This model is called the LMD
state. We estimate it from the decrease in the
spontaneous magnetization observed in the experimental data. For Co2 MnSi, for simplicity,
we assume that the decrease in the magnetization originates solely from the spin-flip in
the Mn atoms, and construct the LMD modelas Co2 Mn↑1−x/2 Mn↓x/2 Si, where Mn↑ and Mn↓denote the up and down magnetic moments,
respectively. For instance, the magnetization
ratio between 0 K and 300 K is 0.983. We
thus assume that 0.85% of the spins are re-132

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

verse while the others are unchanged at 300 K(Co2 Mn↑0.9915 Mn↓0.0085 Si random alloys).
Moreover, we calculate the conductivity using the Kubo-Greenwood formula including
vertex correction, in which the vertex functions
are expressed using the ladder-like approximation. The conductivity tensor is defined as follows:σµν1
lim [σ̃µν (ε + iη, ε + iη)
4 η→0+ σ̃µν (ε − iη, ε − iη)=− σ̃µν (ε + iη, ε − iη)− σ̃µν (ε − iη, ε + iη)].

(1)Here, ε is energy and iη is an infinitesimal
imaginary part. Note that σµν depends on ε.
Moreover, σ̃ is calculated byh̄
Trhjµ G(z1 )jν G(z2 )iCPA ,πN Ω(2)
where N is the number of unit cells, Ω is theunit cell volume, and jµ(ν) is the current operator. The bracket indicates the configuration
average for the disordered systems by CPA.
Figure 1 shows the the temperaturedependent electrical resistivity of Co2 MnSi using the Kubo-Greenwood formula. The resistivity of Co2 MnSi derived from a local phononis proportional to the temperature except in
the low-temperature region. The resistivity
originating from the magnon scattering reflects the experimentally observed magnetization curve. We determined that either local
phonon displacement or LMD alone was insufficient to reproduce the experimental data.
This is expected because at low temperatures,
scattering due to lattice vibration and spin
fluctuation is suppressed, and impurity scattering becomes dominant. It is known that
there are considerable native defects in Heusler
alloys, such as vacancies, interstitials, and antisite defects. For Co2 MnSi, previous works suggest the presence of antisite disorders between
Co and Mn. Scattering effects from these antisite defects may be the main source of theσ̃µν (z1 , z2 ) = −Figure 1: Temperature dependent electricalresistivity estimated by the Kubo-Greenwood
formula.
finite resistivity at low temperature. Therefore, we attempted to calculate the resistivities
considering the Mn-Co antisite disorders. Antisite effects can be easily added to the calculation in the framework of CPA. If we assume
that 1.0% of the Mn-Co antisite disorders (i.e.,(Co0.995 ,Mn0.005 )2 (Mn0.990 ,Co0.010 )Si) is introduced, the calculated residual resistivity is 6.47µΩcm. This value is consistent with the experimental results at extremely low temperature. The pink stars in Fig. 1 represent the calculated temperature-dependent resistivity of
Co2 MnSi when the Mn-Co disorders are included in addition to local phonon and magnon
disorders. The result is in reasonable agreement with the experimental results. Therefore,
it can be concluded that to accurately calculate the finite-temperature transport properties of Co2 MnSi, three disorders (local phonon,
magnon, and Mn-Co antisite disorders) should
be considered in the comprehensive procedureon the basis of CPA.

References[1] H. Shinya, S. Kou, T. Fukushima, A.
Masago, K. Sato, H. Katayama-Yoshida,and H. Akai, Appl. Phys. Lett. 117 (2020)
042402.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Hybrid Ab-Initio/Machine-Learning Optimization of Nano Interfaces
and Molecular Structures
Kenji TSURUTA, Md. Abdullah Al ASAD, Kyosuke SATO,
Masaaki MISAWA, and Satoshi OHMURAa
Graduate School of Natural Science and Technology, Okayama University, Okayama 700-8530aDepartment of Civil and Environmental Engineering, Hiroshima Institute of Technology,
Hiroshima 731-5193
Designing and developing functional
materials/molecules often require vast searchingof target properties from extra-large data set,
which is far out of the capability of conventional
computing algorithms. In recent years, theDeep-Learning (DL)-based molecular design
methods have been extensively studied.
Recently, we have reported [1] a machinelearning method for predicting molecularproperties by mapping a graph representation ofa molecule to a latent variable space and bylinking the variable to physical property of themolecule. Representing molecules in the latent
space enables an efficient property search within
existing data, because the DL model transforms
the discrete representation of a molecular graphinto a continuous variable space suitable forvarious numerical algorithms.
In the present study, we further improve theoutput rate of valid SMILES of decoder byintroducing a discriminator attached to the VAE
stream. Adopting a molecular-mechanics
method to calculate 3D structure from SMILES,
we can optimize physical properties of themolecule by other simulation methods such as
density-functional-theory calculations evenwhen there is not enough data set. The range ofphysical property space covered by the SMILES
representation is thereby expanded and the datadriven optimization using Kernel Ridge
Regression method can be performed within the
search space. We have demonstrated theeffectiveness of this method for optimizing amolecular HOMO-LUMO gap as an example.
Another effort is taken to perform efficient
search for insertion/reaction path of anmolecules on the surface of a functional
materials. We computationally investigate aninsertion process of water into themethylammonium lead halide perovskite(MAPbI3). The rapid decomposition of MAPbI3

reaction with water has been recognized to be amajor obstacle to its solar-cell applications. To
overcome this drawback process, it is important
to identify the initial stage of water insertion into
the MAPbI3. The first-principles calculation
based on the density-functional theory is
performed to investigate the water insertion
process on outer surface layer of MAPbI3 slab
model. Using the Nudged Elastic Band method,
we find that the initial insertion process follows
the three steps: approaching, re-orienting andfinally sinking into the perovskite layer. This
process requires approximately 0.60 eV toovercome an energy barrier, which agrees withan in-situ X-ray diffraction (XRD) measurementof the reaction threshold of water molecules with
the MAPbI3 crystal at room temperature [2].
These computations have been done in part byusing the Super-computing System at SCC-ISSP

Fig. 1 Insertion path of water molecules in the MAPbI3
surfaces and barrier energy variation along the path.

References[1] K. Sato and K. Tsuruta, Mater. Sci. Forum
1016, 1492 (2021).
[2] M. Hada, M. A. A. Asad, M. Misawa, Y.
Hasegawa, R. Nagaoka, H. Suzuki, R.
Mishima, H. Ota, T. Nishikawa, Y. Yamashita,
Y. Hayashi, and K. Tsuruta, Appl. Phys. Lett.
117, 253304 (2020).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Investigation on the electronic structure ofphoto-catalytic double-perovskite
Kazume NISHIDATE
Faculty of Science and Engineering, Iwate University
Ueda 4-3-5, Morioka, Iwate 020-8551

In recent experiments, a signiﬁcant band
gap widening was observed when Sb was
substituted for Bi in the double-perovskite
Ba2 PrBiO6 .
In this work, we study aseries of double-perovskites, Ba2 BiIII BiV O6 ,Ba2 PrBiO6 , and Ba2 PrSbO6 using the ﬁrstprinciples density functional theory with the
Heyd-Scuseria-Ernzerhof hybrid functional toinvestigate the substitution eﬀect on the structural and electronic properties [1].
We use the density functional theory (DFT)
as implemented in the Vienna ab-initio Simulation Package (VASP) and the projector augmented wave (PAW) potentials to study the
structural and electronic properties of the double perovskite. We use the Heyd-ScuseriaErnzerhof hybrid functional (HSE06) to account for the strong correlation eﬀects of thesystem. We use an energy cutoﬀ of 500 eV for
plane wave basis set together with a 6×6×6
k-point grid. The rather high energy cutoﬀ
and dense k-point grid are necessary to predict
correctly the crystal structures in the HSE06
computations. Equilibrium crystal structures
were achieved so that the maximum force component was smaller than 1 meV/Å3 , and the
maximum stress component smaller than 1
meV/Å3 .
In a monoclinic system, the shape of theBrillouin zone depends non-trivially on the lattice vectors. In fact, there are ﬁve possible
shapes of Brillouin zones for the monoclinic
crystal structure depending on the choice oflattice vectors. Where we choose the C2/m

which corresponds to the MCLC1 lattice. To
generate the set of k-points along the edges of
the Brillouin zone, we use the code pymatgen. We show the obtained band structure in
the Figure 1.

Figure 1: Band structure and density of states
curve of Ba2 BiIII BiV O6 . Fermi level is at 0 eV.
We ﬁnd that the BiIII 6s states at the top ofvalence band of Ba2 BiIII BiV O6 vanish on the
Pr substitution for Bi at B ′ III -site. When Sb
is substituted for Bi at B ′′ V -site, the BiV 6s
states at the bottom of the conduction band
vanish causing additional widening of the band
gap.

References[1] K. Nishidate, A. Adiko, M. Matsukawa,
H. Taniguchi, A. Sato, A. Matsushita,
S. Tanibayashi and M. Hasegawa, Mater.
Res. Express 7 (2020) 065505.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Studies on electronic structures and optical properties internary oxide crystals
Takayuki Makino
Research Center for Development of Far-Infrared Region,
University of Fukui, Bunkyo Fukui, Fukui 910-8557
Lithium niobate ternary compound is
known

to

exhibitseveralupward convex in the 1.5－4-eV range (notinteresting

shown in a figure). This feature is in good

properties such as superconducting behavior
underdelithiatedunderstandingsforphase.
thisagreement with the experiment [3].

Deepercompoundareimportant from both technological and basic
viewpoints [1]. In this research, we intend tocompare calculation results on the complex
dielectric function and experimental data.
We

used

the

Quantum-ESPRESSO

package to optimize the crystal structure andperform the band structure calculations. In
this work, we used a set of the optimized
norm-conserving

pseudopotentials.

The

corresponding activity diagram is shown at
the right hand side.

We confirmed that

evaluated bandgap energy (BGE in the figure)is similar to that evaluated by Ylvisaker etal[１].

References

We then moved into study on opticalproperties. For the optical spectra calculations[1] Erik R. Ylvisaker and Warren E. Pickett:such as dielectric functions, we used Respack

Phys. Rev. B 74 075104 (2006).

ab-initio[2] K. Nakamura et al., arXiv:2001.02351

package[2].

Neglecting

contributions from the optical anomalies,(2020).

overall ε1(ω) in the calculated spectrum is a[3] T. Kurachi et al., J. Appl. Phys., submitted.

monotonicallydecreasing

function

with

136

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Vacancy cluster stabilization by impurities and theirmigration property in tungsten
Kazuhito Ohsawa
Institute for Applied Mechanics, Kyushu University,
Kasuga-koen, Kasuga, Fukuoka 816-8580

Introduction

Simulation method

Tungsten (W) and its alloys are plausible

The binding energies of impurities to vacancy

candidates for plasma facing materials (PFMs)

and stabilization of di-vacancy by the impurities

used in fusion reactors because of their excellent

were calculated in terms of first-principle

properties, e.g. high melting point, low hydrogencalculations based on density functional theory.

(H) solubility, and toughness for irradiation.

We used the Vienna ab-initio simulation package

However, a large amount of H and H isotopes(VASP). A large simulation cell, composed ofare retained in vacancy (V) and vacancy type6x6x6 bcc lattice (432 atoms), were used inlattice defects in W specimen nucleated underorder to reduce the effects of periodic boundary

the irradiation circumstance. In particular,

condition imposed on the simulation cell. The

tritium (T) retention in the PFMs is a serious

cut-off energy of plane wave was 520eV.

problem for safety operation of fusion reactors.

The binding energy of impurity (X) to

So, the control of the vacancy type lattice defects

vacancy (V) was defined as

is important subject in the field of PFMs.

Eb(VX)=E[V]+E[X]-{E[VX]+Eref},Vacancy clusters and their interaction with

where E is cohesive energy of the supercell

impurities included in W are investigated bycontaining V, X and vacancy-impurity complex

experimental

methods.

XV, and Eref indicates energy of perfect lattice.

According to first-principle calculations, di-Similarly, the binding energy between VX and V,

vacancy (V2) in W are unstable compared withstabilization of di-vacancy by impurity, wasisolated vacancies. However, the di-vacancy anddefined as

andcomputational

growth of vacancy clusters in W materials were

Eb(V2X)=E[VX]+E[V]-{E[V2X]+Eref}.

observed in positron annihilation lifetime

Positivebinding

spectroscopy.

attractive

interaction.

In

the

presentwork,

weenergycorresponds

Besides,tomigration

investigated the stabilization of di-vacancy byenergies (Em) of impurities and vacancy were

impurities contained in the W specimen.

estimated by nudged elastic band (NEB) method.

137

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Results

Discussion

We investigated interaction of vacancy with

Let’s consider the stabilization of di-vacancy

interstitial type impurities, i.e. hydrogen (H),by the interstitial impurities. W specimen for the

carbon (C), nitrogen (N), and oxygen (O). As

positron annihilation lifetime spectroscopy werelisted in Table I, the four impurities can beprepared in water coolant circumstance, so

accommodated in a W vacancy, because theimpurities of low migration energy (H and O)

binding energies Eb(XV) are positive. While, thewere possible to migrate in the specimen andinteraction between two vacancies is repulsive,

trapped in W vacancy to form vacancy-impurity

that is, Eb(V2)= -0.13eV. According to Eb(V2X),

complex VX. On the other hand, vacancy

all impurities stabilize di-vacancy in W.

diffusion was observed at about 623K, which

However, the stabilization effect of H is quite

corresponds to migration energy for W vacancy

small compared with those of other impurities.

(1.69 eV). The binging energies of H and O to

Fig. 1 shows barrier height of the impurities

vacancy were estimated to be 1.22 and 3.04 eV,and vacancy along the migration paths. The

respectively. Therefore, we infer that VO

migration energies for H and O are quite small

complex is stable at the vacancy diffusioncompared with those of C and N. The reason istemperature, while VH complex may bethat H and O are located at tetrahedral interstitialdissociated at the temperature. Therefore, O is

sites, while C and N are located at octahedral

still accommodated in W vacancy at the vacancy

interstitial sites. Therefore, the migration paths

diffusion temperature. O is the most plausible

between neighboring interstitial sites of H and O

candidate for di-vacancy stabilization among theare shorter than those of C and N.

interstitial impurities contained in W specimen.

Table I: Binding energy of impurity tovacancy Eb(VX), stabilization of di-vacancy
by impurities Eb(V2X), and migrationenergy of impurities and vacancy Em.

Fig. 1: Barrier height of each impurity andvacancy along migration path.

138

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Optical gaps of metastable Ga2O3 and GaN
with impurity doping effectKen-ichi SHUDO
Fac. of Eng/Sci, Yokohama Nat’l Univ.
Tokiwadai 79-5, Hodogaya-ku Yokohama 240-8501
Electronic state of Mg-doped GaN was
calculated using VASP package based on local
density approximation. In contrast to the moststable phase of a well-studied wurtzite GaN,
thin films of haekelite phase (4|8-GaN) aresuggested to show stable p-type semiconductor
even with the dope.
At the same time, we calculated spindependent

electronic

structure

of

two-

dimensional spin network of organic molecule
array,
(MOF)

made

of

metal-organic−framework

fromCl[5,10,15,20-tetra(4-carboxyphenyl)-porphyrin] TCPP with Mn(II)and Fe(III) at the center hole. Spin-resolved

Fig 1．Calculated electronic states

density of states for several spin-polymorph areof an isolated molecule (top), andobtained, as in Fig.1, and photo-absorption

MOF structures of Fe-TCPP forspectra were calculated. These results suggests

ferro-magnetic

that several spin states would coexist because

antiferromagnetic structures, andthe eigenenergies were mutually very close, andthethat ferrimeagnetic phase could be discernible

ferrimagnetic states.

latterandconvergesatwhen the system is cooled. The optical results
are consistent with our experimental findings

photo-transition in the intramolecular spinby means of magnetic circular dichroism

states, and some signals do from Cu-ions that

(MCD) of optical transmission spectroscopy.

link the molecules in MOF formation.

The observed MCD signals originate from the139

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Optical gaps of metastable Ga2O3 structuresmodulated by impurity dope
Ken-ichi SHUDO
Fac. of Eng/Sci, Yokohama Nat’l Univ.
Tokiwadai 79-5, Hodogaya-ku Yokohama 240-8501
Ga2O3 has good electrical conductivity, andits wide bandgap of 4.8 eV offers great
potential for various applications. The most ofresearches of this oxide material are limited
within the most stable βphase. We previously
reported optical spectra [1] of κ- and εGa2O3 , which is widened by Co-doping. Thechange in the electronic states due to this Co
impurity was calculated (Fig.1) to clarify theexperimental photo-absorption.
The photo-absorption in Ga2O3:Co isFig.1: The density of state of Ga2O3:Co.

difficult to be simply associated to theBlue thin curve is the density projected tobandgap of oxide material. But the adjustable

Co impurity.

shift of the cutoff in the photo-absorption is
accounted by the theoretical calculation in thisstudy.

The change of the experimental

workfunction due to the Co doping was also
explained with a band diagram ofε-phase in
Fig. 2. In this phase n-type pinning occurs due
to unintentional impurities such as Si and Ge,
as is intrinsic especially ε-phase, and Ovacancy less contributes.

Fig.2:

Calculated

photoabsorption[1] K. Mukai, A. Tsuno, K. Shudo, and H.

modulated by the Co-impurity dope.

Otani, Jpn. J. Appl. Phys. 58, SBBK05 (2019).

This accounts for the experimental
optical spectra.

140

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Eﬀects of electron–phonon and electron–magnon
scattering on ﬁnite temperature magnetic properties
H. Akai
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

The eﬀects of phonons are taken into account through random displacements of atoms
around their equilibrium positions. The average displacements are estimated from either
the Debye model or ﬁrst-principles phonon calculations: no notable diﬀerences between thetwo was found. The eﬀects of magnongs,
on the other hand, are calculated by randomly ﬂipping the local magnetic momentswith probability determined self-consistently
at each temperature. All the calculations were
performed in the framework of ﬁrst-principles
calculation using KKR-CPA [1].

becomes remarkable in the case of Nd2 Fe14 B
permanent magnet materials. Some examples
of calculated TC are given in Table 1. The ﬁrst
column indicates the temperature in which theaverage displacement due to phonons is calculated. The experimental value of TC is 585K.
Figure 1 shows the calculated magnetizations of Nd2 Fe14 B. Both the eﬀects of phonsand magnons are included. The theoreticalcurve shows a weak ﬁrst-order transition at themagnetic transition temperature, which occurs
as a result of electron–phonon coupling. The
temperature is scaled so that TC reproduces
the experimental value of 585K although thescaling factor is close to 1. The calculated results are fairly consistent with experiments is
concluded.
40
Nd2Fe14B M(T)M (T) (µB/f.u.)

There are several kinds of excitations thathave to be taken into account when discussing
ﬁnite temperature magnetic properties of magnetic materials. Among them are phononsand magnons. Usually, single electron excitations at Fermi surfaces do not contributesigniﬁcantly to the magnetic properties at
the assumed temperature range of 0 ∼1500K.
We have studied the eﬀects of phonons andmagnons on ﬁnite temperature magnetism,targeting at permanent magnet materials.

30

20
thoeryexperiment
Kuz'min

10

00

In the case of bcc Fe, there is a signiﬁcant effect of electron–phonon scattering on the Curie
temperature TC , while that of magnons is notprominent. The eﬀect of magnons, however,Table 1: Calculated TC
phonons only plus magnons
0K
500K

1062K
1198K

100

200

300

400

500

600

Temperature (K)Figure 1: Calculated and experimental magnetizations vs. temperature of Nd2 Fe14 B

References

561K
548K

[1] H. Akai, AkaiKKR, http://kkr.issp.
u-tokyo.ac.jp/ (2002).

141

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Magnetic properties of(Sm1−xZrx)(Fe0.75Co0.25)11+y Ti1−y rare-earth magnetic
materials
H. Akai
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

Figure 1 shows the calculated magnetizations as functions of temperature where theCurie temperatures are scaled so as to fit theexperimental ones. More precisely, first theCurie temperatures, which are not necessarily known experimentally, are estimated by fitting the temperature dependence of magnetic
moment by Kuz’min’s empirical formula. On
the other hand, the theoretical Curie temperatures are obtained by first-principles calculation using KKR–CPA[1]. Theoretical temperature dependence of magnetization is then obtained again using Kuz’min’s formula. Finally,
the temperatures are scaled using experimentally estimated Curie temperatures.
The crystalline magnetic anisotropy constant K1 of (Sm1−x Zrx )(Fe1−y Coy )11.5 Ti0.5 isalso calculated. Since the treatment for 4f
states of Sm is still rather controversial, we

142neglect the contribution of 4f to magnetic
anisotropy through hybridization, adopting an
open core treatment. These results indicatethat adding Co improves the magnetization although it degrades the magnetic anisotropy. Zrslightly contributes to improve the magnetization but not much to the anisotropy. Main
contribution of Zr must be that to structural
stabilization.
2.0(R1-xZrx)(Fe0.75Co0.25)11+yTi1-y

1.5

JS (T)

Rare-earth permanent magnet materials of
SmFe12 family attract much attention because
expected performance using NdFe12 family asa main phase of permanent magnets has beenrecognized as hardly reached. Much work has
been done to seek better intrinsic magnetic
properties for SmFe12 by adding some elements
as ingredients. In this study, we have tried several SmFe12 family cases, which are implied
from experiments to be possible candidates
for permanent magnet materials. Finite temperature properties, including the magnetizations, Curie temperatures, and magnetocrystalline anisotropy, were examined.

1.0
SmFe11Ti
Sm(Fe0.75Co0.25)11Ti
Sm(Fe0.75Co0.25)11.5Ti0.5(Sm0.8Zr0.2)(Fe0.75Co0.25)11.5Ti0.5
Nd2Fe14B
SmFe11Ti
Sm(Fe0.75Co0.25)11Ti
Sm(Fe0.75Co0.25)11.5Ti0.5(Sm0.8Zr0.2)(Fe0.75Co0.25)11.5Ti0.5
Nd2Fe14B

0.5

0.0
0

200

400
600
Temperature (K)

800

1000

Figure 1: Temperature dependence of magnetization of various systems of SmFe12 family.

References[1] H. Akai, AkaiKKR, http://kkr.issp.
u-tokyo.ac.jp/ (2002).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical Analysis of Photocatalytic Reaction Mechanism atTitanium Dioxide Interfaces
Tatsuya JOUTSUKA
Institute of Quantum Beam Science,
Graduate School of Science and Engineering, Ibaraki University, Hitachi, 316-8511 Ibaraki,Japan
We have studied the reaction mechanism ofphotocatalytic

TiO2bare surface but at the hydroxylated surface,surfaces [1] using cp2k program package

especially at the hydroxyl group of the(MPI parallelization with multiple threads). We

hydroxylated (112) and (001) surfaces. The

focused on the energetics and structure duringexperimental

the hole migration. This is a collaborative work

consistently elucidate the high photocatalytic

withactivity at the anatase TiO2(112) surface.

theYamauchioxidationatexperimentalistat

Ibarakianatasephotogenerated hole is stably trapped not at the(Prof.

Satoshi

University),

who

and

theoreticalfindings

conducted the LPCVD experiment.
This experimental and theoretical study
clarifies

the

facet

dependence

of

the

photocatalytic reaction at the anatase TiO2
surface. The <112>-oriented anatase TiO2 layer
is deposited on the Ru(0001) substrate at 360°C
by low-pressure chemical vapor deposition.
The deposition rate is three times higher thanthat of the multi-orientation layer on the Pylex

Fig. 1: Molecular mechanism of hole migration.

glass. The photocatalytic activity induced byultraviolet (UV) irradiation around 365 nm in

References

methylene

is[1] T. Joutsuka, H. Yoshinari, and S. Yamauchi:

significantly high. The density functional

Bull. Chem. Soc. Jpn., 94 (2021) 106–111.

theory (DFT) calculations using the constrained(Selected Paper, Inside Cover, Open Access).

DFT method [2] and the hybrid functionals[2] T. Joutsuka and K. Ando: J. Phys. Chem. B,

show that the (112) surface stabilizes the

124 (2020) 8323–8330.

blue

aqueoussolutionsadsorbed water molecule most strongly. The

143

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ab Initio Calculation of High-Rate Deposition of Metal Films
by LowPressure Chemical Vapor Deposition
Tatsuya JOUTSUKA
Institute of Quantum Beam Science,
Graduate School of Science and Engineering, Ibaraki University, Hitachi, 316-8511 Ibaraki,Japan
We have studied low-pressure chemical

our calculations to analyze the dynamical

vapor deposition of Cu on Ru substrate using

properties by the constrained DFT[3] and the

CuI [1] using cp2k program package (MPI

dynamical reaction path analysis.[4]parallelization with multiple threads). This year,
we focused on the ab initio calculation ofdesorptionofby-products.

This

is

a

collaborative work with the experimentalist [2](Prof. Satoshi Yamauchi at Ibaraki University),
who conducted the LPCVD experiment.
In this study, we elucidated the molecularmechanism of Cu deposition using copper(I)iodide (CuI) on Ru substrate by low-pressurechemical vapor deposition through electronic

Fig. 1: Molecular mechanism of LPCVD of Cu.

structure calculations. Figure 1 shows themolecular mechanism of Cu deposition by the

References

LPCVD method. Using density functional[1] T. Joutsuka, S. Yamauchi: Chem. Phys. Lett.

theory (DFT) molecular dynamics (MD)741 (2020) 137108.

simulations, we show that CuI molecules[2] T. Nishikawa, K. Horiuchi, T. Joutsuka andadsorb and decompose exothermically due to a

S. Yamauchi: J. Cryst. Growth, 549 (2020)strong adsorption of iodine atoms onto the125849.

Ru(001) surface. The rate-limiting step of the[3] T. Joutsuka and K. Ando: J. Phys. Chem. B,

Cu deposition is found to be the desorption of

124 (2020) 8323–8330.

iodine atoms or molecules from the Cu(111)[4] T. Joutsuka and K. Ando: J. Phys. Chem. A,

surface by molecular dynamics simulations.

115 (2011) 678–684.

Based on this study, we are now extending144

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Dynamical stability of two-dimensional simple metals
and ordered alloys
Shota ONO
Department of Electrical, Electronic and Computer Engineering, Gifu University
Gifu 501-1193

The family of two-dimensional (2D) materials has been expanded signiﬁcantly in recent years. However, the dynamical stability
as well as the synthesizability of 2D metals
have not been explored in detail irrespective of
the presence of the interrelationship between
the energetic stability in the 2D and threedimensional (3D) structures. In this study, we
have performed high-throughput density functional theory (DFT) and density functional
perturbation theory (DFPT) calculations toconstruct the metastability database for simple metals and ordered alloys. The databasecurrently includes (I) the phonon dispersionsof 46 simple metals from Li to Pb in the three
2D structures, including the planar hexagonal,
the buckled honeycomb (BHC), and the buckled square (BSQ) lattices [1]; (II) the phonon
dispersions of 2D Po, named poloniumene, inthe planar square structure [2]; and (III) theformation energies of 1081 binary compounds
in the 2D structures (BHC and BSQ as shownin Fig. 1) and the 3D structures (B2, L10 , andBh corresponding to bcc, fcc, and hcp in simple metals, respectively) and the phonon dispersions of more than 50 ordered alloys in the
BHC structure [3].
In Ref. [1], we have demonstrated that thetrend in the dynamical stability of 2D metals
is correlated with that of 3D metals. This provides design principles of ordered alloys: 2D
metals are building blocks for constructing 3D
alloys, where the similarity regarding the dynamical stability of diﬀerent 2D metals is important for creating dynamically stable alloys.
In Ref. [2], we have shown that the 2D polonium has the planar square lattice structure
as its ground state and demonstrated that the

!" #

!$#

!"

!"

Figure 1: Schematic illustration of binary ordered alloys in the BHC and BSQ structures.
After Ref. [3].
spin-orbit coupling (beyond the scalar relativistic approximation) suppresses the Peierls
instability and is necessary to obtain no imaginary phonon frequencies over the Brillouinzone.
In Ref. [3], by analyzing of the formationenergy and the dynamical stability of binary
alloys, we have demonstrated that (i) a negative formation energy is neither a suﬃcient nor
necessary condition for producing the dynamical stability of 2D ordered alloys; and (ii) if anordered alloy in the Bh structure is synthesizable, that in the BHC structure is dynamicallystable. In addition, the stability of ordered AuCu alloys has been studied in Ref. [4].

References[1] S. Ono: Phys. Rev. B 102 (2020) 165424.
[2] S. Ono: Sci. Rep. 10 (2020) 11810.
[3] S. Ono and H. Satomi: Phys. Rev. B 103(2021) L121403.
[4] S. Ono and D. Kobayashi: Phys. Rev. B
103 (2021) 094114.

145

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Boltzmann equation solver for nonequilibrium
electrons and phonons in solids (BENEP). II.
Application to experiments
Shota ONO
Department of Electrical, Electronic and Computer Engineering, Gifu University
Gifu 501-1193

Understanding the ultrafast electron dynamics of laser-excited solids, where theelectron-electron (e-e) and electron-phonon (eph) scatterings occur simultaneously within apicosecond time scale, is important to analyze the pump-probe experimental data. The
author has developed the Boltzmann equation solver for nonequilibrium electrons andphonons which enables us to study the ultrafast electron and phonon dynamics [1]. We
have applied our code to the calculation of the
femtosecond infrared photoluminescence (PL)of silver (see Fig. 1). The preliminary results
have been reported in Activity Report 2019.

Figure 2 shows an application to the timeevolution of PL spectra and the transient PL
at 0.9 eV in silver. The agreement between
the theory and experiments is good, indicatingthat the eﬀect of electron nonequilibrium is important in the PL dynamics. The disagreement
may be attributed to the nanoscale roughness
at metal surfaces and the e-e umklapp scattering on the ultrafast electron dynamics [2].
The author thank Prof. Tohru Suemoto for
useful discussions.
3

1.2

30x10

0.0 ps0.2 ps
0.5 ps1.0 ps

(a)
25

1.0

! "#$%&' #"( )"' *+$,)- *). *- %"/ ( $,0+1213,4 ! 56
7 *+)%#/ ( ,4 8 9 ,!"#$: ; / ( / ( ,4 8 9 ,%"&$
7 *"- $; <+#2 =. ( )%"/ ( ,'! ("&$

,*"&$
,*
.
,,- #$%"
5"> +&+?/ *. %"/ ( ,/ =,) # - ( @,*"&$3,+" - ( @,+#$3,- ( @,%
; +,
/' %
")- *,$' +)%#- ,0+1213,: A6

0.6

10

0.4

5

0.2

0.6

0.8

1.0

Photon energy (eV)

,)"#$
,)
,)
,)
.
/
H,
,,- "%",- "%#$,- &'("): - #- > +%+#$,0* - ( @,1*0"( ,%; +,' #+$+( %
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. @C6

15

0
0.4

D( %
+2#- %"/ ( ,/ =,%; +,E/ *%F> - ( ( ,+G. - %"/ ( ,

0.8
PL (0.9 eV)

Photons/sec

20

B#C$%
- *,$%#. )%. #+

Calc.
Exp.

(b)

0.0
-0.5 0.0

0.5

1.0

1.5

Decay time (ps)Figure 2: (a) The evolution of PL in silver:
The experimental PL (circle) and the calculated PL (solid). (b) Comparison of the transient PL at 0.9 eV. After Ref. [2].

References
Figure 1: Flow chart describing the timeevolution calculation of the distribution functions in metals. After Ref. [2].

[1] S. Ono: Phys. Rev. B 97 (2018) 054310.
[2] S. Ono and T. Suemoto: Phys. Rev. B 102(2020) 024308.

146

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Noisy simulations of first-principles calculations using
quantum classical hybrid algorithms
Wataru Mizukami
Center for Quantum Information and Quantum Biology, Institute for Open andTransdisciplinary Research Initiatives, Osaka University, Osaka 560-8531, Japan,

affected by noises.

In recent years, quantum computers withdozens of qubits have been built; we now expect

In this work, we have investigated theto see quantum devices with hundreds of qubits

influence of this noise on the VQE by using a

in the near future. Such quantum computers arequantum circuit simulator. There are many types

often called noisy-intermediate scale quantumof noises in quantum computers, such as read-devices (NISQs) since they do not have quantumout error and amplitude damping. Since it iserror correction functionality. Nonetheless, indifficult to model all kinds of errors, we have

2019, Google showed that a NISQ with as few

only dealt with depolarizing noise, which is aasoutperform

typical error model for quantum computers, insupercomputers when limited to a specific task.

this study. This noise can be described as Pauli

Many research projects have been currently

operators probabilistically acting on each gate ofunderway to exploit the computational potential

aof NISQs.

depolarizing noise, we can effectively say that53

qubitscould

alreadyquantum

circuit.

In

thepresenceof

One promising algorithm for NISQs is thethe noise probabilistically changes the quantum

quantum-classical hybrid algorithm, which cancircuit at each sampling. It means that theoperate even in the short coherence time of anumerical simulations with depolarizing noise

NISQ. Among them, the variational quantum

using classical computers, are required toeigensolver (VQE) can be applied to first-

simulateprinciples calculations of materials or molecules.

simulation with depolarizing noise is much moreAn advantage of the VQE is that it can

expensive than the simulation without it.

parametrize some wave functions ansatzes such

Besides, because such a simulation is a sampling

as unitary coupled clusters (UCC)in polynomial

problem, the individual circuits changed by thetime,

exponentiallynoise are independent. Hence, the VQE withonclassical

depolarizing noise can be highly parallelizable.

computers. However, if a NISQ is used for theThis year, we have realized the simulation

VQE, the computational results are unavoidablywith depolarizing noise up to 1 million samples

while

the

computationallyUCC
expensiveis147

variousquantum

circuits:theActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

by using the MPI parallelization and thechemical accuracy with the error rates of today's

supercomputer of the ISSP. In addition, by using

quantum computers. This implies that ana many-body expansion, we have studied theefficient way to suppress the effect ofeffect of depolarizing errors on up-to a 100-depolarizing noise is vital for the practicalqubits problem. We have chosen the most basic

application of first-principles calculations using

molecule, the hydrogen molecule, as the

NISQs.

benchmark system. In our program, the PySCF
quantum chemistry program library [1] is used

References

to prepare the second quantized electronic[1] Q. Sun et al., WIREs Comput. Mol. Sci. 8,

Hamiltonian; Qulacs is employed as a quantum

e1340 (2017).

circuit simulator [2]. The obtained numerical[2] Y. Suzuki et al., arXiv:2011.13524

results illustrate that it is impractical to achieve148

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First principles calculations of crystals with quantum classicalhybrid algorithms
Wataru Mizukami
Center for Quantum Information and Quantum Biology, Institute for Open andTransdisciplinary Research Initiatives, Osaka University, Osaka 560-8531, Japan,

quantum circuit parameters.

First-principles calculations of solids or solid
surfaces are routinely performed in materials

This year, we have extended the VQE toscience. They have become an indispensable

solid-state systems [1]. Specifically, we prepare

tool in the fields of condensed matter physics

a second quantized Hamiltonian in the crystal

and inorganic chemistry. The workhorse of theseorbital representation, and make a one-to-one

ab initio calculations is currently density

correspondence between crystal orbitals andfunctional theory (DFT). An approach beyond

qubits. The UCC ansatz in the crystal orbital

DFT is the introduction of quantum chemical

representations has also been converted into themethods such as the coupled-cluster theory (CC).

qubit representation. These mapping allows us

The problem of CC is that it works well only

to describe the electronic structure of acrystalline system on a quantum computer.

for weakly correlated systems. It is known to
break down in systems with strong electron

We have applied the developed VQE-UCC tocorrelation. This issue comes from the fact that

one-dimensional hydrogen chains and calculate

CC is not variational. Although there is atheir potential energy surface, confirming thatvariational CC method, such a method is

the VQE-UCC works in the regime where theexponentiallyofelectron correlation becomes strong so that thecomputational costs. However, in 2014, it wasconventional CC does not work. We have also

shown that a kind of variational CC, the unitarydeveloped an algorithm to calculate the quasi-

CC (UCC), can be solved in polynomial time

particle band structure from the VQE wave

using a quantum computer.

function based on the extended Koopman's

expensive

in

terms

theorem [1].

This method is called the variational
quantum eigensolver (VQE). In the VQE, thewavefunction ansatz is represented by aReferences

quantum circuit. Then, a classical computer[1] N. Yoshioka, Y.O. Nakagawa, Y.-y. Ohnishi,

updates the VQE's wavefunction parameters as

W. Mizukami, arXiv:2008.09492

149

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles Calculation of Electric Field Eﬀects
in Spin-to-charge Conversion Materials
Naoya YAMAGUCHI
Nanomaterials Research Institute, Kanazawa University
Kakuma-machi, Kanazawa, Ishikawa 920-1192
We have studied materials possessing the
Rashba eﬀect that induces spin splitting,which is applicable to spin-to-charge conversion [1]. The Rashba eﬀect originates fromspin-orbit interaction and spatial inversion
symmetry breaking, and is controlled by electric ﬁelds. Based on the modern theory ofelectric polarization, one can apply uniform
electric ﬁelds even for bulk insulators in calculations with density functional theory (DFT)
codes with the periodic boundary condition[2]. We have developed a linear-combinationof-pseudo-atomic-orbital (LCPAO) version ofsuch a function making k-dependent potentials
and implemented it to the OpenMX code. This
year, we tried to focus on electric ﬁeld eﬀects insuch Rashba systems with Berry phases by using the OpenMX code. Under an electric ﬁeld,
cations or anions are expected to shift theirpositions slightly, but shifts of ions’ positions
induce such a large electric polarization thatRashba spin splitting occurs. During structural relaxation, such ions move by following
forces on themselves, but the forces are often smaller than a usual criterion of calculated
forces (e.g. 10−4 Ha/Bohr) when we consider
the realistic strength of electric ﬁelds. However, for nonorthogonal cells such as hexagonal cells, in the case of generalized gradient approximation (GGA), the “egg box effect” appeared as a diﬃculty because OpenMX
uses PAOs expanded in the real space grid tocompute physical quantities, but descriptionof PAOs depends on the origin of the grid,that is, introducing the grid causes numericalerrors. To overcome the diﬃculty, we addedfunctions of calculations of a total energy andforces with several grid origins. Once calculations of electronic systems converge, one canget density matrices (DMs) and taking anotherreal space grid with a diﬀerent origin, one canevaluate an energy and forces again with thefrozen DMs. In the way, we succeeded in evaluating forces under electric ﬁelds with a moderate number of grids (i.e. cutoﬀ energy). We
also added a function to change the order ofthe Lagrange interpolation to estimate density
gradients, and it improved evaluation of forces.
These two functions enabled us to predict not
only relaxed structures under electric ﬁelds but
also static dielectric constants and Born eﬀective charges in any cell shape. Indeed, we conﬁrmed that our calculated values of dielectric
constants and Born eﬀective charges for typicalinsulators are consistent with the prior theoretical and experimental studies. Since we encountered the problems of the ”egg box eﬀect”,
we have not done calculations of applications,but we have suggested a simple model of surface alloys, such as Bi/Ag surface alloys inducing giant spin splitting, based on DFT calculations [3]. This year, we also succeeded in
reducing half of computational time for Berryphases averagely through tuning, and running
our implemented code with up to 323 k-points
for zinc blende primitive cells through eﬃcienttransfer of arrays of k-dependent potentials in
the message passing interface (MPI).

References[1] J. C. Rojas Sánchez et al., Nat. Commun. 4, 2944
(2013).
[2] I. Souza, J. Íñiguez, and D. Vanderbilt, Phys. Rev.
Lett. 89, 117602 (2002).
[3] M. Nur, N. Yamaguchi, and F. Ishii, Materials 13,4444 (2020).

150

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles study of atomic and electronic
structures of intermetallic compound catalysts
Kazuki NOZAWA
Department of Physics and Astronomy, Kagoshima University
1-21-35, Korimoto, Kagoshima 890-0065

This ﬁscal year, we carried out the following
studies using the VASP code with the PAW
method and the PBE exchange-correlation
functional.
Quasicrystals (QCs) are long-range orderedmaterials with no translational symmetry.
Partly because the atomic structure of mostQCs have not been solved completely, DFT
studies have usually been carried out using thesurface of a crystalline phase having a closecomposition and common structural building
unit to the quasicrystalline phase. Recently,
however, single-element quasiperiodic ultrathin ﬁlms have been obtained using the AgIn-Yb QC as a template. The Ag-In-Yb
QC belongs to the only QC family whose
atomic structure has been solved unambiguously. Thus, DFT studies using the actual
quasiperiodic surface atomic arrangement are
required to elucidate the atomic structure of
the ultra-thin ﬁlms. Although a straightforward way to approximate the QC surface is touse an atomic cluster extracted from the structural data of the QC, the cluster size dependence of the adsorption energy for the aperiodic surfaces has not been well studied. Therefore, this time we studied the convergence behavior of the adsorption energy of a single Bi
atom concerning the cluster size [1]. Two typesof clusters, the cylindrical and hemisphericalclusters, are tested. Unnaturally rippled potential energy surfaces were obtained for clusters with smaller radius regardless of the cluster thickness. It was revealed that the ripples
are disappeared when clusters with a suﬃcient

cluster radius of 1.4 nm or larger are used.
This trend is also conﬁrmed in their root meansquare errors. Consequently, it was concluded
that both cluster models tested with a speciﬁc
size are expected to give relative adsorptionenergy within an error of 0.15 eV. It was also
pointed out that the cylindrical cluster modelis relatively economical in terms of the calculation cost than the hemispherical cluster model.
We also investigated the surface atomic
structure of the antiferromagnetic 1/1 Au-Al
Tb approximant crystal using DFT calculation[2]. Experimentally observed stable surface atomic structure showing a linear row
structure of Au/Al atoms, which is an example of a surface reconstruction in this family of
QC-related systems, was found stable by thecalculation.
We studied the inﬂuence of the adsorbed
oxygen atoms on the surface atomic structureand electronic structure of PdZn(111) surface
using DFT calculation[3].

References[1] M. Sato, T. Hiroto, Y. Matsushita, and
K. Nozawa, Mat. Trans. 62 (2021) 350.
[2] S. Coates, K. Nozawa, M. Fukami, K. Inagaki, M. Shimoda, R. McGrath, H. R.
Sharma, and R. Tamura, Phys. Rev. B
102 (2020) 235419.
[3] Y. Otani, Master Thesis (Kagoshima University, 2021).

151

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study on Removal Mechanism of Single Crystalline Si
Planarized by Catalyst-Referred Etching in Pure Water
Pho Van BUI, Kiyoto KAYAO, Kouji INAGAKI, Yoshitada MORIKAWA
Graduate School of Engineering,Osaka University, 2-1 Yamada-oka, Suita, Osaka 565-0871
There is a growing demand on ultra-smooth surface with sub-Angstrom root-mean-

precision optical components for scientific andsquare roughness is achieved on the Si

industrial applications, especially in extreme

substrate.

ultraviolet (EUV) and X-ray regimes. Using the

Our recent studies indicated that the

short-wavelength light, scientific imaging ofremoval mechanism of SiC and SiO2 etching

cutting-edge materials/biological samples andvia CARE is hydrolysis reaction, in which thenanoscale lithography have become possible

catalyst

thanksopticalstabilization of hypervalent state, increasing

components. Low thermal expansion materials

rate of the reaction [3]. Thus, the purpose of thesuch as glass and Si are still the main materials

proposed research is to clarify the removal

used for fabricating these optical components.

mechanism of Si etching via CARE using first-

Compared to glass, Si possesses more attractive

principles calculation. Additionally, in Si

properties,

cleanliness,polishing, the effect of self-oxidation bymachinability, and workability. Accordingly,

oxygen and water is still not well understoodultra-precisionSi

due to the instability of Si under ambient

surfaces has been achieved significant advancescondition. Thus, the oxidation effects of oxygenin accuracy and smoothness. A highly ordered

and water are also taken into account.

to

the

such

ultra-precisionassurfacehighermachiningforassistswater

dissociation

andsurface with a root mean square roughness at

The mechanistic removal pathway of CARE

the level of several tens of picometer is greatly

for Si(111) has been clarified and shown in Fig.

desired for the highest reflectivity and the

1. In the pathway with the Pt catalyst, at first, alowest unwanted scattering [1].

water molecule is dissociatively adsorbed on Pt.

In this study, we apply catalyst-referred

In the next step, the adsorbed OH is transferredetching (CARE), an abrasive-free polishing

to the targeted Si, forming the five-foldmethod, to planarization of a crystalline Si

coordinated state in the metastable state (MS).

surface, using Pt as the catalyst and pure water

At this state, the Si-Si back-bond is elongatedas the etching solution [2]. An atomicallyand weekend. Finally, the Si─Si back-bond is152

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

broken by a proton transfer at the final stateoxidation by oxygen at a terrace site might be(FS). The activation barrier is reduced from 1.0

difficult. The obtained results are quiteeV (without the Pt) to 0.6 eV (with the Pt). We

consistent with the previous study [4]. The

expected that similar results would be observed

obtained results could also explained why theon a Si(100).

wettability of Si(111) surface could be lasted
for several hour in the ambient conditions in theprevious experimental study [5].

Fig. 1: A mechanistic reaction pathway of
the Pt-catalyzed water etching of the Si(111)
surface in comparison with the pathway

Fig. 3: Atomic configurations and energy

without the Pt catalyst.

diagrams of oxidation by an oxygen molecule
at a step-edge and a terrace site.

We consider oxidation effects by an oxygen
molecule at terrace and step-edge sites on a

The study has clarified the mechanistic

Si(111) surface, as illustrated in Fig. 2.

removal pathway of CARE for Si in pure waterand oxidation effect of a Si(111) surface byoxygen or water. Oxygen plays an main role in
the oxidation of a Si(111) surface. Moreover,combined oxidation effects of oxygen andwater might be an important factor to beconsidered in the future.

Fig. 2: Illustration of oxidation effects by an

References

oxygen at terrace and step-edge sites on a[1] R. J. Noll: Opt. Eng. 19 (1980) 249.

Si(111) surface (top-view).

[2] H. Hara et al.: J. Electron Mater. 35 (2006) L11.

The activation barriers of the oxidation by[3] P.V. Bui at al.: Jpn. J. Appl. Phys. 57 (2018)

an oxygen molecule are 0.46 and 0.15 eV,055703.

respectively (Fig. 3). The obtained results[4] F. A. Soria, E. M. Patrito, and P. Paredes-Olivera:

indicated that the oxidation might occur readily

J. Phys. Chem. C 116 (2012) 24607.

in the air at a step-edge site. However, the[5] M. Niwano at al.: J. Appl. Phys. 76 (1994) 2157.

153

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Doping and molecular adsorption of graphene
Yoshitaka FUJIMOTO
Depertment of Physics, Tokyo Institute of Technology
Ohokayama, Meguro, Tokyo 152-8551

Graphene is one of candidate device materials for molecular sensors using field-eﬀect transistors due to their high charge mobility andchemical reactivity to adsorbates. Recently, we
have reported the adsorption properties of environmentally polluting and/or toxic molecules(NO and NO2 moleucles) onto boron andnitrogen-doped graphenes, and only NO andNO2 molecules in air are strongly adsorbed on
the B-doped graphenes.
We here report the adsorption property
of a toxic CO molecule on the boron-doped
graphene and (8,0) CNT to reveal the curvature eﬀects of the graphene using a firstprinciples density-functional calculation [1, 2,
3].
Table 1 shows the adsorption energies andthe binding distances between the B atom andthe adsorbed molecule for the CO molecule on
the B-doped monolayer and bilayer graphenes,
and B-doped (8,0) CNT. The CO molecule isfound to be adsorbed not strongly but weakly
with short distance and small adsorption energy on the B-doped monolayer graphene. In
the case of the B-doped bilayer graphene, theadsorption energy and the binding distance forthe adsorption of the CO molecule show similar

Table 1: Adsorption energy Ea (eV) and binding distance d (Å) between adsorbed moleculeand B atom for CO molecules adsorbed on Bdoped monolayer and bilayer graphenes, andB-doped (8,0) CNT.

Monolayer
Bilayer
CNT

Ea
-0.12
-0.12
-0.62

d
2.89
2.89
1.53

154

to those of the B-doped monolayer graphene,
respectively.
We also study the adsorption energy and thebinding distance of the CO molecule on the
B-doped (8,0) carbon nanotube (CNT). Unlike monolayer and bilayer graphenes, the COmolecule is found to strongly bind on the Bdoped (8,0) CNT with the large adsorptionenergy and the short binding distance. Thus,
the adsorption properties of the CO moleculeon the B-doped (8,0) CNT is found to be enhanced, compared with those on the B-dopedmonolayer and the B-doped bilayer graphenes
due to the curvature eﬀects.
In summary, we have studied the adsorption properties of the toxic CO molecule on
the B-doped monolayer and bilayer graphenes,
and B-doped (8,0) CNT, using first-principles
density-functional calculations. The B-dopedmonolayer as well as bilayer graphenes does
not strongly but weakly bind with the COmolecule, while the B-doped (8,0) CNT canstrongly bind with the CO molecule. The Bdoped (8,0) CNT may be useful for sensor applications to detect CO molecules.

References[1] Y. Fujimoto and S. Saito, Chem. Phys.
478, 55 (2016).
[2] Y. Fujimoto and S. Saito, Jpn. J. Appl.
Phys. 58, 015005 (2019).
[3] Y. Fujimoto and S. Saito, Appl. Surf. Sci.
Adv. 1, 100028 (2020).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Stability and electronic structures of MoS2 nanowires
Toshihiro SHIMADADivision of Applied Chemistry, Faculty of Engineering,
Hokkaido University, Kita-ku, Sapporo, Hokkaido 060-8628
Nanotubes of layered materials started withthe discovery of variety of helicities in carbon
nanotubes.

Since then, various layeredmaterials are found to form nanotube structures.
These structures show important functions suchas catalytic activities, lithium ion storage,transistor

actionandchemicalsensing.

Recently, we discovered that FeO nanoparticles

Fig. 1: Strain energy of MoS2 nanotubes withwork as catalyst to make MoS2 nanowires[1].

square or cylindrical cross sections.

We found that the cross section of the MoS2
nanowires show rectangular shapes. In order toinvestigate the mechanism of the formation andpossible new functions of these nanotubes, weused VASP to calculate the stability of

MoS2

nanotubes with cylindrical and square shaped
cross sections with armchair and zigzag
helicities[2]. The calculation result shows that

Fig. 2: 2D deformation charge density map of

this structure has lower strain energy in the low-square-shaped nanotube.

diameter region (~30 Å) than the conventional

References

cylindrical nanotubes (Fig.1). The electronic[1] M. Weng, T. Yanase, F. Uehara, S. Watanabe,

structure and the surface energy per length of theT.

square nanotubes showed unique properties

CrystEngComm 19, 3915 (2017).

because of ﬁve coordinated Mo atoms at the[2] M. Zhang, M. Weng, T. Tamura, M. Goto, I.

corner. Catalytic activities and unique sensing

Yamane, T. Yanase, T. Nagahama, T. Shimada:functions are expected.

Physica E 130, 114693 (2021).

155

Miura,

T.

Nagahama,

T.

Shimada,Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles derivation of a many-body effective model based on PMT
basis
Hirofumi SAKAKIBARA
Advanced Mechanical and Electronic System Research Center (AMES),
Tottori University, Tottori, Tottori 680-8525
To establish a construction method to[2]. The PMT basis function is a hybrid

obtain a model which captures the low-basis between the plain wave basis andenergythe muffin-tin basis. In the new model

part

of

electronic

structures

obtained in first-principles calculation isconstruction

an urgent problem. The model is often

described in the plane waves basis set

used to calculate physical quantities suchare taken into account in the model

as

and

Hamiltonian expressed on the muffin-tintransition temperatures of magnetism ororbital basis. Namely, we obtain asuperconductivity.

Maximally

projection operator from full-space (PMT

localized Wannier function (MLWF [1]) is

space) to the (reduced) model space,often used to derive a tight-binding

which is spanned by muffin-tin orbital.

model reproducing the first-principles

In the operator, we introduced weightband

However,function so as to reproduce the band

MLWF has a problem that it requires

structure of low energy region. Note thatseveral optimization parameters. This

the new method does not require any

requirement inhibits the automation ofhandful parameters, so this can be usedmodel construction. If the automation isin the automation of model constructions.

achieved, we can search the materials

We have applied MLO to Si crystal.

self-energy,

structure

conductivity,

The

very

well.

method,effects

only

from

The figure 1 shows the comparison of thematerial databases. In addition, MLWF

energy eigenvalues between the first-

has a difficulty in the model construction

principles calculation and MLO. We canfor slabs and surfaces.

see MLO nicely reproduce the first-

havingdesirable

properties

To overcome the problems of MLWF,

principles eigenvalues. Even in other

we propose a construction method assemiconductors such as GaAs and GaN,

Muffin-tin

the eigenvalues are well reproduced.

based

Localized

Orbital(MLO) based on the PMT basis function

In summary, MLO basis function can

156

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

accurately reproduce the eigenvalues
calculated

in

the

first-principles

References

calculations. In the next step, we apply[1] N. Marzari and D. Vanderbilt, Phys. Rev.

MLO to more difficult systems such as

B 56, 12847 (1997).

interfaces or slabs.

[2] T. Kotani, H. Kino, and H. Akai, J. Phys.

Soc. Jpn. 84, 034720 (2015).

Figure 1: Result of MLO in a simple Si crystal.
Solid line shows the eigenvalues obtained infirst-principles calculations and circles shows
the MLO results. The triangles show the result
considering only the MTO basis.

157

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-Principles Analysis of Melt Structure andProperty in Na Flux GaN Growth
Takahiro KAWAMURA
Graduate School of Engineering, Mie University
1577 Kurimamachiya-cho, Tsu, Mie 514-8507

At first, graphite was used as a C source.
After that Murakami et al. used methane(CH4 ) gases and found they were more effective than graphite [3]. In this study, weinvestigated activation free energies for C–C
and C–H bond dissociation in Na–Ga melts
using first-principles calculations and clarified
the reason why CH4 gases are more eﬀective
than graphite.
We used the first-principles molecular dynamics (MD) simulation program STATESenri (Simulation Tool for Atom TEchnology),
which is based on density functional theory
with norm-conserving/ultrasoft pseudopotentials and plane-wave basis sets [4]. We used thegeneralized gradient approximation of Perdew
et al. for the exchange-correlation function [5].
The cutoﬀ energies for the wave functions andcharge densities were 25 and 225 Ry, respectively. The number of k-points for Brillouinzone sampling was 1×1×1.
We modeled Na–Ga (Na:Ga ≈ 4:1) melt

models composed of about 54 atoms. A setof C and C or C and H atoms was includedin the models. Periodic boundary conditions
were used in all directions. We performed constrained MD simulations for 10 ps at 1073 K
and at constant volume. The C–C and C–H
interatomic distances were constrained to therange of 1.0–3.5 Å. By using data from the latter half of the 10 ps period, free energy profiles
were calculated with the blue-moon ensemble
method [6, 7].
Figures 1 show plots of the free energy profiles for C–C and C–H bond in Na–Ga melt.
The horizontal axis is the constrained interatomic distance. The interatomic distance atwhich the free energies reach a local minimum
indicates a stable bond length. The dissociation activation energies were determined from
3
C-C

Change of free energy [eV]To produce high-quality III-V nitride semiconductor devices at low cost, large bulk
GaN crystals for freestanding substrate aredemanded. The Na-flux method is one of
the most promising crystal growth techniquefor bulk GaN. It is known that C additives
improve the growth rate and suppresses thegeneration of polycrystals [1]. Using firstprinciples calculations, we previously foundthat formation and dissociation of the C–Nbond in the Na–Ga melt strongly aﬀects themechanism for enhanced GaN growth [2].

C-H

2

E

1

C-H

=1.34 eV

0

-1

E

C-C

=2.71 eV

-2

-3
1.0

1.5

2.0

2.5

3.0

3.5

Interatomic distance [Å]Figure 1: Free energy profiles for the C–H bondin the Na and Na–Ga melts.

158

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

the energy diﬀerence between a local maximum and a local minimum. From the result,
we found that the activation free energies for
C–C and C–H bond dissociation are 2.71 and1.34 eV, respectively [8]. Because the dissociation energy of the C–H bond is lower than thatfor the C–C bond, CH4 gas decomposes moreeasily than graphite; that is, CH4 gas is more
eﬀective as a C additive than graphite.

References[1] M. Imade, Y. Hirabayashi, Y. Konishi, H.
Ukegawa, N. Miyoshi, M. Yoshimura, T.
Sasaki, Y. Kitaoka, and Y. Mori: Appl.
Phys. Express 3 (2010) 075501.
[2] T. Kawamura, H. Imabayashi, M.
Maruyama, M. Imade, M. Yoshimura,Y. Mori, and Y. Morikawa: Appl. Phys.
Express 9 (2016) 015601.

[3] K. Murakami, S. Ogawa, M. Imanishi, M.
Imade, M. Maruyama, M. Yoshimura, and
Y. Mori: Jpn. J. Appl. Phys. 56 (2017)055502.
[4] Y. Morikawa: Phys. Rev. B 51 (1995)
14802.
[5] J. P. Perdew, K. Burke, and M. Ernzerhof:
Phys. Rev. Lett. 77 (1996) 3865.
[6] E. A. Carter, G. Ciccotti, J. T. Hynes,
and R. Kapral: Chem. Phys. Lett. 156,
(1989) 472.
[7] M. Sprik and G. Ciccotti: J. Chem. Phys.
109 (1998) 7737.
[8] T. Kawamura,
M. Imanishi,
M.
Yoshimura, Y. Mori, and Y. Morikawa:Comp. Mater. Sci. 194 (2021) 110366.

159

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Analysis on atomic and magnetic structure in magnetic
molecular complex, crystal and interface and investigation of
external electromagnetic field effectMasao OBATA1,2
1

Institute of Science and Engineering, Kanazawa University, Kanazawa, Ishikawa 920-1192
2

Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa,
Ishikawa, 920-1192

We have investigated the electronic andHowever, some differences should be pointed

magnetic structure of ferrimagnetic spinel ofout, e.g., the size of the energy gap on the

NiCo2O4 by using the beyond generalized

majority spin. Remarkably, QSGW predicts thegradient approximation (GGA) approach suchunoccupied energy of Ni eg orbitals to be more

as GGA+U or quasi-particle self-consistentthan 1 eV higher than those calculated by GGA.

GW (QSGW). The NiCo2O4 spinel has drawn a

It may affect the estimation of electric andlot of attention for its material application due

optical properties such as reflectance orto its low cost with excellent electronictransmittance.

high

We also extended the QSGW calculation byelectrochemical activity. However, some of the

combining it with the effective screened

latest reports of its first-principles calculation

medium method [3]. It allows us to estimate theresult have some discrepancies with thefinite electric field effect of slab systems on

experimental one. One of the reasons may

GW level without relying on perturbation

come from the poor electron correlation

theory. We have succeeded in evaluating thedescription of GGA calculation. For this study,

dielectric constant in high accuracy [4].

the first-principles calculation package ecalj [1],References

which adopts the mixed-based set between[1] https://github.com/tkotani/ecalj/

local orbital and plane waves, is used. We[2] H. Al Rasyid, M. Obata, T. Kotani, T.

mainly focused on the inverse spinel structure

Oda, The Science Reports of Kanazawa

containing 14 atoms, namely, eight oxygen andUniversity, in press.

six cation atoms, in the primitive cell.

[3] M. Otani and O. Sugino, Phys. Rev. B,

conductivity,

redox

reaction,and73, 115407 (2006).

The results show that both GGA and QSGW
gave the ferrimagnetic magnetic structure with

[4] H. Sakakibara, T. Kotani, M. Obata, T.

a half-metallic electronic configuration[2].

Oda, Phys. Rev. B, 101, 205120(2020).

160

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Molecular dynamics study on non-equilibrium processes ofsilica and silicates using first-principles calculation andmachine leaning
Masaaki MISAWA
Graduate School of Natural Science and Technology, Okayama University
In this project, we studied (1) pressure-

fayalite during compression and decompression

induced amorphization behavior of fayalite andprocesses were obtained. We elucidated that the(2) shock-compression behavior of quartz

high-fold coordinated Si atoms exist in thebased on molecular dynamics simulations.

amorphous phase even after decompression toan ambient conditions. Additionally, it wasFirst-principles molecular dynamics

found that the Si atoms play a role of network-

simulation

former in the amorphous phase at high-pressure,ofpressure-induced

amorphization of fayalite

but change into network-modifier at an ambientconditions. Furthermore, it is expected that the

Fayalite (Fe2SiO4), an end-member of thecrystal-to-amorphous

medium- or long-range order of Fe atoms aretransformation at high-pressure and room-

partially remained in the amorphous phase,temperature conditions [1]. It was reported that

resulting in the appearance of its unique

thismagnetic ordering structure.

olivine,undergoespressure-induced

amorphizedfayalite

exhibits different features from olivine glasses
synthesized by heat-and-quench processes [2].

Molecular

However there are no theoretical investigations

shock-compression behavior of quartz

aboutusing ANN potential

thephenomenonpressure-induced
and

the

amorphizationpressure-induced

dynamics

simulationofArtificial neural network (ANN) potential,

amorphized phase yet.

which is an interatomic potential constructed by

In this study, we perform first-principles

machine-leaning,

attracts

attentionasamolecular dynamics study of fayalite topromising method to achieve extra-large-scale

investigate energetic and structural properties

molecular dynamics (MD) simulation withof the pressure-induced amorphized fayalite.

first-principles accuracy [3,4]. Application of

The volume-and-energy relations, partial pairthis

distribution functions, and coordination number

phenomena, such as fracture and pressure-changes of crystalline and amorphous phases of

induced161

ANN-MDtotransformation,

far-from-equilibriumisimportanttoActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

understand structural properties of materials

reference data [7]. Using this improved ANN-

under extreme conditions. For this purpose, wepotential, it was succeeded that reproducing thehave tried to perform ANN-MD simulation ofelastic-to-plastic transition behavior and plastic

shock-induced structural transformation of

deformation of α-quartz with an accuracy close

silica.

to FPMD simulation. Thus, the ANN-potential

To compute shock-compression behaviors

trained with energy, force, and pressure is awithin the framework of MD method, thepotentially powerful tool to investigate wide

multiscale-shock technique [5] was employedrange of far-from-equilibrium phenomena andin our simulations. Potential energy of shock-will also provide useful information for solid

compressed

earth physics field in future.

α-quartz

obtainedbyfirst-

principles MD (FPMD) method is used as areference data for training of ANN-potential.

References

As a result of ANN-MD simulation for elastic[1] Q. Williams et al.: J. Geophys. Res. 95

shock-wave
behaviorsofregion,elastic-deformation(1990) 21549.

α-quartz

was[2] S. Kohara et al.: Science 303 (2004) 1649.

successfully

reproduced with high-accuracy [6]. On the[3] J. Behler and M. Parrinello: Phys. Rev. Lett.

other hand, for plastic shock-wave region, the98 (2007) 146401.

ANN-potential[4] N. Artrith and A. Urban: Comput. Mater.

hascompletely

failedon

prediction of both structure and energy, because

Sci. 114 (2016) 135.

of that irregular structure appears and rapid[5] E. Reed et al., Phys. Rev. Lett. 90 (2003)

movement of atoms occurs during the elastic-

235503.

to-plastic transition process.

[6] M. Misawa et al.: J. Phys. Chem. Lett. 11

In order to improve the predicting ability of(2020) 4536.

ANN-potential, we introduce a more accurate[7] K. Shimamura et al.: J. Chem. Phys. 153

training method that uses not only potential(2020) 234301.

energy but also atomic force and pressure as

162

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Search and realization of novel electronic properties ofsolid surfaces and interfaces and of small particles
Takeshi INAOKA

Department of Physics and Earth Sciences, Faculty of Science,
University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa 903-0213
We mention two subjects which we
addressed this year.
The Ni(110)-(2x1)O surface is known tohave a missing-row reconstruction
structure, as is shown in Fig. 1 [1]. Oxygen(O) atoms are adsorbed at bridge sites toform Ni-O-Ni atomic chains in the y,namely, [001] direction. The O-derived
bands exist near the upper and lower
edges of the substrate Ni bands. The
bands around the lower edge have alreadybeen studied well by means of firstprinciples calculations using small-scaled
slabs and some experimental studies.
This year, using a large-scaled slab
composed of 21 Ni atomic layers andadsorbed O atoms at both surfaces, weinvestigated the upper O-derived bands,
and identify them with surface states
when separated up from the upper edge ofthe substrate bands.
We employed the program package‘Vienna Ab initio Simulation Package’(VASP) [2,3] on systems B and C.

Fig. 1 Missing- row
reconstruction
structure at theNi(110)-(2x1)O
surfaceyNanoribbons with zigzag edges have
localized edge states, while those witharmchair edges possess no edge states.
We consider the electronic structure ofgraphene systems of finite area. By meansof the tight-binding method, we examined if
edge-localized states can be formed in
finite graphene systems, and how theelectronic structure of these systems
depends on system shapes or areas.
(1) Identification of surface states at theNi(110)-(2x1) O surface [4]Assuming a slab of 21 Ni-atom layerswith O atoms adsorbed at each surface
and using the generalized gradient approximation, we obtained the optimized groundstate structure. Figure 2 (a) shows theband dispersion on the  - Y line formajority spin. As is displayed by an arrow,
there exist a pair of nearly degeneratebands that lie above the densely
distributed substrate bands due to Ni dorbitals. Figure 2 (b) exhibits electrondensity isosurfaces of the higher energy
one of the above paired states at the

E-EF (eV)(a)

x [ 1 10]

0

-0.5

[001]

Graphene is a very popular single-layer
structure of carbon (C) atoms arranged ina hexagonal lattice. The band structure ofthis material is characterized by aso-called Dirac cone, and predicts an
extremely high electron mobility. When thismaterial takes a form of nanoribbons, theband structure due to  orbitals around the
Fermi level depends on edge shapes.

163

-1



Y

y

x

Fig. 2 (a) Band dispersion on the  - Y line
for majority spin and (b) electron density
isosurfaces of the state on the midpoint ofthe  - Y line, as is arrowed in (a).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

middle point of the  - Y line. Isosurfacesof the lower one are almost the same. This
isosurface map clearly indicates that thisstate is localized near the surface, and thatthe px orbital of an O atom, which extends
in the x, namely, [ 1 10] direction, plays amajor role, and it bonds to dxy orbitals of asurface Ni atom. We can recognize thistailed localization at the surface only insuch a large-scaled slab as ours. However,
we still have to verify that these surface
states really exist even in a semi-infinite
substrate. We consider that bulk which canbe obtained in the limit of increasing theslab thickness, and evaluate the upperedges of those bands which correspond to
the substrate bands of the slab. We findthat these upper bulk-band edges are
below the paired nearly degenerate bands.
Through this analysis, we concluded thatthe surface states are really present in thesemi-infinite substrate.
We made the same analysis of the
O-derived bands around the upper edge ofthe substrate bands on the  - X line aswell. We identified the surface states inwhich the py orbital of an O atom bonds tothe dyz orbitals of a surface Ni atom.
(2) -band structure of finite graphenesystems [5]We examined the electronic structure offinite graphene systems for various shapes
and areas. Each eigenstate is expressed ina form of a linear combination of pz orbitalsof C atoms extending in a plane-normal
direction, and each component of its
eigenvector represents the pz orbital
coefficient of the corresponding C atom.
As an example of the results, figure 3
displays the pz-orbital coefficients in color
scale of (a) the lowest-energy state (n=1),(b) the highest-occupied state (n=23) and(c) the highest energy state (N=46) for aparallelogram graphene with 46 C atoms.
This parallelogram is quite special in having
only zigzag edges.
As is shown in Fig. 3 (a), the pz orbital
coefficients in the lowest-energy state arecoherent in sign. On the other hand, figure
3 (c) indicates that, in the highest-energy
state, the coefficient alternates in signalong each hexagonal atom ring. In either of164

these states (a) and (c), the coefficient
amplitude tends to decrease as we movefrom the center to the edge. Thesefeatures are common to various shapes offinite graphene.
Figure 3 (b) shows that the highest
occupied state has edge localization. Red
and blue circles indicate atoms with large
positive and low negative coefficients,
respectively. These coefficients with large
amplitudes alternate in sign along the edgeline. The electron density distribution is
localized around the acute-angle vertices,namely, at those edges farther away fromthe center. Generally, edge localization
occurs at zigzag edges in specific statesat or just near the Fermi level.
(a)

(b)

0.4

(c)

0.3
0.2
0.1
0
0.1
0.2
0.3
0.4

Fig. 3 pz-orbital coefficients in color scale fora parallelogram graphene. (a) Lowest- energy
state, (b) Highest-occupied state, (c)Highest-energy state.

References[1] G. Kleinle et al., Surf. Sci. 225 (1990)
171-183.
[2] G. Kresse and J. Hafner: Phys. Rev. B 47
(1993) 558-561.
[3] G. Kresse and J. Furthmüller: Comput. Mat.
Sci. 6 (1996) 15-50.
[4] T. Inaoka and Y. Uehara: Identification of
surface states formed above the substrate
bands of the Ni(110)-(2x1)O surface, to besubmitted.
[5] T. Ohshiro and T. Inaoka: unpublished.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical Study on Electronic Properties
in New Nanoscale Surfaces and Interfaces
Katsuyoshi KOBAYASHI
Department of Physics, Ochanomizu University
2-1-1 Otsuka, Bunkyo-ku, Tokyo 112-8610

Mirror-symmetrical two states with respect
to each other in a two-dimensional Brillouinzone form a mirror-symmetrical state by making the system ﬁnite along the direction perpendicular to a mirror symmetrical line. All
states become mirror symmetrical in onedimensional systems and all photoelectrons excited with linearly polarized light are spinpolarized. However, the wave functions areeither symmetrical or anti-symmetrical, andthe spin orientation of photoelectrons is determined by the symmetry of wave functions.
The spinor in strong spin-orbit systems containboth type of wave functions and the magnitudeof these components vary.
To investigate the spin polarization in onedimensional Rashba systems we used a simple
Rashba Hamiltonian and numerically solved it.
We used both plane-wave expansion and ﬁnite
diﬀerence methods, and veriﬁed that the diﬀerence between results by these methods is small.
Figure 1 shows an example of calculated re-165

sults. The electron spin is positively and negatively polarized for kx < 0 and kx > 0, respectively, where kx is the wave number along
the one-dimensional direction. The polarization decreases with decreasing |kx |. However,spin polarization is not necessarily low evennear kx ∼ 0. This is due to the propertiesof the Rashba Hamiltonian for the states withenergy E < 0.
Weighted spin expectation value

In 2020 we theoretically studied onedimensional Rashba systems. Perfect spinpolarization and spin-orientation reversal ofphotoelectrons have been observed in spinand angle-resolved photoelectron spectroscopy(SARPES) of strong spin-orbit systems [1, 2].
These phenomena have theoretically been explained in terms of mirror symmetry of thesystems [2, 3]. A problem, however, is thatthe states having mirror symmetry are restricted to lines in two-dimensional Brillouinzones. Only a small amount of photoelectrons
are fully spin polarized. To improve the efﬁciency of spin polarization we considered a
one-dimensional Rashba system and theoretically investigated it.

kx

Figure 1: Spin expectation values calculated asa function of kx for a ﬁxed energy E < 0. Red
and green circles show symmetrical and antisymmetrical components of wave functions.
Expectation values are weighted with the normof each component.

References[1] C. Jozwiak et al.: Nat. Phys. 9 (2013) 293.
[2] K. Yaji et al.: Nat. Commun. 8 (2017) 14588.
[3] K. Kobayashi et al.: Phys. Rev. B 95 (2017)205436.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study on structural elementary excitations at
semiconductor surfaces and interfaces
Hiroyuki KAGESHIMA
Graduate School of Natural Science and Technology, Shimane University
1060 Nishi-Kawatsucho, Matsue, Shimane 690-8504

Our project has been focused on physicalproperties of structural elementary excitationsof semiconductor surfaces and interfaces. We
have performed one topic in this year. It is thephysical properties of oxygen vacancies (VO ) in
SiO2 at interface with Si. [1] The calculations
were performed based on the ﬁrst-principles
calculation. Program package PHASE/0 was
employed.
Because of recent progress of integrated
circuits,
three-dimensional
metal-oxidesemiconductor ﬁeld-eﬀect transistors (MOSFETs) have been attracting attention. The
vertical body-channel-MOSFET has a gateinsulating thermally oxide Si ﬁlm around a Si
pillar with a diameter of several tens of nm,
but it is considered that a large stress distributes in the oxide ﬁlm. When a Si nanowire
with a width of 50 nm and a thickness of
30 nm is processed by dry oxidation at 1000◦ C
for 80 min, it is known that a compressive
strain of about 3% is accumulated near theinterface and a tensile strain of about 3% isaccumulated near the outer surface.
The strain induced in the oxide ﬁlm musthave an unconventional eﬀect on the ﬁlm reliability such as dielectric breakdown. It is known
that the dielectric breakdown of the oxide ﬁlm
is triggered by VO -related defects in the ﬁlm.
The VO -related defects trap holes, and transform into 3-coordinated Si’s with +1 charge.
These 3-coordinated Si’s diﬀuse and aggregate
under a gate-channel electric ﬁeld of MOSFET
operation to create a one-dimensional conduc-tive chain from the Si interface to the gate interface in the oxide ﬁlm. Then, a gate leak current ﬂows through this chain, and leads to thedielectric breakdown. Since the oxide ﬁlm of
the three-dimensional MOSFETs is subjectedby the strain, it is considered that these processes are also aﬀected by the strain.
We focused on the fundamental properties of
VO in the oxide ﬁlm, and investigated the effect of strain on them using the ﬁrst-principles
calculation. We found that the stability of VO
increases under compression. We also foundthat the height of the diﬀusion barrier increases under compression. In addition, we
found that the diﬀusion barrier height is determined by the Si-Si bond length of the VO .
Considering the gate oxide ﬁlm in the vertical body-channel-MOSFET, the VO density
increases because the interfacial oxide ﬁlm issubjected to compressive strain. This suggeststhat interfacial traps are more likely to occur
and performance may be slightly degraded. On
the other hand, tensile strain is applied to thesurface oxide ﬁlm to reduce the density of VO ,but diﬀusion of VO is promoted. This meansthat the reliability of the oxide ﬁlm is aﬀectedby the stain because VO can diﬀuse from theinterface of the oxide ﬁlm to the surface.

References[1] K. Yata and H. Kageshima, Jpn. J. Appl.
Phys. 60 (2020) 035504 (6 pages).

166

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Prediction of properties of organic ferroelectrics andpiezoelectrics by ﬁrst-principles calculation
Shoji ISHIBASHI
Research Center for Computational Design of Advanced Functional Materials (CD-FMat),
National Institute of Advanced Industrial Science and Technology (AIST)
Tsukuba, Ibaraki 305-8565

Organic small-molecular crystals show a variety of crystal structures and electronic properties. Among them, there is a class of compounds called “hydrogen-bonded systems”, inwhich proton transfer causes π-bond dipole
switching. Some of them show ferroelectricity
or antiferroelectricity [1]. First-principles calculations toghther with the Berry phase theory
successfullty predict spontaneous polarization
values of such ferroelectrics [2, 3, 4, 5, 6]. Antiferroelectrics consist of polar subunits. By applying a strong electric ﬁeld, some of them canbe converted into ferroelectric phases. Evaluating polarization of the subunit, the total
polarization can be predicted in such induced
ferroelectric phases [7, 8].
In 2020, we have applied this approachin predicting electric-ﬁeld-induced polarization of bis-(1H-benzimidazol-2-yl)-methane(BI2C), in which non-polar and/or polar subunits exist depending on temperture, andthe obtained polarization values are in good
agreemet with experimetally obtained results[9]. In addition, similarly to our previous workon antiferroelectric squaric acid [10], calculations with a computationally-applied electricﬁeld are ongoing for several hydorogen-bonded
ferroelectrics and anitiferroelectics.

[2] S. Horiuchi, K. Kobayashi, R. Kumai,
and S. Ishibashi, Nat. Commun. 8, 14426(2017).
[3] F. Kagawa, S. Horiuchi, N. Minami, S.
Ishibashi, K. Kobayashi, R. Kumai, Y.
Murakami, and Y. Tokura, Nano Lett. 14,
239 (2014).
[4] K. Kobayashi, S. Horiuchi, S. Ishibashi,
F. Kagawa, Y. Murakami, and R. Kumai,
Chem. Eur. J. 20, 17515 (2014).
[5] S. Horiuchi, Y. Noda, T. Hasegawa, F.
Kagawa, and S. Ishibashi, Chem. Mater.
27, 6193 (2015).
[6] S. Horiuchi, S. Ishibashi, K. Kobayashi,
and R. Kumai, RSC Adv. 9, 39662 (2019).
[7] S. Horiuchi, R. Kumai, and S. Ishibashi,
Chem. Sci. 9, 425 (2018).
[8] K. Kobayashi, S. Horiuchi, S. Ishibashi,
Y. Murakami, and R. Kumai, J. Am.
Chem. Soc. 140, 3842 (2018).
[9] S. Horiuchi, S. Ishibashi, R. Haruki, R.
Kumai, S. Inada, and S. Aoyagi, Chem.
Sci. 11, 6183 (2020).
[10] S. Ishibashi, S. Horiuchi, and R. Kumai,
Phys. Rev. B 97, 184102 (2018).

References[1] S. Horiuchi and S. Ishibashi, J. Phys. Soc.
Jpn. 89, 051009 (2020).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Search of accessible surfaces for catalyst informatics
Yoyo HINUMA
Institute of Innovative Research
Tokyo Institute of Technology
4259 Nagatsuta-cho, Midori, Yokohama, Kanagawa 226-8502
High catalytic reactivity in oxides is

topmost and bottommost surfaces need to be

expected in high index surfaces and at surface

reconstructed, which is the case in the normal

defects, such as corners and step edges, sincespinel surfaces in this study [3]. Surfaces which

there are cations and anions with more

do not have the lowest energy for a given

unfavorable

environmentsorientation, including terminations found byincluding low coordination number. Theoreticalgenetic algorithm calculations (obtained using

studies are leading experimental investigations

the USPEX code [4]), or its surface energy canon irregular sites because of the difficulty of thebe reduced by forming macroscopic facets [5],latter.

were removed.

coordination

To increase the volume and variety of the

The following orientations were found to bedata without compromising veracity, surfaces

experimentally accessible in β-Ga2O3, in orderthat are appropriately reconstructed need to beof increasing surface energy: (100), (20-1),

added. From another viewpoint, terminations(310), (101), (11-2), (11-3), (11-1). This methodthat are likely to be experimentally accessible

can be used for other materials, and will be aneed to be distinguished from those that are not

powerful tool to find overlooked high-energy

becausesurfaces.

only

surfaces

that

can

be

experimentally synthesized, preferably withless effort, can be used industrially andReferences

therefore contribute to improvement of our[1] Y. Hinuma et al.: Comp. Mater. Sci. 113

society.

(2016) 221.

This study considered 67 terminations (34[2] Y. Hinuma et al.: Phys. Rev. Mater. 2 (2018)

orientations) of β-Ga2O3. The automated124603.

nonstoichiometric and nonpolar slab-and-model[3] Y. Hinuma et al.: Mater. Trans. 61 (2020) 78.

generation algorithm already developed by[4] A.R. Oganov et al.: J. Chem. Phys. 124,

Hinuma et al. [1,2] was expanded to allow(2006) 244704.

automatic derivation of models where the[5] Y. Hinuma et al.: Mater Trans.61 (2020) 143.

168

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Calculation of multication oxide surface properties forcatalyst informatics
Yoyo HINUMA
Institute of Innovative Research
Tokyo Institute of Technology
4259 Nagatsuta-cho, Midori, Yokohama, Kanagawa 226-8502
Surface point defects of metal oxides, fornonstoichiometric and nonpolar slab-and-model

instance O vacancies, have a dominant effectgeneration algorithm already developed byon heterogeneous catalysis. The Mars-Van

Hinuma et al. [1,2] was expanded to allow

Krevelen mechanism is one of the mostautomatic derivation of models where thefrequently encountered catalytic process. In one

topmost and bottommost surfaces need to be

example, O vacancies on a metal oxide catalyst

reconstructed, which is the case in the normal

surface act as reaction sites. The energy

spinel surfaces in this study [3]. A large

minimum required to remove O from a surface,variation of up to 3.6 eV in the smallest EOvac ofwhich is denoted as the surface O vacancyaformation energy (EOvac), can be used toorientations of same material. EOvac wasrationalize and predict catalytic performance intypically higher in a more stable surface withinsuch a catalytic process. Calculation of EOvac

the same compound, which is in line withrequireswithchemical intuition. A good correlation between

sufficient spacing between O vacancies, hence

EOvac and Ebulk, band gap, and electron affinity

some estimation of EOvac from less costly

was obtained between the same orientation for

calculations, such as slab-and-vacuum model(100) and (110) surfaces, although the trend for

calculations with minimum cell size and eventhe (111) surface was contradictory.

bulk calculations, will be effective in screening

Referencesmaterials for a given purpose.

[1] Y. Hinuma et al.: Comp. Mater. Sci. 113aslab-and-vacuum

model

The EOvac of ZnM2O4, where M is one of Al,

surfacewasobservedfordifferent(2016) 221.

Ga, In, V, Cr, Mn, Fe, or Co, was calculated.

[2] Y. Hinuma et al.: Phys. Rev. Mater. 2 (2018)

These compounds take the normal spinel

124603.

structure, and the (100), (110), and (111)[3] Y. Hinuma et al.: Mater. Trans. 61 (2020) 78.

surfaces

wereevaluated.

The

automated

169

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles study on complexes of impurity anddislocation in GaN p-n diodes
Yosuke HARASHIMA1,2
1
Institute of Materials and Systems for Sustainability, Nagoya University
Furo-cho, Chikusa, Nagoya, Aichi 464-8601
2
Center for Computational Sciences, University of Tsukuba
Tennodai, Tsukuba, Ibaraki, 305-8577

The development of power semiconductor
devices is one of the key issues for the realization of a sustainable society. GaN has properties suitable for power devices, such as a large
band gap, and is expected to be a candidate
for next-generation power semiconductor materials. On the other hand, the threading dislocations generated during the synthesis of GaN
become a source of leakage current, which impairs the rectifying eﬀect, an important characteristic of the device. It has been reported
that the leakage current is related to the typeof threading dislocation and the condensationof impurities around the dislocation, but the
microscopic mechanism of leakage current generation has not been clariﬁed.
Power semiconductor devices consist of a
combination of p-type and n-type layers, with
impurities such as Si and Mg doped to eachlayer. To understand the mechanism of leakage current generation, it is necessary to understand the electronic state in each layer. The
electronic structure of the complex of Mg andscrew dislocations doped to make the p-layer
has been clariﬁed by our previous studies usingﬁrst-principles calculations and atom probe tomography. [1] The purpose of this study is toanalyze the interaction between Si impurities
doped to make the n-layer and dislocations,and to clarify the properties of the complex
consisting of Si and dislocations.
The eﬀective mass of electrons is smaller

than that of holes in GaN, and the eﬀective
Bohr radius, which indicates the width of the
impurity states, is larger. Therefore, it is necessary to consider larger systems. For larger
system size calculations, we use RSDFT[2, 3], ahighly parallelized and eﬃcient ﬁrst-principles
code. In this study, we consider a screw dislocation with the Burgers vector [0001]. The dislocations break the periodic structure and weuse a supercell. In order to avoid these strainsaﬀecting each other at the periodic boundary,a vacuum layer is inserted in the lateral directions of c-axis.
We consider a 21 Å × 27 Å × 30 Å supercell, which includes about 800 atoms. An
Si atom is substituted at a Ga site. In orderto analyze the binding energy of Si, we performed calculations for several substitutionalsites. We optimized the atomic positions andobtained the stable structures of the complex.
We are analyzing the results for the binding
energy of Si to the screw dislocation.

References[1] T. Nakano, Y. Harahsima, et al.: Appl.
Phys. Lett. 117 (2020) 012105.
[2] J.-I. Iwata, et al.: J. Comput. Phys. 229(2010) 2339.
[3] Y. Hasegawa, et al.: Int. J. High Perform.
Comput. Appl. 28 (2014) 335.

170

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Simulation of scanning tunneling microscopy images ofgraphene ribbons with edges
Junhuan LI, Kenta ARIMA
Department of Precision Engineering, Graduate School of Engineering
Osaka University, Yamada-oka, Suita, Osaka 565-0871
We are aiming at elucidating local electronic

local density of states, an electron density was

structures of finite-size graphene sheets andintegrated over a specific energy window, or atheir impact on scanning tunneling microscopyeV,(STM) images. For this purpose, we have

Molecular Orbital). At each (x, y) coordinate, astarted first-principles calculations of single-

z-height possessing the same electron density

layer graphene ribbons possessing either zigzag(6.72×10-4 /Å3) was investigated and its contour

or armchair edges by the use of a simulation

map was depicted. This approximates a

package named STATE (Simulation Tool for

simulated STM image at the sample bias of a V.

Atom TEchnology). STATE is based on the

We used the module (intel/18.0.5) for thedensity functional theory. The exchange andcompilers and mpt/2.16 for MPI library. The set

correlation potential is described by theof calculation was usually executed on F4cpu

generalized gradient approximation by Perdew-

or F36cpu with suitable nodes in ISSP.

below

HOMO

(Highest

Occupied

To check the performance of our calculation,

Burke-Ernzerhof (GGA-PBE). We also usedand

we modeled a graphene nanoribbon with zigzag

pseudopotentials. When running STATE, weedges terminated by H atoms. Figure 1(a)first defined the atomic structure of a finite-sizeshows a simulated STM image of a zigzag-

graphene. This model as well as otheredged ribbon named C28 at the sample bias of -parameters were placed as an input file on a

1.0 V. C28 indicates the ribbon width

supercomputer.

field

possessing 28 dimer lines across the width. In

method was employed, which is an iterative

Fig. 1(b), a hexagonal carbon network is

method that involves selecting a Hamiltonian,superimposed in the image in Fig. 1(a). Figure

solving the Kohn-Sham equation to obtain a

1 shows that either a hexagonal or a triangularmore accurate set of orbitals, constructing thepattern is formed in the interior of the ribbon

potential for each wave function, and solving

whereas isolated bright spots are formed at boththe Kohn-Sham equation again with these until

edges of the ribbon. The latter is caused by thethe results converge. In order to draw a map of

localized electronic states at a zigzag edge,

both

a

plane-wave

The

basis

set

self-consistent

171

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

which agrees with literature [1]. In the next

References

fiscal year, we are going to characterize the[1] P.L. Giunta and S.P. Kelty: J. Chem. Phys.,
114 (2001) 1807.

distribution of local charge densities of thearmchair-edged graphene ribbon and to unveil[2] J. Li, K. Arima et al.: JSAP (The Japan

its relationship with an STM image around theSociety of Applied Physics) fall meeting

Fermi level.

(2020) 05-101.

Regarding this project, we had three oral

[3] J. Li, K. Arima et al.: JSPE (The Japan

presentations at domestic meetings in 2020 [2-Society for Precision Engineering) fall4].

meeting (2020) 517.
[4] J. Li, K. Arima et al.: JVSS (The Japan(a)Society of Vacuum and Surface Science)(b)

meeting (2020) 1Ba03.

Fig. 1 (a) Simulated STM image of zigzagedged graphene nanoribbon (C28). (b) A
carbon network is superimposed in theimage in (a).

172

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

A theoretical study on the effect of impurity doping on thethermoelectric performance of environmental friendly silicide SrSi2
Tsutomu Iida, Naomi Hirayama, Daishi Shiojiri, Tomoyuki Kadono, and Masato Yamaguchi
Department of Materials Science and Technology, Faculty of Industrial Science and Technology,
Tokyo University of Science, 6-3-1 Niijyuku, Katsushika-ku, Tokyo, 125-8585, Japan
properties from theoretical considerations.
This year, we carried out DFT calculations of
the transport characteristics of α-SrSi2 using the
Heyd–Scuseria–Ernzerhof screened hybrid
functional,
andthencomparedtheexperimentallymeasuredthermoelectric
properties with the computational results.
The bandgap of the polycrystalline α-SrSi2grown by vertical Bridgman method estimatedfrom the carrier density dependence on
temperature was 13.1meV. When the mixing
parameter of the Hartree-Fock contribution to
the exact exchange was 18.7%, the bandgap was
estimated to be 13.27 meV, which almost
reproduces the experimental Eg value.
Furthermore, Seebeck coefficients were
calculated using the Boltzmann transport theory,and the results obtained using the chemical
potential that matches the carrier concentration,
which was determined experimentally, were ingood agreement with the temperaturedependence of the Seebeck coefficient obtained
experimentally. It was concluded that firstprinciples calculations using the hybrid
functional can successfully predict thethermoelectric transport properties of narrowgap thermoelectric semiconductors.

Thermoelectric semiconductors, especiallythose operating at low temperatures, areexpected to be applied to power generation
systems that utilize the vaporization of liquefied
natural gas as cold heat energy sources, and to
self-powered wireless sensors.
α-SrSi2 has been identified as a potential TE
material, and its main attributes are its lightweight, its non-toxicity, and the worldwide
abundance of its constituent elements. α-SrSi2
has relatively good power generation
performance, with a dimensionless figure of
merit ZT = ~0.15 at 300 K [1] and p-typeconduction when the composition is
stoichiometric. For practical use, in order tofurther improve the p-type thermoelectricperformance and achieve n-type conduction of
α-SrSi2 so as to configure pn devices, it would
be necessary to quantitatively understand theelectronic structure through experimental
studies and theoretical calculations.
The electrical properties of polycrystalline αSrSi2 have been examined by M. Imai et al. [2],who revealed that α-SrSi2 is a narrow-gap
semiconductor with an energy gap of 35 meV
and that its dominant carriers are holes. Theirresults, however, were not consistent with theresultsofprevious
electronic-structure
calculations for which density-functional theory(DFT) with the conventional generalized
gradient approximation was used. Most of thecalculated bandgap values were about 0 eV orless, which is much smaller than theexperimentally observed values. This difference
makes it difficult to predict the thermoelectric

References[1] S. K. Singh and M. Imai, Intermetallics 127,
106981 (2020).
[2] M. Imai, T. Naka, T. Furubayashi, H. Abe, T.
Nakama, and K. Yagasaki, Appl. Phys. Lett. 86,
032102 (2005).

173

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

STM simulations for Si(111)7 × 7 surfaces
Kei TANIMOTO and Ken HATTORI

Graduate School of Science and Technology, Nara Institute of Science and Technology,
Takayama, Ikoma, Nara 630-0192
Using

scanning

tunneling

microscopy

The small-size 4 × 4 surface has an advantage(STM), author's group has been studied ironsilicides formation on Si(111) [1] prepared inof fast calculation compared to that in the 7 × 7

ultra-high vacuum. In the initial stage of

surface, maintaining the specific 7 × 7 surface

property (dimer － adatom － stacking-fault

Si(111) 7 × 7 with isolated Fe atoms, we

structure): 4 Si adatoms on 2 × 2 T4 sites, and 2

experimental STM images [2]. Using the super4 × 4 unit cell.

of 4 restatoms terminated with H atom, in aobserved 5 different adsorption types inOn the basis of these results we extended

computing system in the institute for solid statephysics,

wecarried

out

first

principles

the calculations to 7 × 7 surfaces in this year,

calculations for several configurations of Fe

firstly focusing a clean surface using theatoms on Si(111)4 × 4 surface in the last year.

calculation package of Simulation Tool for

Fig. 1. Schematics of clean Si(111) 7 × 7 surface model in side (upper left) and top (upper right)

views, and simulated STM images in filled states (left panel) and empty states (right panel) at
different sample bias voltages (Vs). The red arrow represents side-viewing direction.

174

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Atom TEchnology (STATE)-Senri [3]. The

structure capturing an Fe atom, extension of thecalculated clean 7 × 7 model consists of a Si

adatom-layer, six Si-layers, and a bottom H-

Fe adsorption configurations in the 4 × 4

models.

terminated layer, with 347 atoms. All atoms

The

authors

thankProfs.

Morikawa,

except the last Si layer and bottom H layer are

Hamada, and Inagaki in Osaka University, andfully relaxed at <0.05 eV⁄Å from atomic

Prof. Yanagisawa in Ryukyu University for

positions predicted in the 4 × 4 model, under

their great support in STATE-Senri calculations.

images are simulated using a special STM

References

displaying tool [4].

[1] K. Kataoka, K. Hattori, Y. Miyatake, and H.

700 bands without spin polarization. STM

Daimon, Phys. Rev. B 74 (2006) 155406.

The obtained STM simulation images in Fig.
1 display 12 adatoms in a 7 × 7 unit cell at the[2] K. Kataoka, Dr.. Thesis, Nara Institute ofall Vs, and successfully 6 restatoms at Vs = -1.0

Science and Technology, Nara (2006).

V. We also recognize that corner adatoms[3] Y. Morikawa, Phys. Rev. B {\bf 63} (2001)(COA) are brighter (higher) than center

033405, and references therein.

adatoms (CEA), and atoms on a faulted half[4] The precise STM calculation tool has been

(FH) unit cell are brighter (higher) than thosedeveloped by Prof. I. Hamada in Osaka

on an unfaulted half (UH) unit cell, in filled

University and Prof. S. Yanagisawa in Ryukyu

states. These features are consistent with the

University.

experimental results. The relaxed 7 × 7 cleansurface structure can be applied for the starting175

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles Study of Defects of Magnesium Alloys
Daisuke Matsunaka
Department of Mechanical Systems Engineering,
Shinshu University, 4-17-1 Wakasato, Nagano 380-8553
Magnesium (Mg) has been of increasinglyinterest

from

the

engineeringradius. On the other hand, changes in USFE

viewpoint,

and SSFE for the second-pyramidal slip were

because of its low density and relatively highnot monotonic with respect to the atomic radius

specific strength.

of the solute atom.

In this study, we calculate generalized

In Mg-Y alloy, enhanced activation of

stacking fault energy (GSFE) surface, topyramidal slips improves ductility. It has been

evaluate activation of each slip system in Mg,

suggested that the activation of pyramidal slips

using first-principles calculations. In GSFE

was attributed to intrinsic I1 stacking fault (SF)calculations for pyramidal slips, it is importantenergy stabilized by Yttrium addition. We

to take account of relaxation of atomic

investigated defect nucleation in the vicinity ofconfiguration perpendicular to the slip direction.

a pre-existing intrinsic I1 SF by molecular

For the first-pyramidal slip, out-plane atomic

dynamics simulations. While formation of (11-relaxations were observed during the slip21) twin was observed under shear stress onprocess. The out-plane atomic relaxations(0001)

reduce the GSFE and cause an energy

dislocations were generated with SFs for higher

minimum on the curve, corresponding to theresolved shear stress for pyramidal slips. The

stable stacking fault energy (SSFE). For the

dissociation reactions of the dislocations at thesecond-pyramidal

atomicside ends of the I1 SF were energeticallyrelaxation perpendicular to the slip direction

evaluated, and it was implied that nucleation of

was associated with the stable stacking fault.

the <c+a> dislocations on the first-pyramidal

slip,

in-planealong[11-20],<c+a>partialplanes is more favorable than on the second-

In order to investigate effects of alloying
elements, we carried out the GSFE calculations

pyramidal planes.

with alloy models in which one solute atom

References

was substituted at the slip plane. The unstable[1] R. Hori: Master Thesis, Shinshu Univ.

stacking fault energy (USFE) and SSFE for the(2021).

first-pyramidal slip were more reduced by[2] S. Yoshikawa and D. Matsunaka: Comp.

addition of the solute atom of the larger atomic

Mater. Sci. 179 (2020) 109

176

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Elucidation of the mechanism of self-ordering phenomena
at the interface between organic and inorganic materials
Tomoya Shiota,1 Yuuichi Orimoto,2 Yuriko Aoki2
1

Department of Molecular and Material Sciences, Interdisciplinary Graduate School ofEngineering Sciences, Kyushu University, Fukuoka 816-8580, Japan.
2

Department of Material Sciences, Faculty of Engineering Sciences,
Kyushu University, Fukuoka 816-8580, Japan

We have studied an interface system between

surface dimer was investigated to explicitly

an inorganic solid surface and organic molecules,

account for Ge(001) surface dimer conditions.

PTCDAs on Ge(001) surface using the Density

On the Ge(001) clean surface, the obtained

Functional Theory (DFT) calculations with theactivation barriers for dimer flipping underclimbing image nudged elastic band method andvarious dimer configurations are enough small

kinetic Monte Carlo simulation. All MPI

to overcome at high temperature as well known

parallelized DFT calculations were performed

in many previous experiments. The activation

using Vienna Ab initio Simulation Package

barrier of surface dimers between adsorbed(VASP) version 5.4.4 on the ISSP's newmolecules was larger than that of the clean

supercomputer system.

surface, but sufficient to overcome it at 500K.

First, we elucidated the hopping mechanismof the isolated adsorbed PTCDA molecules on
Ge(001) surface. [1] Subsequently, we simulated
that a PTCDA molecule hops on the Ge(001)under the intermolecular interactions as shownin Fig. 1. It was found that lone adsorbed
PTCDA molecules cannot hop on Ge(001). On
the other hand, they can hop under theintermolecularinteractions

at

500K.

Successively, we performed kinetic Monte Carlo
Fig. 1: The hopping of PTCDA on Ge(001)under the intermolecular interaction.

simulations using the activation energies
obtained by DFT calculations for the hopping of
PTCDA

moleculesinvariousproximity

adsorption configurations at medium coverage.

References

As a result, the formation of one-dimensional[1] T. Shiota, W. Mizukami, H. Tochihara, K.

molecular chains was confirmed.

Yagyu, T. Suzuki, and Y. Aoki, J. Phys. Chem. C
124, 24704 (2020)

Next, the flip-flop motion of the Ge(001)177

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study on Machine Learning Model of Carrier Dynamics
in Semiconductor Devices
Masakazu Muraguchi
Faculty of Engineering, Hokkaido University of Science,
Maeda, Teine, Sapporo 006-8585
variation of the electron density distribution
using time evolution calculations. For
example, the transmission probability with
impurity in the nanowire is sensitive to theposition shift of impurities for y-direction(see Fig.1). As the machine learning method,a Random Forest (RF) is employed formodeling. The mean absolute error isevaluated. As the result, the accuracy of themodel is improved by performing machinelearning based on the extracted features. The
proposed method provides a new perspective
for analyzing the motion of electrons in
nanoscale semiconductors.

In a two-dimensional nanowire systemwith random impurity distribution, wedeveloped a model to predict the electrontransmission probability from the impurity
distribution by combining the time evolutionof the electron wave function and machinelearning.
Electron conduction in nanoscale twodimensional wires with random impurity
distribution is investigated. To prepare thedataset for machine learning, the timedevelopment of an electron wave-packet is
calculated, and obtain the transmission
probability. The time-dependent schrödinger
equation is solved where the finite difference
method is employed with the second-order
split operator method [1,2]. Note that asupercomputer system was used for thesetime-consuming time evolution calculations.
Then, a model that can predict thetransmission probability of electron wave
packets from the space distribution of
impurities build by using the machinelearning. Through this process, the ways to
extract the features of the transmission on
this system is investigated.
The impurity distribution can be
reproduced when the central coordinates areavailable. Therefore, this can be used as afeature. However, this does not directly
include the whole shape of the potential
distribution. Therefore, the features of thesystem were extracted by analyzing the time

Fig.1 Transmission probabilities with the electronenergy where the positions of impurities are shifted
3.3 nm to y-direction between the case (a) and (b).

References[1] N. Watanabe and M. Tsukada: Phys. Rev. B 62
(2000) 2914.
[2] T.Shiokawa, M. Muraguchi and K. shiraishi, Jpn. J.
Appl. Phys. 58 (2019) 112002.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Temperature dependence of liquid ethanol based on semiclassical Kramers-Heisenberg formulation
Ryosuke YAMAMURA, Kento AKIHIRO, Nozomu FUTAMATA, and Osamu
TAKAHASHI
Basic Chemistry Program, Graduate School of Advanced Science and Engineering,
Hiroshima University, Higashihiroshima, Hiroshima 739-8526, JapanThe hydrogen bonding in the condensed
phase

plays

a

important

role

in

the

understanding related liquid such as water andliquid alcohols. We have studied temperaturedependence of liquid ethanol using X-ray
emission spectroscopy (XES) theoretically andexperimentally. The approach of combining
theoreticalandexperimental

methodsis

Fig A: XES spectra based on

important for obtaining the hydrogen bonding

SCKH at 240K and 340K

information. The experimental XES warecarried out using the BL07SU HORNET station

extracted randomly. The number of snapshots

at SPring-8.

are 100 for each temperature. XES spectra canbe

In theoretical method, combining molecular

calculatedbyapplying

semi-classicaldensity

Kramers-Heisenberg (SCKH) formulation to thefunctional theory (DFT) calculations performed.

electronic state of each snapshots. Fig A shows

To construct structure of ethanol in liquid phase

the XES spectra based on SCKH. The calculatedclassical MD are adopted in the NVT ensemble

spectra well correspond to the experimental

at 240 K and 340K and 1 bar using GROMACS

spectra. Now, we analyze the MD snapshots and5.1.4 with OPLS force field. To calculate theinvestigate the relationship between XES

XES spectra, the DFT calculation performed

spectra and hydrogen bonding.

using deMon2K program package. The detail ofReferences

DFT calculation method are following the[1] M. P. Ljungberget, et al.: J. Chem. Phys. 146

previous studied for methanol [1] and ethanol(2017) 134596[2]. In short, the[2] O. Takahashi, et al.: J. Chem. Phys. B 49

dynamics

simulations

(MD)

and

17 ethanol cluster obtained(2017) 11163

from final snapshot of MD simulations are

179

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of analysis method for molecular crystal surface
using wave number space-resolved photoelectron spectroscopy
Kaori Niki
Graduate school of science
Chiba University, Yayoi-cho, Inage-ku, Chiba 263-0022
PTCDA does not contain transition elements, theBy using wave number space photoelectron
spectroscopy, it has become possible to obtain acalculation cost is low. Periodic DFT

photoelectron momentum maps (PMMS) of acalculations were carried out with VASP code

molecular thin film in a short time. This allowed

using the projector augmented wave (PAW)

us to obtain tomography of the wavefunction. It

method with a plane wave energy cutoff of 400

is suggested that more information can be[eV] and the PBE exchange-correlation

obtained by analyzing PMMS in detail. We havefunctional. The criterion convergence chosen forbeen analyzing the surface of molecular crystals

the SCF cycle was 10-8 eV, and optimization

with the aim of establishing a method for

were considered converged once theanalyzing momentum maps based on theforces on all atoms were lower than 10‐8 [eV/Å]

multiple scattering method. For the initial state,

The slab was 12.1 x 12.1 [Å] large, and 10 [Å]

we refer to the electronic state of the adsorption

thick (60 Ag atoms, 2PTCDA per unit cell)systeminitiowith a vacuum separation 20 [Å]. The three

Simulation Packge (VASP) [1,2]. So far, welowest layers were frozen during optimizations.

have suggested that by PMMS, it may be

The Brillouin zone was sampled with apossible to identify the adsorption position of

4x4x1 k-point grid. Electron occupancies

molecules adsorbed on the substrate surface [3].

were determined according to a Methfessel-

In 2020, we expanded the sample to a more

Paxton scheme (order1) with an energy

complex system. We placed VASP on thesmearing of 0.2[eV].

calculatedbyVienna Ab

As a result of structural optimization, PTCDASupercomputer of Institute for Solid State
Physics and performed two calculations.

was curved in an arc with respect to the surface.

1. Structural optimization and multiple

PMMS calculations (using our computer) were

scattering calculation of PTCDA / Ag (111).

performed using these coordinates. The PMMS

3,4,9,10-

has changed significantly compared to the

Perylenetetracarboxylic dianhydride (PTCDA)

results without the substrate. When I did thewas set to the Short-bridge site on Ag (111), andsame calculation on multiple sites, I found thatstructural optimization was performed. Since

PMMS was different for each site. This indicatesThe

initialpositionof180

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

based on the paper [5].

the possibility of obtaining information on theadsorption position from PMMS.

Figure 1 shows the temperature dependence

2. Structure optimization and multipleof energy. The horizontal axis is temperature,scattering calculation of CuPc and TiSe2

and the longitudinal axis is energy, white

In order to calculate the PMMS of Copper (Ⅱ)

triangles are the CDW layer, and black squares

phthalocyanine (CuPc) / TiSe2, the structure of

are the normal phase. From this calculation, it

CuPc and TiSe2 was optimized. First, we

was found that 200K at which the phase

performed structural optimization of CuPc.

transition occurs is approximately σ = 0.3. This

CuPc has a large number of constituent atoms

calculation provided us with a guideline to use σ

and contains transition elements with spin. The= 0.1 for low temperature calculations and σ =calculation cost is high and the calculation

0.4 for room temperature calculations in future.

method is complicated. Highest Occupied
Molecular Orbital (HOMO) -1 was not
calculated

in

the

correct position when

Generalized Gradient Approximation (GGA)
was used as a functional. It has been reported
that HOMO -1 can be calculated correctly using
the hybrid functional according to Heyd et al.
(HSE), but the calculation cost is high [4]. We

Figure 1. Energy dependence of sigma

also tried this, but couldn't succeed.

Using these calculation results obtained, we

Next, the structure of TiSe2 was optimized.

plan to calculate the structural optimization and

TiSe2 takes the CDW layer at low temperatureelectronic state of the adsorption system in 2021.

and undergoes a phase transition to the normal

References

phase at around 200 K [5]. To obtain information[1] G. Kresse, and J. Furthmuller: Phys. Rev. B,

about

54, (1996) 11169.

therelationshipbetweenσandtemperature during smearing, we calculated the[2]G. Kresse, and J. Hafner: Phys. Rev. B, 49

temperature dependence of the charge density(1994) 14251.

wave (CDW) structure and the normal phase.

layers of TiSe2. The calculation conditions are[3] K. Niki. M. Nozaki, S. Kurihara, and N.
Komiya: Vac. Surf. Sci. Jpn. 63 (2020) 336.
[4] K. Sch¨onauer et. al.: Phys. Rev. Lett. 94(2016) 205144.

the same as those described above. The normal[5] F.J. Di Salvo, D.E. Moncton, and J.V.

layer extended the (1x1) structure to (2x2). For

Waszczak: Phys. Rev. B: 14 (1976) 4321.

Structural optimization was performed for two

the CDW layer, the coordinates were entered181

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Analysis of local quantities of electron ﬁeld inmaterial surface
Masahiro FUKUDA
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

The local physical quantities, which is deﬁned in the framework of quantum ﬁeld theory (energy-momentum tensor density, current
density, chiral current density, and so on), aresigniﬁcant to understand physical or chemical
properties of surface materials, since it is noteasy to be explained by bulk feature in solids
such as a band structure.

ative stress as shown in Fig. 1 (d) reveals the“liquid” character of bulk metallicity. These
characterizations will help us to understandchemical bond formation between a material
surface and a molecular cluster deeply.

In the previous work, we developed a program code which enables us to calculate local physical quantities as a post-process calculation from OpenMX [1] (DFT calculation
program code) in order to evaluate the local
physical quantities in large periodic systems.
To proceed the discussion on a relation between the chemical bonding and the local electronic stress, recent research revealed the importance of evaluation of local physical quantities in a certain energy range. Therefore,
in this project, we developed a program code
which enables us to calculate local physicalquantities in a speciﬁed energy range or orbitals.
The physical and chemical nature aroundthe interaction region between atoms in
Ag(FCC) were investigated as a demonstration. In Fig. 1 (a), the positive stress (tensile stress) and the eigenvectors form the spindle structure [2], which visualize a covalentbonding state. On the other hands, in Fig. 1(b), the negative stress (compress stress) andthe eigenvectors form the anti-spindle structure [2], which visualize an anti-bonding state.
Moreover, the distribution of the isotropic neg-(a) DOS(b) −5eV < E < −4eV(c) −4eV < E < −3eV(d) −1eV < E < 1eV

Figure 1: (a) Density of state, (b)-(d) distributions of maximum eigenvalues and eigenvectors of the electronic stress tensor density ofAg(FCC).

References[1] OpenMX, http://www.openmx-square.org/.
[2] A. Tachibana, “New Aspects of Quantum
Electrodynamics”, Springer (2017)182

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.3

Strongly Correlated
Quantum Systems

183

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Machine learning and ab initio analysesof cuprate high-temperature superconductors
Masatoshi IMADA
Toyota Physical and Chemical Research Institute41-1 Yokomichi, Nagakute, Aichi, 480-1192
andResearch Institute for Sicence and Engineering, Waseda University
3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555
Understanding physics of high-Tc cuprate

spin liquids (QSL). It was achieved by using thesuperconductors remains one of the challenges

variational Monte Carlo tools (mVMC) [2]in physics. In this project, we have continued

combined

efforts to clarify physics and mechanism ofmachine developed by us [3,4], tensor network

high-temperature superconductivity, particularly[5,6] and the Lanczos diagonalization. In thefor the copper oxides.

This is a combined

J1J2 Heisenberg model defined on the 2D square

research activity of three different approaches:lattice with the nearest neighbor exchange(1) Parameter search of strongly correlated

interaction (J1) and the next nearest neighborelectron models by using high-accuracy solvers

exchangefor quantum many-body lattice Hamiltonians

established the existence of the QSL in the(2) Parameter-free ab initio studies of real

region 0.49<J2/J1<0.54 [7]. The analyses werematerials by using multi-scale ab initio scheme

elaborated by comparing the accuracy of ourfor correlated electrons (MACE) [1]solver with other tools in the literature. The(3) Data science approaches to expose hidden

accuracy and reliability of our solver were

physicalbyshown to be the best among existing solvers both

combining extended experimental data such as

for the ground states and the excitations. The

by angle resolved photoemission spectroscopy

reliability and robustness of the analyses was(ARPES), quasiparticle interference (QPI) by

confirmed by (i) the size insensitivity of thescanning tunnel microscope (STM) and resonant

correlation-ratio crossing points to identify theinelastic X-ray scattering (RIXS) with the help

QSL-antiferromagnetic transition and the QSLof applied mathematical and information science

totechnology such as machine-learning tools.

insensitivity about the choice of the initialquantities

andmechanisms

with

(J2),

the

we

valence-bond-solid

restrictedhaveBoltzmannfurthertransition

firmly(ii)

theIn the first approach, we have continued tovariational parameters for the wavefunction (iii)

clarify physics of electron fractionalization andbetter size extrapolation of the level crossing

formation of topological states such as quantum

point to infer the ground state phase boundary

184

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

from the level crossing points of the excitation

Accurate algorithms and tools for quantum

spectra, where larger size calculation has been

dynamics were also sought for [9]. A method to

added to enhance the accuracy of thecalculate spectral functions measurable by the

extrapolation.

ARPES representing the imaginary part of theWe have also been investigating the quantum
ground

state

of

the

Heisenberg

developed in addition to the two-particle

antiferromagnet on the pyrochlore lattice [8].

dynamical structure factor for spin and charge

After investigation of various trial wave

[10]. The application to the Hubbard model

functions, we find that the singlet ground state

revealed the d-wave gap structure for the firsthas a linear dispersion at vanishing momentum

time in the superconducting state as shown inwith a finite energy gap to triplet excitations.

Fig.1. It has shown an unrealistically large gap

Furthermore, it has turned out that the groundof the typical Hubbard model implying anstate is fully degenerate for all the point groupoversimplified nature of the Hubbard model as asymmetrymodel of the cuprate superconductors.

represented

S= 1/2electron single-particle Green’s function was

by

the

irreducible

symmetry group, which implies an emergence of

For the ab initio approaches (2), we havethe unprecedented type of quantum spin liquid.

reproduced the experimental phase diagram of
HgBa2CuO4+y [11] by solving its ab initio lowenergy effective Hamiltonian without adjustableparameters [12]. Thanks to this success, in thepresent project in 2020, more thorough andsystematic analyses for several different copperoxide compounds have started. Derivation of abinitio low-energy effective Hamiltonians for theseries of multi-layer compounds including Bi
and solving with refined mVMC tool is underway.
The third data science approach (3) has been
elaborated for the machine learning analysis of
the ARPES data. The comparison with theFig.1: Spectral function along around

literature has clarified the reliability of oursymmetry line. (f) is closest to theanalyses, which shows the emergence ofsymmetry line showing a large d-wave

prominent peak structures in the normal andgap at (π,0) [10].

anomalous parts of the self-energies and their

185

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

cancellation in the Green’s function resulting indoes not occur in the absence of thethe direct invisibility in ARPES, while thefractionalization, it can be used as the stringent

prominent peak is the origin of the hightest for the occurrence of the fractionalization.

temperature

The

This is a combined report for E project 2020-

accuracy and reliability of the present machine

Ea-0005 and 2020-Eb-0005 as well as sharedlearning method were confirmed by several

project for Fugaku project.

superconductivity[13].

This series of work has been done inbenchmark tests, which successfully reproduced

collaboration with T. Misawa, M. Hirayama, K.

the expected exact results and the established

Ido, Y. Nomura, Y. Yamaji, R. Pohle, M.

analyses in the literature. It further establishedCharlebois, J-B. Moree, F. Imoto, A. Fujimori

the robustness against unavoidable experimental

and T. Yoshida. The work is also supported bynoise and extrinsic contributions to spectral

JSPS Kakenhi 16H06345, the RIKEN Center for

functions such as background effects. The origin

Computational Science under the HPCI projectof the failure of previous studies which did not(hp200132) This project has used the software

find the prominent structure in the self-energies

HPhi, mVMC and RESPACK.

References

are exposed by faithfully following the[1] M. Imada and T. Miyake: J. Phys. Soc. Jpn. 79(2010) 112001[2] T. Misawa et al.: Comput. Phys.
Commun. 235 (2019) 447[3] Y. Nomura et al.: Phys. Rev. B.96 (2017)
205152[4] G. Carleo et al.: Nat. Commun. 9 (2018) 5322
[5] H.-H. Zhao et al.: Phys. Rev. B.96 (2017)085103[6] A. S. Darmawan et al.: Phys. Rev. B 98 (2018)
205132.
[7] Y. Nomura and M. Imada: arXiv:2005.14142.
[8] R. Pohle, Y. Yamaji and M. Imada: unpublished.
[9] M. Charlebois and M. Imada: Phys. Rev. X 10
(2020) 041023.
[10] K. Ido, M. Imada and T, Misawa: Phys. Rev.
B 101 (2020) 075124[11] T. Ohgoe et al., Phys. Rev. B 101 (2020)
045124.
[12] M. Hirayama et al.: Phys. Rev. B 99 (2019)245155.
[13] Y. Yamaji et al.: arXiv:1903.08060[14] M. Imada, arXiv:2103.10016.

assumptions by the previous studies and by
showing the error contained in the assumptions.
More thorough studies of the integrated
spectroscopy analysis have been conducted in
the combination of ARPES, and QPI or RIXS.
By using the ARPES data and their machinelearning analyses, a two-component fermion
model

is

constructedtorepresentthefractionalization of electrons supported by theprevious theoretical and experimental studies.
Then the two-component Hamiltonian was
analyzed to predict the RIXS data [14]. The
prediction shows a substantial enhancement of
the RIXS intensity in the superconducting phasein comparison to the normal phase, if theelectron fractionalization correctly describes thelowenergydynamics

ofthecupratesuperconductors. Since such an enhancement186

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical studies of quantum spin liquids byquantum mutual information
Youhei YAMAJI
GREEN, National Institute for Materials Science
Namiki, Tsukuba-shi, Ibaraki, 305-0044

Recent studies on quantum spin liquids(QSLs) revealed that a wide variety of the
QSLs is characterized by emergent fractionalized excitations and their topological nature,
instead of an absence of spontaneous symmetry breaking at zero temperature. Entanglement entropy has been proposed to distinguishtopologically trivial and non-trivial states. Although the entanglement entropy is hard tomeasure in experiments, it is applicable to any
many-body states.

the density matrix with a canonical thermal
pure quantum (cTPQ) state [1, 2] as, ρ̂pure =|Φ(β)ihΦ(β)|/hΦ(β)|Φ(β)i, where |Φ(β)i =e−β Ĥ/2 |Φ(0)i and |Φ(0)i is a normalized random vector. As emphasized in the literature,ρ̂pure is different from ρ̂: any integer power ofρ̂pure is equal to ρ̂ as E[ρ̂mpure ] = ρ̂, where E
is the average over distribution of the randomP
vector |Φ(0)i and Z(β) = n e−βEn . In contrast, the reduced ensity matrix constructedfrom ρ̂pure for the subsystem X (Y ), ρ̂X
pure
X/Y

Instead of the entanglement entropy, mutual
information (MI), a generalization of entanglement entropy, is useful at finite temperatures, where temperature scales characterizing
the fractionalization may emerge. The MI isgiven as relative entropy between the density
matrix and a product of reduced density matrices of a given system: When the system isdevided into two subsystems, X and Y , the MI 
I is given as I = tr ρ̂ ln ρ̂ − ln(ρ̂X ⊗ ρ̂Y ) ,where ρ̂ is the density matrix and ρ̂X (ρ̂Y ) is
the reduced density matrix for the subsystem
X (Y ) by taking a partial trace over the complementary subsystem Y (X).
Naively, the computational and memory
costs for I are higher than those for obtaining an eigenstate. However, typical state approaches enable us to estimate I with O(NH )computational and memory costs, where NH
is the Hilbert space dimension of the target
system, although the density matrix consisting of a typical pure state shows unphysical properties, as follows. When one define(ρ̂Ypure ), satsfies ρ̂X/Y = E[ρ̂pure ].
X/YBecause ρ̂pure and ρ̂ ln ρ̂ = −S(β), whereS(β) is entropy at inverse temperatures β, arecalculated by the cTPQ with O(NH ) computational and memory costs, ρ̂ ln(ρ̂X ⊗ ρ̂Y ) can
be calculated with the similar costs. Here, wenote that ρ̂ appears only once in ρ̂ ln(ρ̂X ⊗ ρ̂Y ).
The MI of an ab initio hamiltonian for Na2 IrO3
has been simulated and the temperature dependence will be published. The reduced density matrices are also useful to clarify thenature of correlated electrons such as hightemperature superconductivity [3].

References[1] S.Lloyd: arXiv:1307.0378; Ph.D. Thesis,
Rockefeller University (1988)[2] S. Sugiura and A. Shimizu: Phys. Rev.
Lett. 111 (2012) 010401.
[3] A. Iwano: master’s thesis, The Universityof Tokyo (2020).

187

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical studies of quantum spin liquid candidates
by highly accurate ab initio effective hamiltonians
Youhei YAMAJI
GREEN, National Institute for Materials Science
Namiki, Tsukuba-shi, Ibaraki, 305-0044

A Kitaev’s spin liquid candidate, α-RuCl3 ,has attracted considerable attention.
Although several studies on the effective hamiltonian of α-RuCl3 , there is no consensus on theeffective hamiltonian and no effective hamiltonian consistently explains experimentally observed specific heat and inelastic neutron scatterings. While these effective hamiltonians significantly deviate from the Kitaev model, theruthenium halide shows experimental signatures of Majorana excitations. To refine theeffective hamiltonian of the ruthenium halide
and to clarify whether the ruthenium halide isin the vicinity of the Kitaev model or not, wetheoretically study the series of the ruthenium
halides, α-RuH3 (H=Cl, Br, I).
Recent developments of deriving abinitio effective hamiltonians by using localized Wannier orbitals and constrained random phase or
GW approximations [1, 2] enables us to study
spin-orbit coupled Mott insulators and correlated (semi)metals. Regardless of the details ofthese methods, as the ionic radius of the halogen atom increases from Cl to I, the correlations in the ruthenium halides become weaker.
The detailed analyses on the effective abinitio
spin hamiltonians and itinerant electron hamiltonians are performed by using HΦ [3] andmVMC [4]. The spin hamiltonian seems to beinvalid for H =I and, at least, t2g hamiltonians
are required to describe the end member of theruthenium halides.
To characterize the excitation spectra of correlated electrons, we have also developed nu-

merical procedures to simulate abinitio spectral functions for the many-body Schrödinger
equation, instead of the effective lattice hamiltonians, by combining variational Monte Carlo
methods and Krylov subspace methods [5]. To
examine the applicability of the present algorithm, it is applied to the single particle spectral functions of liquid helium 3. The selfenergy is derived, which explicitly demonstrate
the strongly correlated nature of liquid helium
3 in an abinitio fashion.

References[1] M. Charlebois, J.-B. Morée, K. Nakamura, Y. Nomura, T. Tadano, Y. Yoshimoto, Y. Yamaji, T. Hasegawa, K. Matsuhira, M. Imada: arXiv:2103.09539.
[2] J.-B. Morée, S. Biermann, Y. Yamaji, and
M. Imada: unpublished.
[3] M. Kawamura, K. Yoshimi, T. Misawa,
Y. Yamaji, S. Todo, and N. Kawashima:
Compt. Phys. Communi. 217 (2017) 180.
[4] T. Misawa, S. Morita, K. Yoshimi, M.
Kawamura, Y. Motoyama, K. Ido, T. Ohgoe, M. Imada, and T. Kato: Compt.
Phys. Communi. 235 (2019) 447.
[5] N. Okada: Dynamical Variational Monte
Carlo Approaches for Excitation Spectraof Many-Body Fermions in Continuum
Space, master’s thesis, The University ofTokyo (2020).

188

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Systematic analysis of ab initio low-energy eﬀective Hamiltonians
for Pd(dmit)2 molecular conductors
Takahiro Misawa
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

Quantum spin liquids, which do not show
any symmetry breaking even at zero temperature, have attracted much interest since theirelementary excitations in the quantum spin liquids are expected to show exotic elementary
excitations such as Majorana particles. Because the exotic elementary excitations may
be useful for next-generation devices such as
quantum computers, a huge amount of works
on searching and identifying the quantum spin
liquids in solids has been done in a decade.

software package RESPACK [5, 6], we evaluate the transfer integrals and two-body interactions such as the Coulomb interactions. As
a result, we have found that the anisotropy of
the transfer integrals and correlations eﬀects
systematically change by changing cations.

Among several candidates of the quantum spin liquids, the molecular solids β ′ X[Pd(dmit)2 ]2 (X represents a cation) oﬀers
an ideal platform for realizing the quantum
spin liquid induced by the geometrical frustration in the magnetic interactions because
the geometrical frustration can be systematically controlled by changing cations X. In experiments, it has been proposed that the Neeltemperatures are systematically controlled bychanging cations X and the quantum spin liquid realizes in X =EtMe3 Sb [1, 2].

Moreover, we have analyzed the low-energy
eﬀective Hamiltonians using the exact diagonalization method [7, 8]. From the numerical exact analyzes of the low-energy eﬀective Hamiltonians, we have shown the significant reduction of the antiferromagnetic ordered moment occurs around X =EtMe3 Sb.
This reduction is consistent with the experimentally observed quantum spin liquid behavior in X=EtMe3 Sb. We have also shown thatthe reduction is induced by both the geometrical frustration in the hopping integrals andoﬀ-site Coulomb interactions. This result indicates that accurate evaluation of the microscopic parameters in the Hamiltonians is essential for reproducing the quantum spin liquidbehavior in the dmit-salts.

In this project, to identify the microscopic
origin of the quantum spin liquid found in
X =EtMe3 Sb, we have performed systematicand comprehensive ab initio derivations of lowenergy eﬀective Hamiltonians for available 9
compounds of β ′ -X[Pd(dmit)2 ]2 (X = Me4 Y ,EtMe3 Y , Et2 Me2 Y and , Y = As, Sb, andP) [3]. In the derivation the low-energy eﬀective Hamiltonians, we ﬁrst obtain the global
band structure for dmit-salts using Quantum
ESPRESSO [4]. Then, using the open-source

In addition to the ab initio study for thedmit-salts, we have also analyzed the longrange spin transport in the topological Diracsemimetals [9] using the real-time evolutionof the quantum systems. Furthermore, usingHΦ [7, 8], we have analyzed the magnetization process of the antiferromagnetic Heisenberg model on the kagome lattice [10]. We
have also developed an open-source library forthe shifted Krylov subspace method (Kω) [11]and an Ab initio tool for derivation of eﬀective

189

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

low-energy model for solids (RESPACK) [5, 6].

References[1] R. Kato, Chem. Rev. 104, 5319 (2004).
[2] K. Kanoda, R. Kato, Annu. Rev. Condens. Matter Phys. 2, 167 (2011).
[3] T. Misawa, K. Yoshimi, T. Tsumuraya,
Phys. Rev. Research 2, 032072 (2020).
[4] P. Giannozzi, O. Andreussi, T. Brumme,
O. Bunau, M. B. Nardelli, M. Calandra,
R. Car, C. Cavazzoni, D. Ceresoli, M. Cococcioni, et al., Journal of Physics: Condensed Matter 29, 465901 (2017).
[5] https://sites.google.com/view/kazuma7k6r[6] K. Nakamura, Y. Yoshimoto, Y. Nomura,T. Tadano, M. Kawamura, T. Kosugi,
K. Yoshimi, T. Misawa, Y. Motoyama,Computer Physics Communications 261,
107781 (2021).
[7] M. Kawamura, K. Yoshimi, T. Misawa,
Y. Yamaji, S. Todo, N. Kawashima, Comput. Phys. Commun. 217, 180 (2017).
[8] https://www.pasums.issp.u-tokyo.
ac.jp/HPhi/en/[9] Y. Araki, T. Misawa,
arXiv:2103.06519.

K. Nomura,[10] T. Misawa, Y. Motoyama, Y. Yamaji,
Phys. Rev. B 102, 094419 (2020).
[11] T. Hoshi, M. Kawamura, K. Yoshimi,
Y. Motoyama, T. Misawa, Y. Yamaji,
S. Todo, N. Kawashima, T. Sogabe,
Computer Physics Communications 258,
107536 (2021).

190

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study of phase formation, transport phenomena and effects ofexceptional points in strongly correlated quantum systems
Norio KAWAKAMI
Department of Physics,
Kyoto University, Kitashirakawa, Sakyo-ku, Kyoto 606-8502
equilibrium approaches.[1]We have studied phase formation andtransport phenomena in strongly correlated(2) Non-Hermitian phenomena

quantum systems. Especially, we have focused

Quasiparticles

on phenomena such as the formation ofwithfinitetheirlifetimesThis

non-Hermitian

provided a concise review of the non-Hermitian
topological band structures for quantum many-

We have discussed the circumstances andbody systems in equilibrium as well as theirrequirements for the emergence of non-classification.[2]Hermitian phenomena in equilibrium singleparticle properties of strongly correlated systems
relationshiplifetime.

new insights into correlated systems. We(1) Open quantum systems

theirfiniteperspective on equilibrium systems provides

becomes essential.

andGreen's

Hermitian topological phenomena because ofpoints when the non-Hermitian aspect of
bands

by

functions of equilibrium systems exhibit non-magnetic phases and the effect of exceptional
quasiparticle

described

to

Non-Hermitian phenomena offer a novel

non-Hermitian

approach to analyze and interpret spectra in thephenomena in open quantum systems (OQS)

presence of interactions. Using the density-

experiencing gain and loss. While the necessity

matrix renormalization group (DMRG), weof postselection has limited the practicality ofdemonstrated the existence of exceptional points

studying non-Hermitian phenomena in the OQS,

for the one-particle Green's function of the 1D

in closed equilibrium systems, the single-

alternating Hubbard chain with chiral symmetry,particle Green's function is described by anwith a corresponding Fermi arc at zero

effective non-Hermitian Hamiltonian without

frequency in the spectrum. They are robust andthe need of postselection. By describing

can be topologically characterized by the zeroth

quasiparticles of strongly correlated systems as

Chern number. This effect illustrates a casean OQS, we demonstrated that the non-where the temperature has a strong impact in 1D

Hermitian Hamiltonian arising in OQS andbeyond the simple broadening of spectral

Green’s functions are equivalent. We have also

features. Furthermore, we demonstrated that

demonstrated the necessity of considering theexceptional points appear even in the two-memory effect in the quantum master equation

particle Green's function (charge structure

by comparing the spectral function in thefactor), where an effective Hamiltonian is

Hubbard model computed by an OQS anddifficult to establish.[3]191

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo(3) Two-dimensional materials
Themagnetic

phosphorene

for device applications.[5]properties

nanoribbons

of

black

have

been

(4) Many-body localization
Strong disorder in low-dimensional strongly

investigated using static and dynamical mean-

correlated systems has been discussed to induce

field theory. Besides confirming the existence offerromagnetic/antiferromagnetic

many-body

edge

the

to precisely determine the critical strength ofinteraction strength to a novel incommensurate

disorder at the localization phase transition inmagnetic phase. Furthermore, we demonstrated

one or higher spatial dimensions. We havethat the difference of the ground state energies ofconsidered the Fock-space localization of many-

the AFM and FM phase is exponentially small,body wavefunctions in an all-to-all interacting

making it possible to switch between both states

modelby a small external field.[4]offermions

anddemonstratedaquantitative agreement of the numericallyspin-dependentobtained moments of eigenstate wavefunctions

thermoelectric effect of graphene flakes with

as well as the spectral statistics to analyticalmagnetic

regime.

predictions.[6]Employing static and dynamical mean-field

References

edges

the

is

Hamiltonian. However, it has been an open issue

unit-cells find a phase transition at weak

investigatedwhich

localization of all many-body eigenstates of themagnetism, our detailed calculations using large

We

localization,in theballistic

theory, we first showed that magnetism appears[1] Y. Michishita, and R. Peters, Phys. Rev. Lett.

at the zigzag edges for a window of Coulombinteractions that increases significantly with

124, 196401 (2020).

increasing flake size. We then used the Landauer[2] T. Yoshida, R. Peters, N. Kawakami, and Y.

formalism in the framework of the non-

Hatsugai, Prog. Theor. Exp. Phys. 12A109

equilibrium

Green'sfunction

methodto(2020).

calculate the spin and charge currents in[3] R. Rausch, R. Peters, and T. Yoshida, New J.

magnetic hexagonal graphene flakes by varying
the temperature of the junction for different flake

Phys. 23, 013001 (2021).

sizes. While in non-magnetic gated graphene,[4] J. Vahedi and R. Peters, Phys. Rev. B 103,

the temperature gradient drives a charge current,

075108 (2021).

we observe a significant spin current for[5] T. T. Phung, R. Peters, A. Honecker, G. T. dehexagonal graphene flakes with magnetic zigzag
edges. Specifically, we showed that in the

Laissardiere, and J. Vahedi, Phys. Rev. B 102,

"meta" configuration of a hexagonal flake

035160 (2020).

subject to weak Coulomb interactions, a pure[6] F. Monteiro, T. Micklitz, M. Tezuka, and A.

spin current can be driven just by a temperature

Altland, Phys. Rev. Research 3, 013023 (2021).

gradient in a temperature range that is promising192

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical study of correlated electron systems
with strong spin-orbit coupling
Yukitoshi MOTOME
Department of Applied Physics,
The University of Tokyo, Bunkyo, Tokyo 113-8656
We have theoretically studied a variety of

relevant mechanism to understand recent new

intriguing phenomena in correlated electron

generation of the topological spin crystals [9].

systems with spin-orbit coupling, ranging from(ii) Kitaev quantum spin liquids: By using theMott insulators to metals. During the last fiscal

quantum Monte Carlo simulation in theyear, we have achieved substantial progress on

Majorana

the following topics (project numbers: 2020-

investigated the effect of randomness on the

Ca-0059 and 2020-Cb-0038). We summarize

Kitaev model for the thermodynamics andthe main results below.

thermal transport [10] and the spin dynamics(i) Topological spin crystals: We clarified that[11]. We also studied the finite-temperatureinterplay between spin, charge, and orbital

phase transitions in a variety of three-degrees of freedom plays a crucial role indimensional extensions of the Kitaev model

stabilizing the magnetic hedgehog crystals[12]. In addition, by using ab initio based

recently found in B20 chiral magnets [1]. We

calculations, we performed a systematic study

also showed that the spin-charge interplay givesof Pr-based f-electron compounds as new

rise to a square-lattice type skyrmion crystals

Kitaev candidates [13]. Summarizing our recent[2]. Based on the results, we made astudies of the physics of Kitaev spin liquids andcollaboration with the experimental group to

the material design of the Kitaev magnets, weclarify the importance of the spin-charge

wrote two review papers [14,15].

coupling in GdRu2Si2 hosting the square(iii) Spin-orbit physics not requiring the spin-

skyrmion crystal [3,4]. We also studied theorbit coupling: We showed that κ-type organic

effect of anisotropy in a triangular lattice

antiferromagnets exhibit an anomalous Hall

system [5]. In addition, we investigated the

response because of an effective spin-orbit

effects of the spatial anisotropy [6], the phase

coupling generated by glide symmetry breaking

shift [7], and the twist angle [8] on theby the antiferromagnetic order [16]. We also

topological spin crystals. We wrote a review

showed that a similar mechanism predicts apaper on the itinerant frustration which is aspin current generation in perovskites with the193

fermionrepresentation,

weActivity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

C-type antiferromagnetic order [17].

(arXiv:2103.10647).

(iii) Multipole physics: We proposed channel-[10] J. Nasu and Y. Motome, Phys. Rev. B 102,

selective non-Fermi liquid behavior in the two-

054437 (2020).

channel Kondo lattice model under a magnetic[11] J. Nasu and Y. Motome, preprint

field [18]. We also clarified optical Hall

(arXiv:2103.10549).

responses in spin-orbit coupled metals with

[12] T. Eschmann, P. A. Mishchenko, K.

magnetic cluster multipole orders [19].

O'Brien, T. A. Bojesen, Y. Kato, M. Hermanns,(iv) Collaboration with experimental groups: In

Y. Motome, and S. Trebst, Phys. Rev. B 102,

addition to [3,4], we made combined studies

075125 (2020).

between our theory based on the ab initio[13] S.-H. Jang, R. Sano, Y. Kato, and Y.

calculations and experiment on topologicalMotome, Phys. Rev. Materials 4, 104420

materials [20,21].

(2020).
[14] Y. Motome, R. Sano, S.-H. Jang, Y. Sugita,

References

and Y. Kato, J. Phys: Condens. Matter 32,[1] S. Okumura, S. Hayami, Y. Kato, and Y.

404001 (2020), [Special Issue on QuantumMotome, Phys. Rev. B 101, 144416 (2020).

Spin Liquids].

[2] S. Hayami and Y. Motome, Phys. Rev.

[15] 求 幸年，那須 譲治, 固体物理 55, 297

B 103, 024439 (2021).

(2020).

[3] Y. Yasui et al., Nat. Commun. 11, 5925

[16] M. Naka, S. Hayami, H. Kusunose, Y.

(2020).

Yanagi, Y. Motome, and H. Seo, Phys. Rev.

[4] 東京大学大学院工学系研究科 プレスリリ

B 102, 075112 (2020).

ース, "電荷密度波で電子構造の「ねじれ」をス[17] M. Naka, Y. Motome, and H. Seo, Phys.

イッチする −トポロジカル状態の高速制御に向Rev. B 103, 125114 (2021).

けた新しい指針を開拓−".

[18] K. Inui and Y. Motome, Phys. Rev. B 102,

[5] S. Hayami and Y. Motome, Phys. Rev.

155126 (2020).

B 103, 054422 (2021).

[19] T. Sato, Y. Umimoto, Y. Sugita, Y. Kato,[6] K. Shimizu, S. Okumura, Y. Kato, and Y.

and Y. Motome, Phys. Rev. B 103, 054416

Motome, Phys. Rev. B 103, 054427 (2021).

(2021).

[7] S. Hayami, T. Okubo, and Y. Motome,[20] N. Mitsuishi et al., Nat. Commun. 11,

preprint (arXiv:2005.03168).

2466 (2020) [selected as FOCUS].

[8] K. Shimizu, S. Okumura, Y. Kato, and Y.

[21] M. Onga et al., Nano Letters 20, 4625

Motome, preprint (arXiv:2009.14569).

(2020).

[9] S. Hayami and Y. Motome, preprint

194

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study on newly discovered nickelate superconductivity
Yusuke NOMURA
RIKEN Center for Emergent Matter Science, 2-1 Hirosawa, Wako, 351-0198
Hubbard-type material) and cuprates (charge-

The recent discovery of superconductivity

transfer-type material).

in the doped nickelate Nd0.8Sr0.2NiO2 has
attracted much attention because the nickelates(B) Then, it is of great interest to investigate

may serve as a cuprate analog superconductor

the strength of magnetic exchange coupling J in[1]. Indeed, the electronic structure of thethe d9 nickelates. Note that a large value of J of

nickelate is similar to that of the cuprates in theabout 130 meV is a characteristic feature of thesense that the strongly correlated x2−y2 orbital

cuprates. We study the J value in theoretically-is present. However, as a crucial difference

designed RbCa2NiO3 and A2NiO2Br2 (A: afrom the cuprates, which shows Mott insulating

cation with the valence of +2.5) (Fig. 1). We

behavior, RNiO2 (R=Nd, Pr) is not a Mott

show that these nickelates have a sizeable

insulator due to the carrier doping from themagnetic exchange coupling as large as about

rare-earth layer (self-doping) [2].

80-100 meV, which is not far smaller than thatof the cuprates [4].

In the present study, we investigate thefollowing fundamental questions: (A) Is it
possible to design nickelates whose electronic
structure is more similar to that of the cuprates?
(B) Can we expect large magnetic exchange
coupling J in the cuprate-analog nickelates?
For (A), using a concept of “block layers”,
we perform a systematic materials design oflayered nickelates. Then, we find several
dynamically stable cuprate-analog nickelates[3]. In such nickelates, the self-doping is absent,
and hence the x2−y2 orbital becomes half-filled.
Therefore, the correlation effect will induce

Fig. 1: Crystal structure of RbCa2NiO3 andMott insulating behavior in such d9 nickelates.

A2NiO2Br2 (A: a cation with the valence of +2.5).

Using the d9 nickelates, we can perform a faircomparison between the nickelates (Mott-

195

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

References[1] D. Li et al., Nature 572, 624 (2019)[2] Y. Nomura et al., Phys. Rev. B 100, 205138(2019) [Editor's suggestion][3] M. Hirayama and T. Tadano et al., Phys.
Rev. B 101, 075107 (2020)[4] Y. Nomura et al., Phys. Rev. Research 2,
043144 (2020).

196

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Studies on superconductivity in multiorbital systems with an incipient bandand designing of new nickelate superconductors
KAZUHIKO KUROKI
Department of Physics, Osaka University
1-1 Machikaneyama, Toyonaka, Osaka, 560-0043, Japan

SUPERCONDUCTING MECHANISM OF A
NEW CUPRATE SUPERCONDUCTOR
BA2 CUO3+δ

Recently, Li et al.[1] reported high-Tc superconductivity in a new cuprate Ba2 CuO3+δ witha K2 NiF4 -like layered structure. There, they ﬁnd
several unique features which strongly suggest thatthe material is a diﬀerent type of cuprate superconductor that opens up a new paradigm. Namely,a large amount of oxygen vacancies are present
within the CuO2 planes, and a great amount ofholes are doped which should cause a large deviation of the Cu valence from 2+. Also, the distance
between Cu and the apical O is shorter than thein-plane Cu-O distance, so that the octahedron iscompressed along the c axis. This should result ina crystal ﬁeld very diﬀerent from that of the ordinary cuprates, namely, the 3d3z2 −r2 orbital lifted inenergy above the 3dx2 −y2 orbital. These ﬁndings
suggest that the mechanism of superconductivity
in the Ba2 CuO3+δ may be considerably diﬀerent
from that for the conventional cuprates.
In 2020 ﬁscal year, we have studied possible superconducting mechanisms of Ba2 CuO3+δ [2]. In
order to study the superconducting mechanism of
the new superconductor, a realistic model Hamiltonian is required, which has to start with a determination of the crystal structure. For the 2-1-3 composition in particular, the chain structure is known
to be stable in an actual material Sr2 CuO3 . As another possibility within the 2-1-3 composition, we
considered a Lieb lattice type structure. First principles total-energy calculation performed with the
VASP code shows that the chain and the Lieb lattice structures are close in the total energy, so thatthe latter may also be considered as a candidate.
Focusing on these two structures, we have calculated their band structures, and extracted theWannier orbitals to construct multiorbital Hubbard models, i.e, a two-orbital model for the chain
structure and a six-orbital model for the Lieb typestructure. We have applied ﬂuctuation exchange
approximation to the eﬀective models, and discuss
the possibility of superconductivity by solving thelinearized Eliashberg equation. We have shownthat s-wave and d-wave pairings closely competewith each other and, more interestingly, that a coexistence of intra- and interorbital pairings arises.

197

We also reveal an intriguing relation of the Liebmodel with the two-orbital model for the usual
K2 NiF4 -type cuprate where a close competition between s- and d-wave pairings is known to occur.
We have further shown that s±-wave superconductivity is strongly enhanced when the d3z2 −r2band is raised in energy so that it become nearly
incipient with the lower edge of the band close
to the Fermi level within a realistic band ﬁlling
regime. The enhanced superconductivity in thepresent model is in fact shown to be related to an
enhancement found previously in the bilayer Hubbard model with an incipient band. Namely, we
can show that, by orbital basis transformation[3],the two-orbital model can be transformed to the bilayer Hubbard model when all the intra and interorbital interactions have the same magnitude. In
reality, the interactions are diﬀerent in magnitude,
but we ﬁnd that the similarity between the twomodels holds to some extent. The strong enhancement of s±-wave superconductivity in the bilayer
model with an incipient band has been shown by
a number of previous studies, including our numerical study[4] based on multi-variable variational
Monte Carlo method[5, 6].

DESIGNING NICKELATESUPERCONDUCTORS

Inspired by the proposed superconducting mechanism for Ba2 CuO3+δ , in 2020 ﬁscal year,
we have also theoretically designed unconventional nickelate superconductors with d8 electron
conﬁguration[7]. Although the materials that wedesign apparently have nothing to do with bilayer
systems at ﬁrst glance, electronic structure of thesematerials resemble that of the bilayer Hubbard
model, thereby strongly enhancing superconductivity. It is known that bilayer Hubbard model withappropriately large interlayer electron hopping exhibits s±-wave superconductivity with extremely
high-Tc , but it is generally diﬃcult to realize sucha situation in actual bilayer-type materials due tovarious restrictions regarding the atomic orbitals.
We have adopted a completely diﬀerent strategy torealize the desired situation, by which we design amixed-anion nickelates as candidates for new highTc superconductors.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo2
mately equivalent to large interlayer hopping in abilayer system, as schematically depicted in Fig.2.
Applying the ﬂuctuation exchange approximation
to the ﬁve orbital model of these materials, we haveshown that the maximum superconducting transition temperature of some of them may be evenhigher than that of the high-Tc cuprates.
FIG. 1.
Band structures of (a) La2 NiO4 , (b)Ca2 NiO2 Cl2 and (c) (b) Ca2 NiO2 H2 (taken from
Ref.[7]).
two-orbital

bilayerorbital-1

antibonding

EF

DE

EF

orbital-22t⊥bonding

FIG. 2. Schematic figure of the correspondence between
the two-orbital model and the bilayer model (takenfrom Ref.[7]).

8More speciﬁcally, we have considered d nickelates with K2 NiF4 structure, where the apical oxygens are replaced by halogens or hydrogens. The
lattice parameters are determined by structural optimization using VASP. The The band structures of
two of the proposed candidates, Ca2 NiO2 Cl2 and
Ca2 NiO2 H2 , are shown in Fig.1 together with thatof a reference material La2 NiO4 . The key point
here is that the large crystal ﬁeld splitting of theorbital energy levels, induced by replacing the apical oxygens by halogens or hydrogens, is approxi-

198

We have further found that our theory may also
be related to another newly discovered superconductor (Nd,Sr)NiO2 [8]. In this superconductor, thenickel electron conﬁguration is expected to be close
to d9 , but this might be aﬀected, e.g., by the reduction process during the synthesis of the material. Since the band structure of (Nd,Sr)NiO2 itself, due to the absence of apical oxygens, resembles that of the proposed mixed anion-nickelates,(unintentional) reduction of the electron number in(Nd,Sr)NiO2 may also result in a similar s±-wave
superconductivity.

[1] W.M. Li et al., Proc. Natl. Acad. Sci. USA 116,
12156 (2019).
[2] K. Yamazaki et al. Phys. Rev. Res. 2, 033356(2020).
[3] H. Shinaoka et al., Phys. Rev. B 92, 195126 (2015).
[4] D. Kato and K. Kuroki, Phys. Rev. Res. 2, 023156(2020).
[5] D. Tahara and M. Imada, J. Phys. Soc. Jpn. 77,
114701 (2008).
[6] T. Misawa et al., Comp. Phys. Comm. 235, 447(2019).
[7] N. Kitamine, M. Ochi and K. Kuroki, Phys. Rev.
Res. 2, 042032(R).
[8] D. Li et al., Nature (London) 572, 624 (2019).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Bulk-edge correspondence for non-Hermitian
topological systems
Tsuneya Yoshida
Department of Physics,
1-1-1 Tennodai, Tsukuba, Ibaraki, JAPAN 305-8571
In this year, we have studied topologicalphases in non-Hermitian systems [1-6].
In particular, by employing numerical
diagonalizationofmatrix,

have

we

a

non-Hermitianelucidatedthetopological properties of non-Hermitian
fractional quantum Hall state [1].

Fig.1 Spectrum of the Liouvillian matrix

Specifically, we have analyzed a two-describing fractional non-Hermitian quantum

dimensional open quantum system with- Hall states.

two-body loss. Such a system is described

dimensions and symmetry, e.g., one

by Lindblad equation. Vectorizing thedimensional open quantum systems withdensity matrix, we have mapped theinversion symmetry.

Liouvillian to the Liouvillian matrix.

We have also analyzed classical systems

Diagonalizing
analyzed

thismatrix,

topological

we

have

in term of topological band theory[7-9].

properties.

Our

Our

analysishave

elucidated

that

analysis elucidate that for a system with

topological phenomena are observed a

two-body

variety of systems beyond quantum

loss,

the

Liouvilliangapremains open (see Fig. 1). In addition,
introducing
number,we

topologyofthepseudo-spin

haveelucidated

systems.

Chern

References

thatfractional[1] T. Yoshida, K. Kudo, H. Katsura, andquantum Hall states is maintained for

Y. Hatsugai, Phys. Rev. Research 2

this open quantum systems.

033428 (2020)

Our approach of the characterization[2] T. Yoshida, Phys. Rev. B 103 125145

can be also generalized to other cases of(2021).

non-Hermitian

199

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo[3] H. Araki, T. Yoshida, and Y. Hatsugai,(2020).

J. Phys. Soc. Jpn. 90 053703 (2021).

[7] T. Yoshida, T. Mizoguchi, and Y.

[4] P. Delplace, T. Yoshida, Y. Hatsugai,

Hatsugai arXiv:2012.05562.

arXiv: 2103.08232.

[8] T. Yoshida, T. Mizoguchi, Y. Kuno and[5] R. Rausch, R. Peters, and T. Yoshida,

Y. Hatsugai arXiv: 2103.11305

New J. Phys. 23 013011 (2021).

[9] T. Yoshida and Y. Hatsugai, Sci. Rep.

[6] T. Yoshida, T. Mizoguchi, and Y.

11 888 (2021).

Hatsugai Phys. Rev. Research 2 022062.

200

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical analyses on quantum spin liquids in strongly
correlated electron systems
Kota IDO
Institute for Solid State Physics,
The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581
β’- Pd(dmit)2 salts have attracted attention

find that the energy of quantum spin liquids

as candidate materials where a quantum spinusing our proposed wavefunction is much

liquid emerges [1]. This system consists of thelower than those using the conventional pairing

dimers of two Pd(dmit)2 molecules and cations.

wavefunction. In addition, we performed

Since the dimers form an anisotropic triangularvariance extrapolations of energies by using thelattice, this system is considered as a two-

power Lanczos method [4]. As the results, we

dimensional correlated electron system withsucceed in reproducing the stability of thestrongAlthoughquantum spin liquid obtained by using thenumerical studies play an important role in

fixed-node method [5]. Our results suggest thatinterpretingthethis approach is a new efficient way to analyze

candidate materials for quantum spin liquids, it

the ground state in strongly correlated electron

is difficult to accurately analyze large two-systems with the geometrical frustration and todimensional systems with strong frustration andclarify the nature of the spin liquids.

geometricalfrustration.

experimental

resultsinmany-body correlations.

In addition, we have analyzed the groundIn this study, to perform the ground state

states of an extended Kitaev model using theanalysis on strongly correlated electron systems

VMC method. It is a future issue to study notwith geometrical frustration, we improved theonly the ground states but also nonequilibrium

accuracy of the trial wavefunction of thephenomena in quantum spin liquids.

variational Monte Carlo (VMC) method. To
achieve this goal, we proposed a two-

Referencescomponent[1] K. Kanoda, R. Kato, Annu. Rev. Condens.

pairing

wavefunction

as

the

fermionic wavefunction. The difference from

Matter Phys. 2, 167 (2011).

the conventional pairing wavefunction is that[2] G. Carleo and M. Troyer, Science 355, 602

the strength of the pairing is dependent on the(2017).

number of the local density. By using this[3] Y. Nomura, A. S. Darmawan, Y. Yamaji, andwavefunction

recently

M. Imada, Phys. Rev. B 96, 205152 (2017).

developed neural network correlators [2, 3], we[4] E. S. Heeb, T. M. Rice, Z. Phys. B 90, 73

performed benchmarks for the t-t’ Hubbard(1993).

model on the square lattice and the triangular[5] L. F. Tocchio, A. Parola, C. Gros, and F.

lattice with one-dimensional anisotropy. We

Becca, Phys. Rev. B 80, 064419 (2009).

combined

with

201

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Search for multiple-Q magnetic orders in systems
with bond-dependent anisotropic interactions
Satoru Hayami
Department of Applied Physics, The University of Tokyo, Tokyo 113-8656

Noncoplanar spin textures have attracted
considerable attention for potential applications to next-generation electronic and spintronic devices. In the project with numbers:
2020-Ca-0002 and 2020-Cb-0005, we have theoretically investigated a plethora of noncoplanar spin textures in correlated electron systems. We have presented the main results thisyear below.
(i) Magnetic hedgehog lattice: A magnetic
hedgehog lattice (HL), which is characterized
by a periodic array of magnetic monopoles
and antimonopoles, is one of the noncoplanar multiple-Q states in the three-dimensionallattice system. The emergence of the HLs
has been suggested in the noncentrosymmetricmetal MnSi1−x Gex [1, 2] by experiments, but
their microscopic origins have not been fully
clarified owing to the unconventional shortmagnetic periods of the spin textures. We haveinvestigated the stability of the HLs by analyzing an eﬀective spin model derived from anitinerant electron model [3]. By using the variational calculations and simulated annealing,
we obtained two types of HLs in the wide rangeof model parameters in the ground-state phase
diagram. The results indicate the importanceof the interplay between the DzyaloshinskiiMoriya(DM)-type interaction by the spin-orbit
coupling and the multiple-spin interactions by
the spin-charge coupling.
(ii) Square skyrmion crystal: We have studied an instability toward a square skyrmion
crystal (SkX), which consists of two helices with equal weight, in a centrosym-

202

metric tetragonal lattice system [4].
We
considered an eﬀective spin model from anitinerant electron model on a square lattice. Reflecting the itinerant nature of electrons, the spin model exhibits the bilinear and biquadratic interactions in momentum space [5]. We also introduced fourfoldsymmetric bond-dependent anisotropic andeasy-axis anisotropic interactions to stabilize
the multiple-Q states. By performing simulated annealing, we have shown that the square
SkX appears by the synergy eﬀect among thebiquadratic, bond-dependent anisotropic, andeasy-axis anisotropic interactions in an external magnetic field. We have also shown thatthe magnetic phase diagram obtained by simulated annealing well reproduces the experimental results for the SkX hosting material
GdRu2 Si2 [6, 7].
In addition, we have investigated the vorticity and helicity of the square SkX in centrosymmetric itinerant magnets. Owing to theabsence of the DM interaction in centrosymmetric magnets, the vorticity and helicity of
the SkX are arbitrary. In other words, theNéel SkX, Bloch SkX, and two anti-SkXs aredegenerate. In such a situation, we foundthat the anisotropic Ruderman-Kittel-KasuyaYosida (RKKY) interaction depending on the
wave vectors lift the degeneracy of the SkXs
with the diﬀerent vorticity and helicity [8].
Our result opens a possibility of controlling thetypes of the SkXs through the electronic band
structures.
(iii) Triangular skyrmion and meron crys-

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

tals: We have studied the SkXs and meron
crystals in itinerant hexagonal magnets [9].
On the basis of the eﬀective spin model withthe bilinear and biquadratic interactions in
momentum space [5], we examined the eﬀectof two magnetic anisotropies on the stabilityof the multiple-Q states: The one is the local single-ion anisotropy and the other is the
sixfold-symmetric bond-dependent anisotropy.
In the case the single-ion anisotropy, we foundthat both the SkXs with the skyrmion number of one and two, which are denoted as thensk = 1 SkX and nsk = 2 SkX, appear under the single-ion anisotropy, although theirstability against the single-ion anisotropy is
diﬀerent with each other. For the nsk = 2
SkX, it is found that the stable region underthe easy-axis anisotropy is wider than that for
the easy-plane anisotropy at zero field. Meanwhile, the critical magnetic field to destabilize the nsk = 2 SkX is larger for the easyplane anisotropy than that for the easy-axis
anisotropy. For the nsk = 1 SkX, there is a
drastic eﬀect of the single-ion anisotropy on its
stability; the nsk = 1 SkX is very weak (strong)against the easy-plane(-axis) anisotropy.
Under the bond-dependent anisotropy, we
also obtained both the nsk = 1 and nsk = 2
SkXs in the wide range of model parameters.
Notably, we found a variety of chiral magnetic
states with nonzero scalar chirality, which isdistinct from the SkXs. Especially, we obtained two types of the meron crystals: One
is the nsk = 1 meron crystal, which consists ofone meron-like and three antimerion-like spin
textures in the magnetic unit cell and the otheris the nsk = 2 meron crystal consisting of fourmeron-like spin textures in the magnetic unitcell.
The eﬀective spin model in itinerant magnets will provide a deep understanding of themechanism of the multiple-Q states, whichhave been recently observed in experiments, inan eﬃcient way. Indeed, we reproduced themagnetic phase diagrams in Gd3 Ru4 Al12 [10]203

and CeAuSb2 [11], which host the multiple-Q
states, by analyzing the extended eﬀective spinmodel.

References[1] T. Tanigaki et al., Nano Lett. 15 (2015)5438.
[2] Y. Fujishiro et al., Nat. Commun. 10(2019) 1059.
[3] S. Okumura, S. Hayami, Y. Kato, and
Y. Motome, Phys. Rev. B 101 (2020)
144416.
[4] S. Hayami and Y. Motome, Phys. Rev. B
103 (2021) 024439.
[5] S. Hayami, R. Ozawa, and Y. Motome,
Phys. Rev. B 95 (2017) 224424.
[6] N. D. Khanh et al., Nat. Nanotech. 15(2020) 444.
[7] Y. Yasui et al., Nat. Commun. 11 (2020)
5925.
[8] S. Hayami and R. Yambe, J. Phys. Soc.
Jpn. 89 (2020) 103702.
[9] S. Hayami and Y. Motome, Phys. Rev. B
103 (2021) 054422.
[10] M. Hirschberger, S. Hayami, and Y.
Tokura, New J. Phys. 23 (2021) 023039.
[11] S. Seo et al., Commun. Phys. 4 (2021) 58.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Time-Dependent DMRG Study of Spectral Shape in
the Optical Conductivity of Two-Dimensional
Hubbard Model
Takami TOHYAMA
Department of Applied Physics, Tokyo University of Science, Tokyo 125-8585

The parent compound of cuprate superconductors is a Mott insulator in two dimensions.
The optical conductivity in the compound has
been measured and its spectral features havebeen discussed experimentally. However, theoretical understanding of its spectral shape isstill far from complete. This is due to theoretical diﬃculty caused by strong coupling of
localized spins and holon/doublon created byphotoexcitations. For example, it is unclear
whether there is a magnetically induced excitonic peak at the absorption edge or not [1, 2].
In order to clarify spectral properties of the
optical conductivity in two-dimensional Mott
insulator, we use time-dependent densitymatrix renormalization group (tDMRG) technique for a half-ﬁeld Hubbard model withsecond-neighbor hopping (t-t′ -U model) andcalculate time-dependent current induced byelectric ﬁeld applied along the x direction, fromwhich we can obtain the optical conductivity.
In our tDMRG the time-evolution operator
necessary for the calculation of time-dependent
wave function is evaluated by using a kernel
polynomial method [3], which is an approach
good for lattices more than one dimension.
We use a 6×6 square lattice of the t-t′ -Umodel with U/t = 10 under open boundary
condition [4]. The number of states kept in
tDMRG procedure is 4000. We note that we
also use an 8×8 lattice to check size dependence for a t-U model and ﬁnd that the difference of the optical conductivity in the twolattices is small. For the 6×6 lattice withoutt′ , the optical conductivity shows a prominent
peak at the absorption edge followed by continuous spectral weight distribution above thepeak position. The peak intensity depends onthe value of t′ , exhibiting a maximum of thepeak intensity at t′ = 0 as a function of t′ .
Since t′ introduces a diagonal antiferromagnetic exchange interaction, the eﬀect of frustration competing with the nearest-neighborexchange interaction appears. The frustrationeﬀect should not be dependent on the sign oft′ . This is the case of the present result. We
can say that magnetic interactions contributeto the peak at the absorption edge, indicating
magnetic origin of the peak, i.e., magnetic exciton. However, we note that there is no gap
between the peak and continuum mentioned
above. This is diﬀerent from a standard exciton where the exciton is deﬁned as a boundstate with well-deﬁned binding energy.

References[1] T. Tohyama, Y. Inoue, K. Tsutsui, and
S. Maekawa: Phys. Rev. B 72 (2005)
045113.
[2] X.-J. Hana et al.: New J. Phys. 18 (2016)
103004.
[3] K. Shinjyo and T. Tohyama: Phys. Rev.
B 103 (2021) 035141.
[4] K. Shinjyo, Y. Tamaki, S. Sota, and T.
Tohyama, in preparation.

204

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development and application of DFT+DMFT
software DCore
Hiroshi SHINAOKA
Department of Physics, Saitama University,
Saitama 338-8570

To make DFT+DMFT available to moreusers and to promote the development of acommunity of users and developers, we needan open-source program package with a userfriendly interface.
In this project, we have developed an opensource program, DCore v3.0.0 [1], that implements DMFT. This program features an interface based on text and HDF5 files, allowing
DMFT calculations of tight-binding models tobe performed on predefined lattices as well as
first-principles models constructed by external
DFT codes through the Wannier90 package.
Furthermore, DCore provides interfaces to avariety of quantum impurity solvers such as
quantum Monte Carlo codes developed in the
ALPS projects. DCore is implemented on the
top of the TRIQS Python library (Toolbox for
Research on Interacting Quantum Systems).
DCore v3.0.0 supports Python 3.x and TRIQS
3.0.

We used DCore to generate hybridization
functions for a five-orbital 2 × 2 cluster impurity model for LaAsFeO [2]. The impurity
model involves 40 spin orbitals. The hybridization functions computed by DCore are shownin Fig. 1. The hybridization functions havelarge off-diagonal elements and decay exponentially in the intermediate representation (IR)basis. We found that the exact hybridization
functions with large off-diagonal elements canbe fitted accurately with 332 bath sites using
sparse modeling techniques.
This report is based on the collaboration
with Y. Nagai, J. Otsuki, M. Kawamura, N.
Takemori, K. Yoshimi.
La( c ) W it h o u t r a n d o mO

p o t e n t i a Asl

Fe2
Fe1

1 0 1
∆i j ( l )Dynamical mean-field theory (DMFT) has
become a standard theoretical tool for studying strongly correlated electronic systems. In
a DMFT calculation, an original lattice model
is mapped to an effective Anderson impurity problem whose bath degrees of freedom
are self-consistently determined. Although
the DMFT was originally proposed for solving models such as Hubbard models, it canbe combined with density functional theory(DFT) based on ab initio calculations for describing the electronic properties of strongly
correlated materials. This composite framework, called DFT+DMFT, has been applied
to various types of materials.

1 0∆1 1 ( l )∆1 6 ( l ) ×−4∆1 7 ( l ) ×

1 0 −2
1 0 −4

1 0 −91 0 −1 4
0

1 0

2 0

3 0
l

4 0

5 0

6 0

Figure 1: Illustration of the DMFT selfconsistency cycle implemented in DCore

References[1] H. Shinaoka, J. Otsuki, M. Kawamura, N. Takemori, K. Yoshimi,
arXiv:2007.00901v3[2] H. Shinaoka and Y. Nagai, PRB 103,
045120 (2021)

205

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Classical Monte Carlo study of J1-J2 Heisenberg
antiferromagnet on the kagome lattice
Hiroshi SHINAOKA
Department of Physics, Saitama University,
Saitama 338-8570

Frustrated XY antiferromagnets have been
investigated extensively in the past decades
due to exotic phenomena induced by geometrical frustration. The classical nearest-neighbor
XY antiferromagnet on the kagome lattice isa typical two-dimensional frustrated magnet.
This model hosts a macroscopically degenerate
ground-state manifold. Small perturbations
such as thermal fluctuations lift the macroscopic degeneracy. This gives rise to various
exotic phenomena. An interesting question is
how next-nearest-neighbor interaction affects
the competition of degenerated states at finite
temperature.

Figure 1: q = 0 and
tions

√

3×

√

3 spin configura-based on the collaboration with F. Kakizawa
and T. Misawa.

In this project, we investigated the finitetemperature phase diagram of classical J1 J2 XY antiferromagnets on the kagome lattice through extensive Monte Carlo simulations [1, 2] using loop updates. We implemented the code in Julia, which is a modern
programming language for scientific computing. The code is parallelized using MPI.jl.
We found that a weak antiferromagnetic J2
induces an unconventional first-order transition at low temperatures. Furthermore, in thevicinity of the first-order transition, we find an
octupole ordered phase between two competing quasi-long-range orders with different spin
configurations (See Fig. 1). At antiferromatic
J2 = −0.03, the ground state is the q = 0
state. As shown in Fig. 2, there is a firstorder transition between the high-temperatureparamagnetic phase and the q = 0 quasi-longrange-ordered phase. At J2 = −0.005, theBerezinskii-Kosterlitz-Thouless transition appears at a higher temperature. This report is

Figure 2: Temperature (T ) dependence of thespecific heat C computed for J2 = −0.03 andJ2 = −0.005

References[1] F. Kakizawa, T. Misawa, H. Shinaoka,
APS March Meeting 2021, Y39.00012.
[2] 柿澤文哉, 三澤貴宏, 品岡寛, J1 –J2 古典
反 強 磁 性XY カ ゴ メ 模 型 に お け る 新 奇相転移、 日本物理学会第76回年次大会（2021年), 12pC1-8.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Research of Quantum Critical Points
Emerging between Two-Channel Kondo andFermi-Liquid States
Takashi HOTTA
Department of Physics, Tokyo Metropolitan University
1-1 Minami-Osawa, Hachioji, Tokyo 192-0397

In this research, we have investigated theemergence of quantum critical points (QCP)
near a two-channel Kondo phase by evaluating
an f -electron entropy of a seven-orbital impurity Anderson model hybridized with three (Γ7and Γ8 ) conduction bands with the use of a numerical renormalization group (NRG) method.
First we consider the local f -electron Hamiltonian Hloc . For the purpose, we introduce one
f -electron state, which is deﬁned by the eigenstate of spin-orbit and crystalline electric ﬁeld
(CEF) potential terms. Under the cubic CEF
potential, we obtain Γ7 doublet and Γ8 quartet
from j = 5/2 sextet, whereas we ﬁnd Γ6 doublet, Γ7 doublet, and Γ8 quartet from j = 7/2
octet. By using those one-electron states asbases, we describe Hloc as
Hloc =∑†(λj + Bj,µ + Ef )fjµτ
fjµτ

j,µ,τ

+

∑ ∑ ∑

j1∼j4 µ1∼µ4 τ1∼τ4

Iµj11jτ21,jµ32jτ42 ,µ3 τ3 µ4 τ4 (1)× fj†1 µ1 τ1fj†2 µ2 τ2fj3 µ3 τ3fj4 µ4 τ4 ,where fjµτ denotes the annihilation operator ofa localized f electron in the bases of (j, µ, τ ),j is the total angular momentum, j = 5/2 and7/2 are denoted by “a” and “b”, respectively,µ distinguishes the cubic irreducible representation, Γ8 states are distinguished by µ = α
and β, while Γ7 and Γ6 states are labeled byµ = γ and δ, respectively, τ is the pseudo-spin
which distinguishes the degeneracy concerning
the time-reversal symmetry, and Ef is the f -electron level to control the local f -electron
number at an impurity site.
As for the spin-orbit coupling term, we obtain λa = −2λ and λb = (3/2)λ, where λ isthe spin-orbit coupling of f electron. In thisresearch, we set λ = 0.1 and 0.11 for Pr and Ndions, respectively. Concerning the CEF potential term for j = 5/2, we obtain Ba,α = Ba,β =1320B40 /7 and Ba,γ = −2640B40 /7, where B40
denotes the fourth-order CEF parameter forthe angular momentum ℓ = 3. Note that thesixth-order CEF potential term B60 does notappear for j = 5/2, since the maximum size ofthe change of the total angular momentum isless than six. On the other hand, for j = 7/2,
we obtain Bb,α = Bb,β = 360B40 /7 + 2880B60 ,Bb,γ = −3240B40 /7 − 2160B60 , and Bb,δ =360B40 − 3600B60 /7. Note also that B60 term
appears in this case. In the present calculations, we treat B40 and B60 as parameters.
Now we consider the matrix element I of
the Coulomb interaction. Here we skip the details of the derivation of I, but they are expressed with the use of four Slater-Condon parameters, F 0 , F 2 , F 4 , and F 6 . Although the
Slater-Condon parameters of a material should
be determined from experimental results, here
we simply set the ratio as F 0 /10 = F 2 /5 =F 4 /3 = F 6 = U , where U is the Hund’s ruleinteraction among f orbitals. it is reasonable
to set U as 1 eV in this research.
In Fig. 1, we show the local CEF groundstate phase diagram for n = 3, obtained from207

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1.5

0.015

G6 doublet
W=10-3
x=0.0

0.005

1

W=10
x=-1.0-3

0.0-0.005-0.01-0.015-0.2

Simp

B60 [meV]0.01

G8 quartet

n=3
U=1
l=0.11

0.5 log 2-0.1

0.0
B40 [meV]

0.1

0.2

the diagonalization of Hloc . For n = 3, theground-state multiplet for B40 = B60 = 0
is characterized by total angular momentum
J = 9/2. Under the cubic CEF potentials, thedectet of J = 9/2 is split into three groups asone Γ6 doublet and two Γ8 quartets.
Now we include the Γ7 and Γ8 conduction
electron bands. Here we consider only the hybridization between conduction and j = 5/2
electrons. The Hamiltonian is given by∑εkc†kµτckµτ +k,µ,τ

+ Hloc ,

log f

0.5

Figure 1: Local CEF ground-state phase diagram on the plane of (B40 , B60 ) for n = 3.
Red line denote the trajectory of B40 = W x/15
and B60 = W (1 − |x|)/180 in the range of−1 ≤ x ≤ 0 for W = 10−3 .

H =

L=8.0
x=0.0
M=5000x=-0.3x=-0.372
x=-0.4x=-0.5n=3
U=1
l=0.11
W=10-3
V=0.7∑

Vµ(c†kµτ faγτ +h.c.)

k,µ,τ

(2)

where εk is the dispersion of conduction electron with wave vector k, ckγτ is an annihilation operator of conduction electrons, and Vµdenotes the hybridization between f electronin the µ orbital and conduction electron of theµ band. Here we set Vα = Vβ = Vγ = V .
In this research, we analyze this model by
employing the NRG method [1]. We introduce
a cut-oﬀ Λ for the logarithmic discretizationof the conduction band. Due to the limitationof computer resources, we keep M low-energy
states. Here we use Λ = 8 and M = 5, 000.
Note that the temperature T is deﬁned as T =DΛ−(N −1)/2 in the NRG calculation, where N

0 -9
10

-8

10

-7

-6

-5

-4

10 10 10 10
temperature T [eV]

-3

10

-2

10

Figure 2: Entropies Simp vs. temperature forn = 3 in the range of −1 ≤ x ≤ 0 with W =√10−3 . Note that ϕ is given by ϕ = ( 5 + 1)/2.
is the number of the renormalization step andD is a half of conduction band width. Here we
set D = 1 eV.
Here we brieﬂy discuss the typical results forn = 3 [2]. In Fig. 2, we show entropies Simp vs.
temperature, when we change the CEF parameters from x = 0 (Γ6 doublet) to x = −1 (Γ8quartet) for n = 3, W = 0.001, and V = 0.7.
For x = 0 and −0.3, we obtain the magnetic
two-channel Kondo phase, while for x = −0.4
and −0.5, the screened Kondo phase appears,
since the Γ8 quartet eﬀectively expressed by
S = 3/2 spin is screened by three conduction
electrons. At x = −0.372 between two-channel
Kondo and Fermi-liquid phases, we ﬁnd an entropy plateau of log ϕ. In this case, we could
not observe the residual entropy of log ϕ at low
enough temperatures, but the signal of QCP is
considered to be obtained.

References[1] H. R. Krishna-murthy, J. W. Wilkins, andK. G. Wilson, Phys. Rev. B 21, 1003
(1980).
[2] T. Hotta, J. Phys. Soc. Jpn. 89, 114706(2020).

208

-1

10

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Disorder eﬀect on Kitaev quantum spin liquids
Joji Nasu
Department of Physics, Yokohama National University
Hodogaya, Yokohama 240-8501, Japan

Quantum spin liquid has been actively studied in strongly correlated electron systems. It
is a state that does not show magnetic order down to the lowest temperature, whichappears in insulating magnets and thought
to appear owing to the cooperation of strong
quantum ﬂuctuations and many-body eﬀects.
Thus far, one considers geometrical frustration, which is essential to realize this state in
the Heisenberg quantum spin model in the lattice structure. However, in this situation, one
usually suﬀers from the negative sign problem
in the quantum Monte Carlo method. Hence,the properties of quantum spin liquid have notbeen well understood theoretically.
On the other hand, attempts to realize quantum spin liquids other than the Heisenberg
model have been made. Among them, the Kitaev model has recently attracted considerable
attention because its ground state is a quantum spin liquid as an exact solution. Experimentally, many physical quantities such as speciﬁc heat, entropy, magnetic excitation, andthermal transport properties have been measured in ruthenium and iridium compounds,
which are believed to be described by the Kitaev model, and have been compared with theoretical studies. In the real systems, eﬀects
of the disorder are inevitably present, which
complicates extracting the nature of the Kitaev quantum spin liquid. Thus, calculations
incorporating such eﬀects are necessary to separate the properties intrinsic to Kitaev quantum spin liquids from others.

and bond randomness using quantum Monte
Carlo simulations. The spin Hamiltonian isrewritten into the free Majorana fermion system coupled to Z2 variables. The Majorana
fermion system is diagonalized using the LAPACK library, and the conﬁgurations of theZ2 variables are updated by the Markov chain
Monte Carlo method. To avoid the freezing of
the conﬁgurations, we employ the parallel tempering technique using the MPI library. Here,
we calculate thermodynamic quantities such as
the speciﬁc heat and thermal transport [1]. We
ﬁnd that the speciﬁc heat remains largely intact even in the presence of disorder at higher
temperatures compared to the spin-exchange
energy, while the low-temperature behavior issensitive to the disorder. For thermal transport, the longitudinal component of the thermal conductivity is suppressed by the disorder. This behavior is common to site dilution
and bond randomness. On the other hand, thethermal Hall conductivity is aﬀected by these
disorders diﬀerently. We ﬁnd that the quantization of the thermal Hall conductivity is robust against the bond randomness but is fragile for the site dilution.

References[1] J. Nasu and Y. Motome: Phys. Rev. B
102 (2020) 054437.

In this study, we perform numerical calculations for the Kitaev model with site dilution

209

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Effect of quenched disorder on a triangular lattice fermionicmodel
Chisa HOTTA
Department of Basic Science,
The University of Tokyo, Meguro-ku Komaba, Tokyo 153-8902
We studied the fermionic model on amoving the location of pins, and eachtriangular lattice with quenched disorder[1]. We

timediagonalizing the ball-fermions under theare targeting the so-called tV model on ainteraction from pins, the system is safely

triangular lattice consisting of transfer integrals

thermalized to the pinball-liquid phase. Wet and nearest neighbor Coulomb repulsions V,

made full use of the ISSP supercomputing

whose ground state is known to host a Pinballsystem to perform the calculation up to theliquid phase [2,3] at large V/t, which is a statesystem size of 24x24; the finite temperature

where part of the fermions localize on one ofphase transition is observed as a divergence inthe three-sublattices, and form a symmetry

the specific heat. Also the low energy profile ofbreaking long range order. The rest of thethe pinball liquid state is well reproduced. We

fermions remain metallic and propagate along

also found that at extremely low temperature,

2/3 of the lattice sites forming a honeycomb

the introduction of the quenched disorder willband. To be precise, the long range ordered

drive the system to some sort of a glassy phase,fermions (pin) and metallic fermions(ball) are

where there starts to appear a domain wall

not fully separate, but exchange by the quantum

structure of pinball phase. This domain

fluctuation. In this study, we focus on the finite

becomes distinct as the system size becomes

temperature properties of this phase, by adding

larger and the degree of disorder is increased,

a quenched disorder to the transfer integral.

which is detected in the broad structure of the

However, it is quite difficult to fully solve

Replica overlap distribution function.

the standard tV model at finite temperature in a

References

reasonably large system size. Therefore, we[1] Keita Urakami and Chisa Hotta, in preparation.

introduce[2] Chisa Hotta and Nobuo Furukawa , Phys. Rev.

the

Falikov-Kimball

type

of

approximation and set the pins to be classical,

B 74, (2006)193107.

while keep the balls to be quantum, and[3] Chisa Hotta, Nobuo Furukawa, Akihikoperform the Monte Carlo calculation. By

Nakagawa, and Kenn Kubo , J. Phys. Soc. Jpn. 75,

changing the ratio of pin and ball and by(2006) 123704.

210

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ordered states in strongly correlated Dirac electron
systems of organic conductors
Akito KOBAYASHI
Department of Physics, Nagoya University
Nagoya 464-8602

In the low temperature phase (T < Tco =135K) of the organic Dirac electron system α(BEDT-TTF)2 I3 , it is believed that the electron correlation breaks the spatial inversion
symmetry and transitions to a stripe chargeordered insulator. The electron correlationinduces the reshaping of Dirac cones andthe anomalous spin fluctuation. We investigated the electron correlation eﬀects on theanomalous thermoelectric eﬀects and the spin
fluctuations[2, 4, 6]. In contrast, the elementsubstituted α-(BETS)2 I3 shows insulating behavior at low temperatures below 50 K, but nocrystal symmetry breaking or charge densitychange is observed in X-rays, and no sign ofmagnetic transition is obtained from NMR. In
this study, we constructed an extended Hubbard model based on first-principles calculations and analyzed it using mean-field approximation. It was shown that a magnetic transition occurs due to a short-range Coulomb interaction as shown in Fig. 1[3]. However, sinceno magnetic transition was observed in the experiment, it is necessary to investigate otherpossibilities. In addition, we showed possibleedge magnetism in Dirac nodal line systems of
single component molecular conductors [1, 5].

References[1] T. Kawamura, B. Zhou, Akiko Kobayashi,
Akito Kobayashi, accepted to J. Phys.
Soc. Jpn. (2021/03/30)

Figure 1: A candidate of ordered states in α(BETS)2 I3 .
[2] M. Hirata, A. Kobayashi, C. Berthier and
K. Kanoda, Rep. Prog. Phys. 84 036502(2021)[3] D. Ohki, K. Yoshimi, and A. Kobayashi,
Phys. Rev. B 102, 235116 (2020)[4] D. Ohki, M. Hirata, T. Tani, Kazushi K.,
and A. Kobayashi, Phys. Rev. Research 2,033479 (2020)[5] T. Kawamura, D. Ohki, B. Zhou, Akiko
Kobayashi, Akito Kobayashi, J. Phys.
Soc. Jpn. 89, 074704 (2020)[6] D. Ohki, Y. Omori, A. Kobayashi, Phys.
Rev. B 101, 245201 (2020)

211

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of electronic structure calculation forsolids with post-Hartree-Fock calculations
Kazutaka NISHIGUCHI
Department of Physics, Osaka University
Toyonaka, Osaka 560-0043, Japan– Electronic structure calculation for solids
with post-Hartree-Fock calculations –Continuing from our preceding-term study, we
have theoretically studied a new method ofelectronic structure calculation for solids withquantum chemistry calculations. Our proposed procedure is as follows. We first startwith Hartree Fock (HF) calculation for solids
and construct maximally localized Wannierfunctions as a localized basis set. Then we
consider a real-space cluster in the Wannier
representation and solve it numerically withequation-of-motion coupled cluster (EOM-CC)
theory. Here we have used VASP (The Vienna
Ab initio Simulation Package) [1, 2, 3, 4, 5]
in the HF calculations, Wannier90 [6, 7, 8, 9]in the wannierization method, and GELLAN
program [10] in the EOM-CC calculations.
We apply this method to typical semiconductors, namely, bulk Si and SrTiO3 , and evaluate these energy band gaps as a benchmark.
Developing the preceding-term study, we use
symmetry-adapted Wannier functions [9] inconstructing the localized basis set with Wannier90. We then can observe that the localizedbasis set can be obtained stably and the band
gap can be improved compared to that with
the HF calculations. However, it is still insuﬃcient because the number of the localizedbases is not suﬃcient to take into account theelectron correlations. To increase the numberof the localized bases will be an interesting future work.

CaZn2 X2 (X = Sb, As, P) –Continuing from our preceding-term study,
we have numerically evaluated a formationenergy of n-type doping in a strong candidate of high performance thermoelectric materials CaZn2 X2 (X = Sb, As, P) by the
first-principles calculations based on the density functional theory (DFT). We consider thechemical doping into the interstitial site andthe element substitution of Ca, where thedopant is assumed to be the alkaline earth
metals (Mg, Ca, Sr, Ba) and group 3 elements (Sc, Y, La). The ionization energy ofthese elements is relatively small as cations
so that the smaller formation energy is expected. To take into account the chemical doping, the 3 × 3 × 2 supercell calculations are
performed (Figure 1) with the Perdew Burke
Ernzerhof (PBE) functional, namely, the generalized gradient approximation (GGA). Here
we have used VASP [1, 2, 3, 4, 5] in the firstprinciples calculations.

Figure 1: 3 × 3 × 2 supercell of CaZn2 X2 (X =Sb, As, P). (Left) Doping into the interstitialsite. (Right) Element substitution of Ca.

– Formation energy of n-type doping in

For the interstitial doping one can observe212

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

in Figure 2 that the chemical doping of Ca
and group 3 elements is favorable according
to the formation energy. In addition, for theelement substitution of Zn one can also see in
Figure 3 that the element substitution for Sc
is stable. This tendency of the formation energy is considered to depend on the ionizationenergy of these doping elements and the ionicradius against the interstitial site and Ca vacancy site. The improvement of the exchange
correlation functional such as the hybrid functional and the inclusion of the finite-size supercell eﬀect will be important future works.

Figure 3: Formation energy of the element substitution of Ca.
[3] G. Kresse and J. Furthmüller, Comput.
Mater. Sci. 6 15 (1996).
[4] G. Kresse and J. Furthmüller, Phys Rev.
B 54 11169 (1996).
[5] VASP (The Vienna Ab initio Simulation
Package): https://www.vasp.at[6] N. Marzani and D. Vanderbilt, Phys. Rev.
B 56 12847 (1997).
[7] I. Souza, N. Marzani, and D. Vanderbilt,
Phys. Rev. B 65 035109 (2001).
Figure 2: Formation energy of the doping into
the interstitial site.

[8] Wannier90: http://www.wannier.org[9] R. Sakuma, Phys. Rev. B 87 235109(2013).

References[1] G. Kresse and J. Hafner, Phys. Rev. B 47
558(R) (1993).

[10] GELLAN: A hierarchical massivelyparallel quantum chemistry program,
Kobe University[2] G. Kresse and J. Hafner, Phys. Rev. B 49
14251 (1994).

213

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of electronic structure calculation forsolids with quantum chemistry calculations
Kazutaka NISHIGUCHI
Department of Physics, Osaka University
Toyonaka, Osaka 560-0043, Japan– Electronic structure calculation for solids
with quantum chemistry calculations –A new method of electronic structure calculation for solids with quantum chemistry calculations have been studied theoretically. We firststart with Hartree Fock (HF) calculation forsolids and construct maximally localized Wannier functions as a localized basis set. Then
we consider a real-space cluster in the Wannier
representation and solve it numerically withequation-of-motion coupled cluster (EOM-CC)
theory. Here we have used VASP (The Vienna
Ab initio Simulation Package) [1, 2, 3, 4, 5]
in the HF calculations, Wannier90 [6, 7, 8] inthe wannierization method, and GELLAN program [9] in the EOM-CC calculations.
We apply this method to typical semiconductors, namely, bulk Si and SrTiO3 , and evaluate these energy band gaps as a benchmark.
We can observe that the band gap can be improved compared to that with the HF calculations, but it is not suﬃcient because the localized basis set is diﬃcult to converge stably.
To achieve stable construction of the localizedbasis set will be an interesting future work.
– Formation energy of n-type doping in
CaZn2 Sb2 –A formation energy of n-type doping in astrong candidate of high performance thermoelectric materials CaZn2 Sb2 have been numerically evaluated by the first-principles calculations based on the density functional theory(DFT). We consider the chemical doping into
the interstitial site and the element substitu-

tion of Zn, where the dopant is assumed to be
the alkaline earth metals (Mg, Ca, Sr, Ba) andgroup 3 elements (Sc, Y, La). The ionizationenergy of these elements is relatively small as
cations, so that the smaller formation energy
is expected. To take into account the chemical
doping, the 3 × 3 × 2 supercell calculations are
performed (Figure 1) with the Perdew Burke
Ernzerhof (PBE) functional, namely, the generalized gradient approximation (GGA). Here
we have used VASP [1, 2, 3, 4, 5] in the firstprinciples calculations.

Figure 1: 3 × 3 × 2 supercell of CaZn2 Sb2 .
(Left) Doping into the interstitial site. (Right)
Element substitution of Zn.
For the interstitial doping one can observe in
Figure 2 that the chemical doping of Ca andgroup 3 elements is favorable according to theformation energy. In addition, for the element
substitution of Zn one can also see in Figure
3 that the element substitution for Mg, Ca,Sr, and group 3 elements is stable. This tendency of the formation energy is considered todepend on the ionization energy of these doping elements and the ionic radius against theinterstitial site and Zn vacancy site. On theother hand, the calculated formation energy is214

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

now understood to be qualitative because thePBE functional is not suﬃcient to evaluate theaccurate energy band gap for semiconductors
and the finite-size supercell eﬀect is not included in these calculations, but the tendencyof the formation energy is important for material synthesis of n-type semiconductors. The
improvement of the exchange correlation functional such as the hybrid functional and theinclusion of the finite-size supercell eﬀect will
be important future works.

[4] G. Kresse and J. Furthmüller, Phys Rev.
B 54 11169 (1996).
[5] VASP (The Vienna Ab initio Simulation
Package): https://www.vasp.at[6] N. Marzani and D. Vanderbilt, Phys. Rev.
B 56 12847 (1997).
[7] I. Souza, N. Marzani, and D. Vanderbilt,
Phys. Rev. B 65 035109 (2001).
[8] Wannier90: http://www.wannier.org[9] GELLAN: A hierarchical massivelyparallel quantum chemistry program,
Kobe University

Figure 2: Formation energy of the doping into
the interstitial site.

Figure 3: Formation energy of the element substitution of Zn.

References[1] G. Kresse and J. Hafner, Phys. Rev. B 47
558(R) (1993).
[2] G. Kresse and J. Hafner, Phys. Rev. B 49
14251 (1994).
[3] G. Kresse and J. Furthmüller, Comput.
Mater. Sci. 6 15 (1996).

215

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Quantum Monte Carlo simulation and electronic
state calculations in correlated electron systems
Takashi YANAGISAWA
Electronics and Photonics Research InstituteNational Institute of Advanced Industrial Science and Technology (AIST)
AIST Central 2, 1-1-1 Umezono, Tsukuba 305-8568

the band parameters.
0.006

PS

∆E /N

We carried out numerical calculations on
the basis of the optimized variational Monte
Carlo method[1, 2, 3, 4]. We have investigated the ground-state phase diagram of thetwo-dimensional Hubbard model and the twodimensional d-p model. We performed parallel computations by using a Monte Carlo algorithm. In order to reduce statistical errors,
we carried out 200 ∼ 500 parallel calculations.
Parallel computing is very necessary to reduce
Monte Carlo statistical errors.

0.004

AF
0.002

AFI
SC
0

We employed the improved wave function ofan exp(−λK) − PG -type[1]. This wave function is a very good many-body wave function because the ground-state energy is lowered
greatly and the ground-state energy is lower
than those that are evaluated by any otherwave functions[2]. We can improve the wave
function systematically by multiplying by operators PG and e−λK several times.
We exhibit the condensation energy as afunction of the doping rate x for the three-band
d-p model in Fig. 1 where Ud = 10tdp and thelevel difference is taken as ∆dp ≡ ǫp − ǫd =tdp [6]. There is the AF region when x is small
and the SC region exists near the optimum region x ∼ 0.2. We should mention that there
is a phase-separated region in the low-doping
region where x < 0.07. This indicates the existence of AF insulator phase in the low doping
region. This is similar to the phase diagramof the 2D Hubbard model. The phase separation (PS) is, however, dependent on the level
difference ∆dp . As ∆dp decreases, the phaseseparated region decreases and vanishes when
∆dp approaches zero. Thus the area of phaseseparated region can be controlled by changing

216

0

0.05

0.1

0.15

0.2

0.25

0.3

x

Figure 1: AF and SC condensation energies asa function of the hole doping rate x for ∆dp = 1
on a 8 × 8 lattice with tpp = 0.4 and Ud = 10 inunits of tdp . There is a phase-separated region
when x is small.

References[1] T. Yanagisawa et al., J. Phys. Soc. Jpn.
67, 3867 (1998).
[2] T. Yanagisawa, J. Phys. Soc. Jpn. 85,
114707 (2016).
[3] T. Yanagisawa, J. Phys. Soc. Jpn. 88,
054702 (2019).
[4] T. Yanagisawa, Condensed Matter 4, 57(2019).
[5] T. Yanagisawa, Phys. Lett. A403, 127382(2021).
[6] T. Yanagisawa et al., EPL (2021).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Calculation of the electronic state in a large model of theorganic charge ordering system using mVMC
Masatoshi SAKAI, Riku TAKEDA, Ryoma ISHII
Department of Electrical and Electronic Engineering,
Chiba University, 1-33 Yayoi-cho Inage, Chiba 263-8522
We have studied the electronic state of thethe system.

large-size model of the organic charge order

The other work in progress is about -(BEDT-

system by using the supercomputer. We made aTTF)2PF6, of which metal-insulator phasebase model of -(BEDT-TTF)2I3 by citingtransition is 297 K [2]. In this work, we could

reference [1] and carried out a 28 x 28 site

not find the physical parameters in previous

calculation to reveal the electron number

works, so we began to calculate from the band

dependence of the charge order structure of thestructure before carrying out model calculation

correlated electron system. The simulationof correlated electronic system. We usedsoftware mainly used in this work was mVMC,

Quantum Espresso and Respack to obtainas preinstalled in the ENAGA and OHTAKA

physical parameters to build the calculation

supercomputer systems. The electron number

model used in mVMC or HPhi. We learned

dependence of the charge order structure is

Quantum Espresso and Respack, and now wesignificant for us to support our experimental

have just achieved the end of the calculation ofwork. Our experimental work was the metal-

the Respack. Therefore, we will verify theinsulator phase transition transistor which was

results and apply the next step by using mVMC

observed in organic charge order material of -or HPhi to reveal the physical principle of the(BEDT-TTF)2I3 near the metal-insulator phase

phase transition field-effect transistor.

transition at 137 K. We expect that thecalculation of electron number dependence ofReferencescharge order structure and energy will give a[1] Daigo Ohki, Genki Matsuno, Yukiko Omori

theoretical backbone to our experimental result.

and Akito Kobayashi: Crystals 8, (2018) 137.

Our group made an effort to learn about[2] Hayao Kobayashi, Takehiko Mori, Reizo

supercomputer and mVMC, and now we are

Kato, Akiko Kobayashi, Yukiyoshi Sasaki,

finally in routine calculation by varying

Gunzi Saito and Hiroo Inokuchi: Chem. Lett.

electron number from 376 to 404 electrons in(1983) 581.

217

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study for high-Tc cuprates using four-band d-p model
Hiroshi WATANABE
Research Organization of Science and Technology, Ritsumeikan University
1-1-1 Noji-Higashi, Kusatsu-shi, Shiga 525-8577

The discovery of superconductivity incuprates [1] has brought about the significant
progress in strongly-correlated electron systems. However, we have not yet reached a unified understanding of their properties, including their material dependence of the superconducting transition temperature Tc . Recent development of theories and experiments sheds
light on the importance of the orbital degreeof freedom in cuprates [2, 3]. To elucidate thematerial dependence of Tc , we study the fourband d-p model for La2 CuO4 and HgBa2 CuO4
systems that properly includes the orbital degree of freedom. The ground state properties
are studied with the variational Monte Carlo(VMC) method. The Gutzwiller-Jastrow typewave function is used for the VMC trial wave
function. The system size for the calculation is N =24×24=576 unit cells (and thus
576×4=2304 orbitals in total), which is large
enough to avoid finite size eﬀects.
The superconducting correlation function
vs hole doping rate δ for the La2 CuO4
and HgBa2 CuO4 systems are shown in Fig. 1.
The dome-shaped behavior and the material
dependence are consistent with experiments.
We show that the Cu dz 2 orbital contribution
around the Fermi energy is destructive for dwave superconductivity, and thereby becomesa key factor to determine Tc . The energy diﬀerence ∆dp between Cu dx2 −y2 and O p orbitals
is also shown to be a key factor. Our result
accounts for the empirical correlation between
Tc and model parameters and gives the unified
description beyond the usual one-band Hubbard, t-J, and even three-band d-p models.
P dd

Figure 1: Superconducting correlation function P dd vs hole doping rate δ for the La2 CuO4
and HgBa2 CuO4 systems.

References[1] J. G. Bednorz and K. A. Muller, Z. Phys.
B 64, 189 (1986).
[2] H. Sakakibara et al., Phys. Rev. Lett. 105,
057003 (2010).
[3] C. E. Matt et al., Nat. Commun. 9, 972(2018).

218

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Studies of the superconductivity and magnetic statesin the strongly correlated electron systems using
Hubbard models.
Atsushi Yamada
Department of Physics, Chiba University
Chiba 263-8522, Japana, Chiba 277-8581

A spin liquid state has attracted a lotof interest. This state is realized in geometrically frustrated systems like the chargeorganic transfer salts κ-(BEDT-TTF)2 X[1]and Cs2 CuCl4 .[2] Hubbard model on the anisotropic triangular lattice is a simple theoretical model of these compounds, and spin liquid state is found in this model.[3] A spin liquid could arise also in the intermediate coupling region of strongly correlated systems between a semi-metal and ordered state, because
in this case a correlation-driven insulating gap
might open before the system becomes ordered. This possibility might be realized in
the half-ﬁlled Hubbard model on the honeycomb lattice, where a semi-metal is realized at
U = 0.
We have studied the magnetic and metal-toinsulator transitions by variational cluster approximation using 10-site and 16-site clusters
as a reference system. Parts of numerical calculations were done using the computer facilities of the ISSP. We found that UAF = 2.7 and
UMI = 3.0 for 10-site cluster, and UAF = 2.7
and UMI = 3.2 for 16-site cluster.[5] This result
also rules out the existence of the spin liquid inthis model. Our results agree with recent large
scale Quantum Monte Carlo simulations.[4]We are currently improving our program using MPI technique so that we will be able tostudy a larger cluster size system.

References[1] Y. Shimizu, K. Miyagawa, K. Kanoda,
M. Maesato, and G. Saito, Phys. Rev.
Lett. 91, 107001 (2003); Y. Kurosaki, Y.
Shimizu, K. Miyagawa, K. Kanoda, and
G. Saito, Phys. Rev. Lett. 95, 177001(2005).
[2] R. Coldea, D.A. Tennant, A.M. Tsvelik,
and Z. Tylczynski, Phys. Rev. Lett. 86,
1335 (2001); R. Coldea, D.A. Tennant,and Z. Tylczynski, Phys. Rev. Lett. 68,
134424 (2003).
[3] T. Yoshioka, A. Koga, and N. Kawakami,
Phys. Rev. Lett. 103, 036401 (2009); P.
Sahebsara and D. Sénéchal, Phys. Rev.
Lett. 100, 136402 (2008); L.F. Tocchio,
H. Feldner, F. Becca, R. Valenti, and C.
Gros, Phys. Rev. B 87, 035143 (2013); A.
Yamada, Phys. Rev. B 89, 195108 (2014);
L.F. Tocchio, C. Gros, R. Valentı́, F.
Becca, Phys. Rev. B 89, 235107 (2014); A.
Yamada, Phys. Rev. B 90, 235138 (2014).
[4] S. Sorella, Y. Otsuka, and S. Yunoki, Sci.
Rep. 2, 992 (2012); F. F. Assaad andI. F. Herbut, Phys. Rev. X 3, 031010(2013); F. Parisen Toldin, M. Hohenadler,
F. F. Assaad, and I. F. Herbut, Phys. Rev.
B 91, 165108 (2015).
[5] A. Yamada, Int. J. Mod. Phys. B 30,
1650158 (2016).

219

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.4

Cooperative Phenomena
in Complex Macroscopic Systems

220

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Tensor-Network Renormalization-Group Studyof Critical Phenomena
Naoki KAWASHIMA
Institute for Solid State Physics,
The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581
The objective of the project is to develop
newmethods

forstudyingtheIn [2], we studied the J-K- model, a model

criticalthat may represent some aspect of thephenomena, both classical and quantum, andcompound -RuCl3, which is expected to be

apply them to strongly correlated systems.

close to the Kitaev spin liquid and presents

Especially, we aim at improving the real-spacesome features hinting a non-trivial topologicalrenormalization group (RSRG) method based

structure of its state. We discovered that theon the tensor network representation with thechiral spin liquid phase proposed by ahope for fuller understanding of the structure ofpreceding study is realized in a narrower region

the scaling dimensions of 2+1 or 3 dimensional

than predicted. In addition, we discovered two

fixed-point theories.

more non-magnetic phases that our calculation

In [1], we proposed a method for obtaining

suggested possesses also non-trivial topologicalan efficient low-rank approximation of a given

structure.

tensor. This was motivated by the conventional

In [3], we studied the spin-1 Kitaev model.

RSRG methods such as the loop-TNR andThis was motivated by the preceding work byentanglement filtering. In those methods, theLee, Kaneko, Okubo and I on the conventional

crucial part is removal of redundancy in the

spin-1/2

tensor-network representation arising from

relationship between the gapless Kitaev spinloops. They can be regarded as a special form

liquid and the classical loop gas model. In [3],of low-rank approximation of a given tensor. It

in contrast to the S=1/2 case, we discovered themight then be useful also for more general class

gapful spin liquid with Z2 structure of theof tensors, e.g., the image data in the form ofquasi-particles.

case,

in

which

we

discovered

tensors. The proposed method successfully

In [4], we improved the high-order tensor

identified the redundant structure of therenormalization group (HOTRG), one of theentanglement naturally formed in the process of

conventional RSRG besed on the tensor-

thenetwork representation. In the HOTRG, wetensorrenormalization

group

(TRG)

calculation.

bind two parallel bonds together to form one

221Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

renormalized bond in much the same spirit as

characterization

the Migdal-Kadanoff RG. In doing so, we needphenomena has been a tough problem even fora projection operator for the rank reduction. In

DMRG.

its simplest implementation of the HOTRG,

characterize various phases including symmetry

only the local environment is taken into

protected topological phases by the 2nd

account in computing the projection operator,

cohomology group represented by the resulting

while it would obviously be better to optimize

fixed-point tensors. Critical behaviors between

the projector in more global environment.

the phases are also accurately characterized.

In

of

our

the
study,

quantum
wecritical

successfully

Several methods for better optimization has
been

proposed

at

the

cost

of

References

highercomputational complexity. The method we[1] Hyun-Yong Lee, and Naoki Kawashima: J.

proposed is based on the corner transfer-matrix

Phys. Soc. Jpn. 89, 054003 (2020)

technique and reduces the computational[2] Hyun-Yong Lee, Ryui Kaneko, Li Erncomplexity without serious degrading of theChern, Tsuyoshi Okubo, Youhei Yamaji, Naoki

accuracy.

Kawashima and Yong Baek Kim: Nature

In [5], we applied the method of variational

Communications 11, 1639 (2020).

uniform matrix-product-state (VUMPS), an[3] Hyun-Yong Lee, Naoki Kawashima and

MPS-based

Yong Baek Kim: Phys. Rev. Res. 2, 033318

methodforone-dimensional

quantum systems to the 2-leg ladder system(2020).

with[4] Satoshi Morita and Naoki Kawashima: Phys.

four-bodyinteraction,

i.e.,

a

one-

dimensional analogue of the JQ model that

Rev. B103, 045131（1-6） (2020)shows a deconfined critical phenomena. While[5] Takuhiro Ogino, Ryui Kaneko, Satoshi

DMRG is known to be a very powerful

Morita,numerical

Kawashima: Phys. Rev. B 103, 085117 (2021).

dimensional

tool

in investigating thequantum

systems,one
direct222

Shunsuke

Furukawa

and

Naoki

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Molecular Dynamics Simulations of Bio-Inspired
Materials
Wataru Shinoda
Department of Materials Chemistry, Nagoya University
Nagoya 464-8603

We have studied the surface hydrophobicity
of self-assembled monolayers (SAM) [1] using
massive parallel computer simulations. The
surface hydrophobicity was investigated for arange chemically functionalized (–CF3 , –CH3 ,–OCH3 , –OH) SAMs as illustrated in Fig. 1.
These SAMs have many industrial and biological applications such as for making well-defined
non-fouling surfaces, cell supports, receptors,
sensors, microarrays, separation devices, andfor surface reactions [1, 2]. A good understanding of surface properties of these SAMs can allow us to further modify and control them forthe specific uses.

Figure 1: Surface hydrophobicity of chemically functionalized (–CF3 , –CH3 , –OCH3 , –OH) self-assembled monolayers. (a) Structureof a water droplet on the fluoroalkyl SAM surface (b) The formation of a cavity near the
SAM-water interface.
The study was conducted with all-atom(AA) simulation model using the LAMMPS

223

molecular dynamics (MD) simulation package[3]. The systems were modeled using the optimized potentials for liquid simulation (OPLS)
force field [4]. SPC/E rigid-body water model
was used for the water molecules [5]. A wide
range of packing densities and chain lengths
were considered in the study to understandtheir eﬀects on the surface hydrophobicity.
Analyses of the MD trajectories were done using the in-house codes. The complete detailsof the computational method can be found in
Ref. [6, 7].
The surface hydrophobicity was investigatedby means of (1) the structure, (2) the contact
angle of a water droplet on the surface, and(3) the cavity formation free energy. In the
structure, we mainly focused on density distribution, hydrogen-bonding, chain flexibility via
root mean square displacement (RMSD), androughness of the SAM surfaces. The free energy of cavity formation was calculated fromindirect umbrella sampling methods [6, 7],
in which used massive parallel computing resource. The results were found quite consistent with experiments. Through these studies,
we demonstrated a systematic path to examine the hydrophobicity of such synthetic surfaces. For the hydrophobic surfaces such as forthe fluorinated chains, it was found that thesurface hydrophobicity is mainly governed bypacking density rather than the chain length.
It increases on reducing the packing densityof SAMs. The SAM flexibility causes an enhancement in the surface hydrophobicity inde-

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

pendent of chemical functional groups. These
information would be certainly useful for thematerial design and modifying the surfaces.
Additionally, we developed a coarse-grained(CG) model for the semi-fluorocarbon diblocks
and studied the hemimicelle formation of thesechains at the air-water interface using ISSP
supercomputer. These systems contain morethan 100,000 particles even in the CG model.
We showed a mechanism of micelle formation
for these diblocks and successfully explained
the non-coalescence behavior of micelles, which
was a puzzle for the experimentalists [8]. It
was found that an unique alternating P-phaseforms in between the micelles, which has lateral and vertical dimensions of the nanoscaleorder (see Fig. 2). We believe that this Pphase could be reason for the non-coalescencebehavior of micelles under strong compression.

Figure 3: Adsorption of protein on synthetic
SAM surfaces.
time scale. In this study, we will also consider
the adsorption of more larger systems such as
virus capsids and organelles.

References[1] J. C. Love, L. A. Estroﬀ,J. K. Kriebel, R.
G. Nuzzo, and G. M. Whitesides: Chem.
Rev. 2005, 105 (2005) 1103.
[2] J. E. Raynor, J. R. Capadona, D. M.
Collard, T. A. Petrie, and A. J. Garcia:
Biointerphases 4 (2009) FA3.
[3] S. Plimpton:(1995) 1-19.

J. Comput. Phys. 117[4] W. L. Jorgensen, D. S. Maxwell, and J.
Tirado-Rives: J. Am. Chem. Soc. 118(1996) 11225.
Figure 2: The hemimicelle formation of semifluorocarbons at the air-water interface andthe structure of P-phase existing in between
the hemimicelles.
More recently, we studied the amino acids
and protein adsorption on the SAM surfaces(see Fig 3). We are in the process of summarizing results of these simulations for the publication. We found ISSP supercomputer really
useful for conducting simulation of such largescale complex systems. We are further looking
to simulate protein adsorption on the polymers
using a coarse-grained model to cover extensive

224[5] H. J. C. Berendsen, J. R. Grigera, andT. P. Straatsma: J. Phys. Chem. A. 91(1987) 6269.
[6] H. O. S. Yadav, A. -T. Kuo, S. Urata andW. Shinoda: Langmuir 35 (2019) 14316.
[7] H. O. S. Yadav, A. -T. Kuo, S. Urataand W. Shinoda: J. Phys. Chem. C 124(2020) 14237.
[8] H. O. S. Yadav and S. Harada, A. -T. Kuo,
S. Urata, and W. Shinoda: Mol. Phys.
(2021) e1910355.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Construction of data assimilation in materials science
Munehisa MATSUMOTO
Institute of Materials Structure Science, High Energy Accelerator Research Organization
Oho 1-1, Tsukuba 305-0801

We have been developing methods to use
both of experimental data and theoretical data
to better characterize and predict good magnetic materials [1, 2]. Experimental data takenfrom actual materials and corresponding computational data constitute an integrated data
model. The desired properties of materials areoften well defined and it now looks as though it
is getting more and more feasible to implementa scheme for rational materials design based on
the integrated data among various experimental probes and ab initio materials data. However, during the course of our developments weare rather finding the relevance of stochastic
aspects of the materials design.
The problem is caused by multiple requirements which are often simultaneously imposed on the target materials. For permanent
magnets, a candidate compound should havestrong magnetization, magnetic anisotropy,
high Curie temperature, and sufficient structure stability. Unfortunately it is hardly thecase that all of these can be maximized witha particular chemical composition. Trade-off’s
are encountered and we have to work with agood compromise. Besides, another problem
is imposed by the multi-scale nature of materials. The material is put into practical use
in a macroscopic world in non-equilibrium andat the moment it is hardly possible to keep all
those extrinsic parameters under control in themodeling.
A starting point is to restrict the working
parameter space and implement an optimization scheme therein referring to the given setof requirements for the target material [2]. An-other solution which potentially has the flexibility to deal with the effect of the extrinsic parameters is a stochastic sampling over the landscape of the parameter space. A set of equivalently preferable parameter points can be sampled out and proposed as a set of candidate
materials to meet the given needs. We notethat the external needs can vary depending onsocial and economical trends. Even some unexpected requirements can pop up depending on
how the material is used in practical applications. These are not predictable, which points
to an unavoidable stochasticity in the materials design. Thus it seems to be a good idea toconsider the materials design as a stochastic
process working on the integrated data spaceconstructed over various experimental probes
and theoretical calculations. We adapt thedata assimilation techniques in weather forecasts into the materials science. Developments
are in progress and will be reported in detailelsewhere.
The author benefited from the online schoolfor data assimilation in the autumn 2020 [3].

References[1] MM, T. Hawai, K. Ono, Phys. Rev. Applied 13, 064028 (2020).
[2] Y. Harashima, K. Tamai et al.,Phys. Rev. Materials 5, 013806 (2021).
[3] http://www.data-assimilation.
riken.jp/jp/events/riken_da_tr_
2020/index.html

225

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Data integration between experiments andcalculations: the new stages
Munehisa MATSUMOTO
Institute of Materials Structure Science, High Energy Accelerator Research Organization
Oho 1-1, Tsukuba 305-0801

We have been working on magnetic materials made of transition metals and rareearth elements. Since magnetism is a relatively low-energy phenomenon coexisting withhigh-energy properties of conducting electrons
in the metallic parts, fundamental problems
caused by the dichotomy between localized
magnetic moments and delocalized electrons
is already implied. On top of this, we encounter the multiple-scale problem where theintrinsic properties determined on the basis of
atomic-scale structure is combined with extrinsic properties controlled by the microstructure
to yield the macroscopic properties of magnetic
materials. They both involve different layersof physics and we have accordingly used combined approaches such as LDA+DMFT [1] toaddress the magnetism of localized f -electrons
embedded in the metallic environments. Herea quantum impurity problem is solved withquantum Monte Carlo method within the dynamical mean field theory (DMFT), and therealistic electronic structure is addressed withdensity functional theory based on local density approximation (LDA). In an analogous
spirit, we have worked on a computational
scheme where the electronic structure calculations for metallic ferromagnets and the input structure information taken from the Rietveld analysis of neutron diffraction data proceed via feedback to each other, which is tentatively termed “LDA+Rietveld” [2]. Here theexperimental data play the role of an effective
self-energy in the language of LDA+DMFT.

226

Both approaches can be considered as developments for data integration of different types.
The LDA+DMFT was originally developed forthe simulation of strongly correlated electron
systems which may be considered as a prototype to bridge over multiple scales in thetarget systems, which is often encountered inphysics and materials science. While the pastfiscal year 2020 was dominated by the serious
pandemic problem, remote working and online learning tools have significantly improved
which helped us to import several techniquesfrom experts outside of our conventional discipline. This included the data assimilation
techniques in weather forecast where unpredictable phenomenon coming from nonlinear
dynamics can be put under numerical control
by combining a limited number of observatory
data and relatively abundant simulation data.
This methodology adapted into the materials
science might help the upcoming materials design and discovery to be done in an accelerated
and predictable way, prospectively including
a more comprehensive data integration withsample-fabrication processes. Further developments are in progress.

References[1] MM, Phys. Rev. Materials 4, 054401(2020).
[2] MM, T. Hawai, K. Ono, Phys. Rev. Applied 13, 064028 (2020).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Co-equivalent of Ce in 4f -3d intermetallics
Munehisa MATSUMOTO

Rare-earth permanent magnets based on
Nd-Fe-B alloys have been widely used and expected to be even more of the key material in
the upcoming decades. The weak anisotropy
field at high temperatures and the relatively
low Curie temperature of the main-phase compound, Nd2 Fe14 B, sometimes require supplementary rare metals in order to put the material in practical use. Since such rare metals
are expensive and not always straightforwardly
available, we have been in urgent quest forgood ferromagnets on which permanent magnets may be developed in a cost-effective, robust, and sustainable manner. In this regard,
clarification of the potential utility of Ce canbe of a help. Indeed from the viewpoint ofsolid state physics, many interesting phenomena associated with Ce, such as valence fluctuations, heavy fermions, and unconventional
superconductivity, have been known. Some of
the fundamental ideas can help in answering
the problems posed from material science.
We have looked into the potential utility of
Ce for most of the representative propertiesof a ferromagnet to qualify as a constituent
of a permanent magnet, namely, magnetization, magnetic anisotropy [1], Curie temperature, and structure stability. Among all theseproperties, we have observed that the largest
merits actually seem to originate in the valence fluctuations, in particular the contribution from Ce4+ states to the bulk properties.
One of such aspects can be illustrated with
an effect of Ce substitution in SmFe12 [2]: wecan computationally get an analogue of the
Slater-Pauling curve with the Ce-substituted
ferromagnets. The magnetization of the Febased ferromagnet shows a peak as a function

227of the concentration of dopants, typically Co.
Remarkably, the same thing can happen evenwhen the dopant is Ce.
Obviously it is hard to observe this phenomenon in real experiments. There seems
to be a strict constraint on the inter-atomic
distance between the rare-earth sublattice andthe transition-metal sublattice in order for the
delocalized 4f -electron to contribute to thebulk magnetization that is mostly made of 3delectrons. Especially for Nd2 Fe14 B with therelatively inflated lattice, extracting the meritof Ce with the Slater-Pauling analogue is notstraightforward. Nevertheless there has beensome actual observation [3] confirmed bothexperimentally and computationally. Several
findings as exemplified by these cases point tosome hope for promising ferromagnets with reduced costs. So far we identified and understood several singular cases. Systematic quest
to pop up further candidates on the basis ofdata assimilation between theory and experiments are in progress.
Helpful discussions with K. Saito, T. Ueno,
and H. Shishido through the JSPS KAKENHI
15K13525 project are gratefully acknowledged.

References[1] H. Shishido et al., arXiv:2103.10202.
[2] MM, T. Hawai, K. Ono, Phys. Rev. Applied 13, 064028 (2020).
[3] X. Tang et al., Acta Materialia 175, 1(2019).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Finite temperature properties of frustrated systems
Tsuyoshi OKUBO
Department of Physics, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 133-0033

A variety of exciting phenomena, including non-collinear magnetic order, magnetization plateaus, and spin liquids, occur in thefrustrated spin systems. Frustrated interactions often appear as geometrical frustrations
based on the antiferromagnetic interaction on
triangular units. Another origin of the frustration might be the competition of several interactions, such as the J1 -J2 model on the squarelattice. The honeycomb lattice Kitaev model
could be considered as an example of the latter frustration [1]. In the Kitaev model, theinteractions are Ising type, Siγ Sjγ , and the spincomponent γ = x, y, z is determined from thedirection to the neighboring site. The Kitaev
model is exactly solvable, and its ground stateis known to be a spin liquid without long-range
magnetic order. Such Kitaev interaction could
appear in the realistic situation through thestrong spin-orbit interaction [2]. α-RuCl3 is
an example of such a Kitaev compound. In
this compound, the ground state is not the
spin liquid: it is a magnetically ordered state.
However, when we apply a magnetic ﬁeld, thecompound looks show the spin-liquid-like behaviors. In particular, a half-integer thermal
Hall conductivity was observed at ﬁnite temperature [3], indicating the appearance of Kitaev spin liquid.
In this year’s project, we investigated ﬁnite
temperature properties of the Kitaev modelwith oﬀ-diagonal interactions motivated by the
recent experiments on a Kitaev compound.
The model Hamiltonian is given as∑h ∑ x(S + S y + S z ), (1)H=
Hγ − √3 iγ∈x,y,zwhere for γ = z,∑
[KSiz Sjz + Γ(Six Sjy + Siy Sjx )Hz =⟨i,j⟩z+ Γ′ (Siz (Sjx + Sjy ) + (Six + Siy )Sjz )].
(2)
In the cases of γ = x, y, we consider similarinteraction with cyclic rotation of x, y, z components. To numerically calculate the physicalquantities at a ﬁnite temperature, we represent the system’s density matrix as a tensor
network and optimize its elements.
Firstly, we considered pure ferromagnetic
Kitaev model (K = −1, Γ = Γ′ = 0 and
h = 0) in the thermodynamic limit. In ourprevious calculation using the inﬁnite tensor
product operator (iTPO) tensor network, wehave found that the accuracy at the low temperature is not suﬃcient; we could not quantitatively reproduce the low-temperature speciﬁc heat peak previously calculated by quantum Monte Carlo [4]. In this year, we considered a cluster optimization of the tensor to improve the accuracy. In the standard optimization based on the imaginary time evolution,
we perform Suzuki-Trotter decomposition andonly optimize two sites simultaneously (simple update). In the new cluster optimization,
we consider the imaginary time evolution ofsix sites and optimize them simultaneously. In
Fig. 1, we plot thus obtained speciﬁc heat for
the Kitaev model in the thermodynamic limit.
Although both the simple update and the cluster optimization reproduce two expected peakstructures of the speciﬁc heat, the lower peakheight is largely increased by using the cluster

228

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

optimization. Because the speciﬁc heat calculated by unbiased QMC shows a higher peakthan the present data obtained by the cluster
optimization, the accuracy is still not enough.
However, we hope it will be improved when we
consider larger bond dimensions in the future.

0.2

Simple update
Cluster update

imental observation [3]. We also investigatedthe eﬀect of the weak Γ and Γ′ terms, and we
found that depending on the sign of Γ and Γ′ ,the thermal Hall conductivity is largely modiﬁed from that of the pure Kitaev model.
A part of this work has been done in collaboration with J. Nasu, T. Misawa and Y. Motome.

References

0.15[1] A. Kitaev: Ann. Phys. 321 (2006) 2.

0.1[2] G.
JackeliandG.
Khaliullin,
Phys. Rev. Lett. 102 (2009) 017205.

0.05[3] Y. Kasahara, T. Ohnishi, Y. Mizukami, etal., Nature 559 (2018) 227.

0[4] J. Nasu, M. Udagawa, and Y. Motome:
Phys. Rev. B 92 (2015) 115122.

0.001

0.01

0.1

1

10

100

[5] H. Li, D.-W. Qu, H.-K. Zhang, et al.
Phys. Rev. ResearchBw 2 (2020) 043015.
Figure 1: Speciﬁc heat of the inﬁnite Kitaev
model calculated by iTPO method. (open circle) Speciﬁc haet calculated by the standard
simple update. (ﬁlled circle) Speciﬁc heat calculated by the new cluster optimization.
Secondary, we investigated the thermal Hall
conductivity under a magnetic ﬁeld. As wediscussed, the accuracy of the inﬁnite size simulation is still insuﬃcient. Thus, we calculated
the thermal Hall conductivity for the ﬁnite size
cluster, and the density matrices are represented by matrix product operators (MPO) instead of iTPO. It has been demonstrated thatby using such MPO representation, indeed, one
can calculate ﬁnite temperature properties of
the Kitaev model very accurately [5]. By using
this MPO representation, we successfully calculated the thermal Hall conductivity undera magnetic ﬁeld. For the pure Kitaev model,
the thermal Hall conductivity has a peak at aﬁnite temperature, and it overshoots the halfquantized value; it is consistent with the exper-

229

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Conformation of ultra-long-chain fatty acid in lipid
bilayer
Kazutomo KAWAGUCHIa , Koh M. NAKAGAWAb , Satoshi NAKAGAWAa ,Hideo SHINDOUc , Hidemi NAGAOa , and Hiroshi NOGUCHIba
Institute of Science and Engineering, Kanazawa University,
Kanazawa, Ishikawa 920-1192, Japanb
Institute for Solid State Physics, University of Tokyo, Kashiwa, Chiba 277-8581
cDepartment of Lipid Signaling, National Center for Global Health and Medicine,
Shinjuku-ku, Tokyo 162-8655, Japan; Department of Lipid Science, Graduate Schoolof Medicine, University of Tokyo, Bunkyo-ku, Tokyo, 113-0033, Japan

In living cells, the most abundant lipids
are phospholipids, which have a polar headgroup and two hydrocarbon tails. Each tailtypically contains between 14 and 22 carbon
atoms. Around C22 fatty acids such as docosahexaenoic acid (C22:6, DHA) are calledvery long-chain fatty acids (VLCFAs). Moreover, much longer chains, called ultra-longchain fatty acids (ULCFAs), with 32 to 36
carbons with 6 double bonds were found at
the sn-1 position of phosphatidylcholine (PC)in photoreceptors, spermatocytes, fibroblasts,
and keratinocytes. However, the biosynthestic mechanisms and biological roles of ULCFAs
have not understood yet. In this study, we examined the conformation of one of ULCFAs,
dotriacontahexaenoic acid (C32:6) containing
phosphatidylcholine (dTSPC, C32:6-C18:0), in
phospholipid bilayers using all-atom molecular
dynamics simulations [1].
One dTSPC is embedded in the lipid bilayer
consisting of one of the following three lipids:
Distearoyl PC (DSPC, C18:0-C18:0), StearoylDHA PC (SDPC, C18:0-C22:6), and stearoyloleoyl PC (SOPC, C18:0-C18:1). Moreover, we
examined the effects of the difference in lipid
density between the two leaflets.
We found that the ultra-long tail of the ULCFA flips between two leaflets and fluctuates
among an elongation into the opposite leaflet,lying between two leaflets, and turning back.
The time scale of the conformational change
between the elongated and turned shapes is ∼230

10 ns, so that it is quite fast. The ratio of thesethree states depends on the lipid-density difference between the two leaflets. The sn-1 chain is
located at the opposite leaflet more frequently,
as the lipid density of the opposite leaflet relatively decreases. We have clarified the linear
relationships between the position of the sn-1
terminal of dTSPC and the lipid-density difference in all three types of membranes.
The main difference among the three types
of host lipids is the number of the double
bonds, and clear effects appear in the orderprofiles. Nevertheless, the conformation of dTSPC exhibits no qualitative differences. A minor influence is found in the distribution of C32
of dTSPC. Different shapes are obtained between SDPC and the others, whereas those of
C18 and C3 are not. In the SDPC membrane,
C32 has a rounded triangular distribution. In
contrast, a small peak or shoulder shape appears for the DSPC and SOPC membranes.
As described above, we revealed that ULCFA can sense and rapidly respond to thelipid-density difference to reduce such a difference. This behavior may be essential for thefunctions of ULCFAs in living cells.

References[1] K. Kawaguchi, K. M. Nakagawa, S. Nakagawa, H. Shindou, H. Nagao, and H.
Noguchi: J. Chem. Phys. 15, 165101(2020).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Giant magnetic response of hidden SU(2) symmetricantiferromagnets induced by impurity disorder
Hidemaro SUWA
Department of Physics, University of Tokyo
Hongo, Bunkyo, Tokyo 113-0033

In the research area of antiferromagnetic(AFM) spintronics, one of the most fundamental and challenging subjects is the efficient
manipulation of the AFM order parameter.
The key to extreme susceptibility lies in twodimensional (2D) systems with spin isotropy.
Although the ground state typically has a longrange order, any continuous symmetry is notbroken at finite temperature in a 2D systemwith short-range interactions, according to theMermin-Wagner theorem. As a result, themagnetic susceptibility exhibits an exponential divergence in the low-temperature region.
Here the strongest divergence is obtained in
the presence of the spin isotropy.
To achieve a giant magnetic response, wehave proposed exploiting the hidden SU(2)symmetry built in a spin-orbit system [1]. The
large spin-orbit coupling of iridates gives rise toJeff = 1/2 quantum states and pins the Jeff =1/2 pseudo-spins on the IrO6 octahedral network. The octahedral rotation around the axis
perpendicular to the plane can lead to a canted
in-plane magnetic order and a linear coupling
to uniform magnetic fields without breaking
the spin isotropy. This hidden SU(2) symmetry is revealed by a staggered rotation of thespin reference frame under the frustration-free
condition of the Dzyaloshinskii-Moriya interaction. Nevertheless, real materials have otherperturbations to the pure 2D spin isotropic system: in particular, spin anisotropy introducedby the mixing with the Jeff = 3/2 orbitals. For
efficient manipulation of the AFM order, it is

crucial to make the perturbations smaller thanthe external fields we control.
We have shown that the AFM tunability
can be systematically and significantly enhanced by introducing magnetic dilution anddiminishing the spin anisotropy effect in the
2D antiferromagnets. We used ISSP System B
and C in class C projects (ID: 2020-Ca-0097,
2020-Cb-0091) and calculated the large-scalequantum spin system consisting of morethan one million spins using ALPS/looper(http://github.com/wistaria/alps-looper).
Hybrid parallel computation was performed
using up to 3,456 cores. We numericallyshowed that the non-magnetic substitution
significantly suppresses the spin stiffness.
Therefore, the perturbation of the controllable
magnetic field, quantified by the ratio of
the Zeeman energy to the intralayer spin
stiffness, is significantly enhanced and dominant over the other perturbations. We haveaccomplished an extreme response of SU(2)symmetric AFM fluctuations in a diluted
system close to the percolation threshold. The
quasi-2D system of iridates thus represents a
prototype of the magnetic dilution problem in
2D pseudo-spin-half antiferromagnets, leading
to a tunability of effective spin anisotropy.

References[1] L. Hao, D. Meyers, H. Suwa, et al., Nat.
Phys. 14, 806 (2018)

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of Thermal Functional Materials Using
Materials Informatics
Junichiro SHIOMI
Department of Mechanical Engineering,
The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8656
principles lattice dynamics, the Monte Carlo

The ability to effectively reduce a material’s
its

ray-tracing method, and effective medium

electrical properties unchanged is the ultimate

theory was used to understand the mechanism

goal for thermoelectric materials. Due to theofrelative difference in the mean free paths

nanostructured silicon as well as the weak

(MFPs) of electrons and phonons, introducing

temperaturenanostructures can effectively scatter phonon

conductivity values as well as its temperature

while affecting less to the electron transport.

dependence

For example, the thermal conductivities ofexperimental measurements.

thermalconductivity

nanostructured

whilematerials

likekeeping

phonontransportindependence.
are

also

The

verified

multiphasethermalby

thesuperlattice,nanowire, and nano-porous material are about
one or two orders of magnitude lower than thebulk counterpart.
On the other hand, Silicon also has many
allotropes other than the commonly seen
diamond phase (referred to as Si-I phase) andhas nature low thermal conductivity. Underhigh pressure, it can also form the bodycentered cubic (BC8, referred to as Si-III)phase and rhombohedral (R8, referred to as SiXII) phase as well as many other intermediate

Figure 1(a) Bulk thermal conductivity of Si-I, Si-III, andphases. How those multiphase nanostructure

Si-XII phases of silicon ure (b) The thermal conductivity

will affect the thermal conductivity remains

spectrum as a function of effective mean free (c) The effective

unknown.

thermal conductivity of nanograin Si-I, Si-III, and Si-XII at

In this work, we utilized a multiscalemodeling

techniquethat

includingdifferent temperature. (d) The effective thermal conductivity

first-of multiphase nanograined silicon as function of temperature.

232

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

The bulk phonon properties of the three

a temperature-independent behavior. This weakphases are shown in Fig. 1(a), which aretemperature dependence suggests that thecalculated from anharmonic lattice dynamics

phonon-boundarywith interatomic force constants from first-

temperature-independent process in the elastic

principle calculations. The bulk phonon thermal

regime, is the dominate process that limits the

conductivities of these three phases of silicon

thermal transport. To further verify theare quite high, which is unfavored for thesimulation, we also compared the simulation

thermoelectric energy conversion. Even for the

results with the experiment measurements, and

Si-III phase, which has the lowest thermal

the results are shown in Fig. 1(d). The inputs

conductivity among the three phases, theparameters like the volume fractions and thethermal conductivity is still above 10 W/mK at

averaged grain sizes are extracted from theroom temperature. Base on the Monte Carlosamples, and the good agreement between the

ray-tracingthat

simulations and the experimental measurements

introducing nanograin is an efficient way tosuggests the prediction power of our multiscale

reduce its lattice thermal conductivity. Taken

modeling scheme.

simulations,

we

found

scattering,

which

is

a

the Si-phase as an example [Fig. 1(b)], wefound that with the decreasing in the grain sizes,

References

both the effective mean free path and the[1] C. Shao, K. Matsuda, S. Ju, Y. Ikoma, M.

thermal conductivity will be shifted to low

Kohno, & J. Shiomi, Journal of Appliedvalues. The effective thermal conductivity the

Physics, 129(8), 085101 (2021)

nanograined

siliconasafunctionoftemperature is shown in Fig. 1(c), which shows

233Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Efficient Sampling Simulation of
the Soft Modes Significantly Contribute to Protein Properties
K. TAKEMURA, D. TRAN, K. TAKABA, M.M. SOBEH, Y. MIYAZAWA, R. KIUCHI,
T.N. WIJAYA, T. OGAWA, Y. TAIRA, R. MISU, and A. KITAOSchool of Life Science and Technology, Tokyo Institute of Technology
Ookayama, Meguro, Tokyo 152-8550
As an efficient conformation sampling

sampled during previous cycles of eePaCS-

method, we previously developed parallel

MD and solving the “convex hull problem”

cascadeprovide the edges and vertices.

selection

molecular

dynamics(PaCS-MD) [1]. PaCS-MD consists ofcycles of multiple independent short MD
simulations. The initial structures of eachcycle were selected as the closest structures
to a target structure based on suitableproperties

such

as

root-mean-square-

deviation (RMSD), center-of-mass distance.
These selections increase the probability ofrare event occurrences, and PaCS-MD
enhances conformation sampling without
external perturbations.

Fig. 1 Schematic illustration of the evolution

One problem in the original PaCS-MDof the vertices and edges in eePaCS-MD.

is a requirement prior knowledge of thetarget structure. To address this issue, we
proposededge

expansion

The sampling efficiency of the method

PaCS-MD

can be examined by conducting eePaCS-MD(eePaCS-MD) [2]. As illustrated in Fig. 1,

from one state and examinimg whether theeePaCS-MD

initialsampled conformations contain the target

structure (black cross). The initial structures

structures or not. For this purpose, we appliedof each cycle are randomly taken from theeePaCS-MD to open-close transitions (Fig.2)

vertices (stars) of a multi-dimensionalof

principal

componentThemaltose/maltodextrin binding protein (MBP),

subspaceconsists

conformations

adenylate kinase (ADK). We conducted

requires

only

the

subspace.
of234

glutaminebinding

protein(QBP),

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

eePaCS-MD from both open and close states.

the close state when simulations started fromthe open state). For QBP and MBP, closeopen transitions were also successfully
sampled.

We

also

showedthatthecombination of eePaCS-MD and accelerated
MD(eePaCS-aMD) achieved

improvementofsampling

a furtherefficiency.

Minimum RMSD (RMSDmin), time to reach
RMSDmin (tmin), and the total computational
cost used to reach the opposite state for the
first time (T1st) of eePaCS-aMD are shown in
Table 1. OC and CO represent open to closeand close to open transition, respectively. As
shown in Table 1, open to close transitions
were observed within 10 ns, which is several
orders of magnitude shorter simulation timethan conventional MD. Thus, eePaCS-MD isa very efficient sampling method that does
not require prior knowledge.
Table 1 Summary of results (eePaCS-aMD)
TargetQBP (OC)QBP (CO)MBP (OC)MBP (CO)ADK (OC)ADK (CO)Fig. 2 Structures of target complexes. (A)Glutamine
Maltosebindingbinding

protein(QBP).

(B)

protein(MBP).

(C)

Adenylate kinase (ADK). Structures colored

RMSDmin (Å)
1.3
1.3
1.2
1.3
1.9
3.2

tmin (ns)
4.9
6.4
6.7
7.2
8.9
9.3

T1st (ns)
40.4
52.8
41.6
49.4
114
-

Referencesin black and white correspond to close and[1] R. Harada and A. Kitao. J Chem Phys 139,

open states, respectively.

035103 (2013).
[2] K. Takaba, D.P. Tran and A. Kitao. J

For all targets, eePaCS-MD efficiently

Chem Phys 152, 225101 (2020).

sampled open-close transitions (generated
conformations containing structures similar to235

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Anderson-Kitaev spin liquid
Masahiko G. YAMADA and Satoshi FUJIMOTO
Department of Materials Engineering Science, Osaka University
Toyonaka, 560-8531, Japan

More than half a century, the Anderson
localization has been investegated intensively
on the low-dimensional electron systems or
fermionic systems. Normal magnets with along-range order does not have a fermionic excitation, and thus the randomness effect has
been investigated in a different manner. On
the other hand, in Kitaev spin liquids excitations are described by Majorana fermions,and the Anderson localization of Majorana
fermions can be expected. We name this new
localized state Anderson-Kitaev spin liquid.
This state potentially explains the experimental observation in α-RuCl3 or A3 LiIr2 O6 with
A = H, D, Ag.
We discovered Anderson-Kitaev spin liquidin the bond-disordererd Kitaev model witha numerical simulation. In the presense ofa magnetic field, we need to recompute theflux gap of the disordered Kitaev model inthe third-order perturbation. We compute
this quantity in two methods. One is the exact diagonalization of the Majorana one-body
Hamiltonian, and the other is the kernel polynomial method. Especially, the kernel polynomial method is very much suitable for theparallel computing, and we implement a hybrid parallelization code for this algorithm fora large-scale simulation. We note in the small
scale two methods agree well.

a rapid decay as the disorder strength grows.
After the extrapolation, the region where thethermal Hall conducitivity is quantized disappears when only 5% disorder is added. These
results are published in npj Quantum Materials [1].
Overall we discover the new Anderson transition into an Anderson-Kitaev spin liquid
thanks to the supercomputer in the Institutefor Solid State Physics. The calculation has
been done in the manner suitable for the supercomputer based on our newly establishedmethod.

References[1] M. G. Yamada: npj Quantum Mater. 5(2020) 82.

With a massive parallel computation, we
succeed in computing the flux gap, andhence the thermal Hall conductivity up to aO(10000)-site system for the bond-disordered
Kitaev model. In the 100 × 100 honeycomb
lattice, the thermal Hall conductivity shows236

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Analyses on complex fluids using multiscale simulation
platform
Ｙohei MORII and Toshihiro KAWAKATSU
Department of Physics, Tohoku University, Sendai, Miyagi 980-8578
We have been developing a simulation platform

The obstacle is an elastic cylinder that rotates

named Multiscale Simulation Platform forwith a rotation rate (i.e. the speed at the surface

complex fluids (MSSP), with which one canof the obstacle/flow speed) 1.0, and thesimulate macroscopic complex flows coupled

Reynolds

with microscopic molecular simulators. MSSP

number 4.0, respectively.

uses smoothed particle hydrodynamics (SPH)

SPH particles, each of which contains 1000

method, where each hydrodynamic particle

FENE dumbbells. As a result, total number ofcontains microscopic molecular simulator or

dumbbells are 230,000,000.

microscopic stress calculator.

We can confirm that the rotation of thenumber

40.0,

andWeisenberg

We used 230,000

In this project, we implemented moving

obstacle induces an asymmetric flow patternboundary conditions into MSSP so that we canaround the obstacle, and that the dumbbells are

simulate moving and deforming objects such as

strongly stretched at the obstacle surface, which

floating filler particles and deformable vesicles

is the origin of the nonlinear behavior of the[1].

viscoelastic fluid.

Figure 1 shows several characteristic flow

We also develop a simulation technique withproperties of a viscoelastic fluid passing by awhich one can simulate an elastic membrane,

rotating cylindrical obstacle. The viscoelastic

i.e. a vesicle, in a channel flow.

fluid is modelled as a Newtonian fluid where

preliminary work for simulating red blood cells

many dumbbells, i.e. each consists of two

in a blood Bessel.

particles connected by a finite extensible

References

nonlinear elastic (FENE) spring, are immersed.

[1] Y.Morii and T.Kawakatsu, in preparation.

This is a

Figure 1: A FENE dumbbell flow around a rotating cylindrical obstacle. (a) Flow field,(b) pressure distribution, and (c) orientation distribution of FENE dumbbells.

237

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Topological Order and Quantum Dynamics inQuantum Many-body Systems
Synge TODO
Department of Physics, University of Tokyo, Tokyo, 113-0033
Institute for Solid State Physics, University of Tokyo, Kashiwa, 277-8581

We have developed various novel numerical methods for quantum/classical many-bodysystems with strong correlations and performed large-scale simulations on ISSP supercomputer systems.
Rokhsar and Kivelson proposed the quantum dimer model in 1988 as a low-energy eﬀective model for frustrated magnets. Although
there is no negative sign problem in the Hamiltonian of the quantum dimer model, Monte
Carlo simulations are challenging because of
the strong geometrical restriction on the conﬁguration of the dimers. With the help of eﬃcient cluster update based on stochastic series
expansion, we now extend our simulation to amore general class of models, including dimers
and monomers and multiple interactions between them. It can include a larger Hilbert
space based on the quantum dimer model, under the same framework of Monte Carlo simulation and update techniques, by which we
can detect the deconﬁnement of monomers
under the ﬁnite temperature phase transition(Fig. 1). We also implemented the exchange
Monte Carlo method on the quantum dimer
model to make a winding number-free simulation, with the kinetic terms to break a dimer
into two monomers and still obtain the measurements for only dimer conﬁgurations.
In the meantime, the real-space renormalization group method using tensor networks
has recently been widely used as a numerical method for many-body spin systems. The
tensor network method can eﬃciently com-

Figure 1: Deconﬁnement of monomers in quantum dimer model.
pute the physical quantities of large-scale classical and quantum systems. However, existing methods, such as TRG and HOTRG, havea problem that the computational complexity becomes enormous as the spatial dimension increases. Our proposed Anisotropic Tensor Renormalization Group can dramaticallyreduce the computational complexity of highdimensional systems such as three-dimensional
quantum systems. Furthermore, by extending
the tensor network to include tensors not only
on the vertices but also on the lines connecting the vertices, the accuracy of the real-space
renormalization method can be increased bya factor of 100 compared to existing numerical methods that require a similar amount ofcomputation time.

238

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Confirmation of stress-overshoot phenomena under biaxial
elongational flow of ring-linear mixtures
Katsumi HAGITA1 and Takahiro MURASHIMA2
1

Department of Applied Physics, National Defense Academy, Yokosuka 239-8686
2

Department of Physics, Tohoku University, Sendai 980-8578

Recently, we have studied (linear-rich) ring-

complexes such as catenanes and bonded-rings

linear mixtures [1,2] using Kremer-Grest (KG)

consist of two or three rings per complex as[3] bases coarse grained molecular dynamics

shown in Fig. 1. We studied the cases with

(CGMD) simulations. To study linear-chain(Nlinear, Nring) = (160,40), (160,80), (160,120),

penetrations into rings, we performed topology(160,160), (40,160), (10,160) and ring fraction

analyses based on the Gauss linking number

was fixed to be about 0.1. Here, Nlinear and Nring(GLN) for all pairs of linear and ring polymers.

denotes number of beads per a linear chain and

The probability distributions of the number ofa ring, respectively. To keep enough statisticallinear chain penetrations per ring (nP) wereprecisions, we used large system sizes withevaluated. We have investigated the possibility

approximate 0.7 M beads. As the initialof increase of nP by some conditions in order torelaxation run, we performed a tun with 109

make rings to work as a movable cross-linkers.

MD steps for each system. As the MD solvers,

In the preliminary simulations at the last

we used LAMMPS [5] for preparations at theyear, we discovered the increase of nP under

ISSP supercomputer. At later we also usedbiaxial elongational flows [4]. Here, we used

HooMD-bule [6] on the GPUs for continuous

our extended uniform extensional flow (UEF)

product runs.

method [5]. We also discovered the stressovershoot under the biaxial elongational flows.
Although the stress overshoot under uniaxial
elongational flows were reported, that under
biaxial elongational flows had been not. Thus,
we proposed the D-Class project to publish apaper as quickly as possible.
In the proposed D-Class project, we started
systematic preparation of ring-linear blends.

Fig. 1: Schematics of single ring, bonded-rings,

Here, we treated uncatenated rings and ring

poly-catenanes and ring-linear mixture.

239

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

In the present project, we developed amethod to estimate nP by using GLN. Here, theends of linear chains are virtually connected toeach other, but we prepared an extra linear
chain and connected it to the original linear
chain to form a cyclic chain as explained in ourwork [1,2]. For computation of GLN among
cyclic chain and ring polymer, we used theTopoly Python package [7]. Figure 2 shows theprobability

distributionsoflinearchainspenetrating into a single ring with (Nlinear, Nring)

Fig.

3:

Stressovershootunderbiaxial= (160,40), (160,80), (160,120), (160,160).

elongational flows. (Nlinear, Nring) = (160,40)

References[1] K. Hagita and T. Murashima: Polymer 218(2021) 123493.
[2] K. Hagita and T. Murashima: Polymer 223(2021) 123705.
[3] K. Kremer and G. S. Grest: J. Chem. Phys.
92 (1990) 5057.
[4]T.

Murashima,

K.

Hagita,andT.

Kawakatsu: Under review in Macromolecules.
[5]T.

Murashima,

K.

Hagita,andT.

Fig. 2: Probability distributions of linear chains

Kawakatsu: Nihon Reoroji Gakkaishi (J. Soc.

penetrating into a single ring with (Nlinear, Nring)

Rheol. Jpn.), 46 (2018) 207.

= (160,40), (160,80), (160,120), (160,160).

[6] S. Plimpton: J. Comp. Phys. 117 (1995) 117.
[7] J. A. Anderson, et. al.: Comput. Mat. Sci.
173 (2020) 173, 109363

In this project, we also performed deformed
simulations with the deformation rate of 0.001[8] P. Dąbrowski-Tumański, et. al.: Brief.

in order to grub preliminary results. As results,

Bionformatics (2020) bbaa196.

we obtained the key result for biaxial
elongational flows as shown in Fig. 3.

240

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Frustration-induced symmetric skyrmion lattices
in three dimensions
K. MITSUMOTO1, R. OSAMURA2, K. AOYAMA2 and H. KAWAMURA1
1

Molecular Photoscience Research Center, Kobe University, Kobe 657-8501
2

Graduate School of Science, Osaka University, Toyonaka 560-0043

Considerable attention has recently been paid

dimensional (3D) with certain amount of

to “skyrmion”, a topologically stable nano-scaleinterlayer coupling. In this year’s project, we

spin texture, both from fundamental interest ofinvestigate the properties of the possible

topology and also from possible application toskyrmion and skyrmion lattice in 3D, by

spintronics. In the usual situation, skyrmion andperforming extensive Monte Carlo simulations“skyrmion lattice” are stabilized in the non-on the frustrated classical Heisenberg model on

centrosymmetric magnets without the inversion

the 3D stacked-triangular lattice. We investigate

center via the anti-symmetric Dzyaloshinskii-

by means of extensive Monte Carlo simulations

Moriya (DM) interaction, which energeticallyboth (i) the short-range interaction model

discriminates

spirals.

mimicking insulators, i.e., J1-J3-J1c Heisenberg

Meanwhile, it was proposed in Ref.[1] that themodel, and (ii) the long-range RKKY interaction

symmetric skyrmion and skyrmion lattice might(falling with 1/r3) model mimicking metals.

“right”

and“left”

be stabilized in centrosymmetric magnets withIn the short-range model (i), the transition

the inversion center by the frustrated exchange

behavior of the 3D model turns out to be similarinteraction. Examples might be the J1-J3 (J1-J2)

to that of the 2D model for the ferromagnetic

Heisenberg magnet on the two-dimensional

interlayer coupling, exhibiting the skyrmion(2D) triangular lattice under magnetic fields. In(anti-skyrmion)-lattice state, while, for thesuch frustrated magnets, in contrast to the DM

antiferromagnetic interlayer coupling, the naturecase, “right” and “left” spirals are energeticallyof the skyrmion-lattice state changes somewhat.

equivalent, and the skyrmion with both signs ofIn the RKKY model (ii), we also find thethe scalar chirality (or the topological charge) isskyrmion-lattice state, which, however, seems topossible, giving rise to both the skyrmion andaccompany an exotic replica-symmetry breaking

anti-skyrmion lattices. Interestingly, skyrmion(RSB) unlike the short-range model.

and anti-skyrmion lead to the topological Hall
effect of mutually opposite signs.
Realmagnets

areofcourse[1] T. Okubo, S. Chung and H. Kawamura, Phys.
Rev. Letters 108, 017206 (2012).

three-

241

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Rotational dynamics of water molecules on the lipid
membranes
Yuji HIGUCHI
Institute for Solid State Physics, The University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

We calculate the rotational relaxation ofwater molecules on the lipid membranes
with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) head groups. The
relaxation is faster in PE than that in PC(Fig. 1), which is consistent with the previous
experiment [4]. To reveal the mechanism of
the diﬀerent relaxation, hydrogen bond (HB)
networks among water molecules are analyzed.
The number of HBs in PE is less than that in
PC. The PE head group is strongly hydrated,which breaks the HB network. In contrast, theweaker hydration around the PC head groupdoes not break the HB network. In DFTB-MD
simulation, the head groups of PC and PE aremodeled as N(CH3)4+ and NH4+, respectively.
The rotational relaxation of water molecules
and the number of HBs around ions are consistent with those on the lipid membranes, conﬁrming the mechanism. Thus, we successfully
reveal the atomistic mechanism of the diﬀerent

water dynamics on the lipid membranes [5].

Rotational relaxation

We have studied the structures and properties of soft matter. We revealed the fracture processes of semicrystalline polymers [1]by coarse-grained molecular dynamics simulations. Understanding the mechanical properties is essential to improve the toughness ofpolymeric materials. This year, we study thewater dynamics on the lipid membranes, which
are considered as a model system for biological membranes. All atomic molecular dynamics (MD) simulations are performed on System
B and C using the LAMMPS program [2] andDFTB+ software [3].

1.0
0.8

PC
PE

0.6
0.4
0.2
0.0
0

10

20
30
Time (ps)40

Figure 1: The rotational relaxation of watermolecules just above the lipid membranes. Ten
trajectories are shown, which conﬁrms the signiﬁcant diﬀerence.

References[1] Y. Higuchi: Phys. Rev. E 103 (2021)
042502.
[2] S. Plimpton:(1995) 1.

J. Comput. Phys. 117[3] B. Hourahine, et al.: J. Chem. Phys. 152(2020) 124101.
[4] M. Hishida, K. Tanaka, Y. Yamamura,and K. Saito, J. Phys. Soc. Jpn. 83 (2014)
044801.
[5] Y. Higuchi, Y. Asano, T. Kuwahara,
and M. Hishida: Langmuir (2021). DOI:
10.1021/acs.langmuir.1c00417

242

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

FRG study on realization of the Kitaev quantum
spin liquid in condensed matter physics
Kiyu FUKUI, Yukitoshi MOTOME, and Yusuke KATO
Department of Physics, The University of Tokyo, Bunkyo, Tokyo 113-0033
Department of Applied Physics, The University of Tokyo, Bunkyo, Tokyo 113-8656
Department of Basic Science, The University of Tokyo, Meguro, Tokyo 153-8902

Frustrated quantum spin systems have beenstudied intensively for very long time. In
general, however, it is impossible to solve
them exactly mathematically. Therefore, numerical approaches to investigate them areindispensable. Numerical approaches usedwidely to study them are, for example, exact diagonalization (ED), quantum Monte
Carlo (QMC), density matrix renormalizationgroup (DMRG). Each method has pros andcons, of course. Since 2010s, a new method
called pseudo-fermion functional renormalization group (PFFRG or pf-FRG) has been usedgradually [1]. Although PFFRG overestimatesordering tendencies to magnetic orders [2],it can treat large-size systems and stronglyfrustrated systems and detect quantum paramagnetism due to strong frustration. We done
two studies on the feasibility of the Kitaev
quantum spin liquid by PFFRG [3].
The first one is the study on the feasibilityof it in ultracold molecular systems trappedin the optical lattice rather than in solids. We
define dipolar Kitaev model on the honeycomb
lattice as
1∑ 1
H=−
3
2
3rij
i̸=j

(1)

i,j

4π x x)]Si Sj
3
2π y y+ Jy [1 − 2 cos(2Φij −)]Si Sj
3+ Jz [1 − 2 cos(2Φij )]Siz Sjz },(2)× {Jx [1 − 2 cos(2Φij −based on the realization of Kitaev-type inter-243

actions proposed in 2013 [4]. In the dipolar
Kitaev model, the interactions between thenearest-neighboring sites are consistent with
the Kitaev model, but those between sites farther than the nearest-neighbor are more complicated. We apply PFFRG to this model toinvestigate the ground state at each parameter. The results show that FM order andzigzag AFM order are realized in the FM andAFM dipolar Kitaev model, respectively, forall anisotropy parameters. Furthermore, in order to investigate the connection between the(nearest-neighbor) Kitaev model and the dipolar Kitaev model, we introduce an artificial
range of interactions and calculate the susceptibility when approaching the dipolar Kitaev
model with long-range interactions from the
Kitaev model with only nearest-neighbor interactions. From this calculation, it is clarified
that the spin liquid state realized in the Kitaev model is quickly collapses, as the range
of interactions is extended. After the proposals of Kitaev-type interaction in ultracold polar molecular systems by microwave irradiationin 2013, the calculation based on these proposals has not been performed, and whether
Kitaev quantum spin liquid state is actuallyrealized has remained an open question. We
address this issue with PFFRG and elucidated
the above results for the first time.
The other is the study on the realization of
the Kitaev quantum spin liquid in the highspin materials. We calculate the phase dia-

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

gram of the spin-S Kitaev-Heisenberg model[4] S. R. Manmana et al., Phys. Rev. B 87,
with S = 1/2-5/2 and S = 50. Its Hamilto081106 (2013); A. V. Gorshkov, K. R.
nian isHazzard, and A. M. Rey, Mol. Phys. 111,
1908 (2013).
∑∑[
]
H=A
2 sin(2πξ)Siµ Sjµ + cos(2πξ)Si · Sj .
[5] M. L. Baez and J. Reuther, Phys. Rev. Bµ ⟨i,j⟩µ96, 045144 (2017).
(3)
We apply the extension of PFFRG to treat
spin-S systems proposed in 2017 [5]. The
obtained phase diagrams of the KitaevHeisenberg model for S = 1/2 and S = 1
are in general good agreement with the previous studies by other numerical methods. The
phase diagram for S = 50 is also in good agreement with the previous study on the classicalKitaev-Heisenberg model by Monte Carlo simulation, except for some special points. As aresult of systematic calculations with diﬀerent
S, for S ≤ 3/2, both the AFM and FM Kitaev spin liquid regions have a finite extent.
For S ≥ 2, no region showing Kitaev spin liquid state was found. Therefore, we believethat S = 3/2 gives an upper bound on thespins possessed by the candidate materials inwhich Kitaev quantum spin liquid is realized.
The phase diagram calculation of the KitaevHeisenberg model with a systematic change ofspin S, as we perform here, has not been done
before. This is the first study of the applicationof spin-S PFFRG to the Kitaev-Heisenberg
systems. The results we obtain here provide
a guideline for the recent intensive search forcandidate materials of S > 1/2 Kitaev quantum spin liquid.

References[1] J. Reuther and P. Wölfle, Phys. Rev. B
81, 144410 (2010).
[2] S. Göttel, S. Andergassen, C. Honerkamp,
D. Schuricht, and S. Wessel, Phys. Rev. B
85, 214406 (2012).
[3] K. Fukui, Ph.D Thesis, The University ofTokyo (2021).

244

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Molecular dynamics simulations for assembly anddisassembly of protein aggregates
Hisashi Okumura
Exploratory Research Center on Life and Living Systems,
Institute for Molecular Science, Okazaki, Aichi 444-8585
Proteins are normally folded correctly andbonds formed between C=O and N–H in theperform functions that are necessary to sustain

amyloid fibril are broken with each pulse oflife. However, when the concentration oflaser irradiation. In most cases, these bonds areproteins increases due to aging or other reasons,reformed spontaneously after the irradiation.

they can aggregate and cause a variety ofHowever, if a water molecule happens to enter

diseases. Alzheimer’s disease, which is one

the gap between C=O and N–H made by thetype of dementia, is caused by amyloid-β (Aβ)

laser irradiation, the reformation of thepeptides,sphericalhydrogen bonds is inhibited. This role of wateroligomers or amyloid fibrils. We are conducting

molecules is quite different from other known

theoretical studies on the aggregation andmechanisms. This new mechanism can explain

disaggregation of Aβ peptides [1]. In this fiscal

recent experiments showing that amyloid fibrils

year, we investigated the destruction process ofare not destroyed by laser irradiation under dry

an Aβ amyloid fibril by infrared free electron

conditions [2].

which

aggregate

intolaser irradiation using molecular dynamics

Furthermore, we found that more α-helix

simulation.

structures are formed after the laser-irradiatedIn recent years, Aβ aggregates have been

amyloid-fibril destruction. This is because theirradiated with infrared free electron lasers andα-helix structure has a different resonancedestroyed.

non-equilibrium

frequency from the β-sheet structure. Our

molecular dynamics simulations of Aβ amyloid

findings provide a theoretical basis for the

fibrils under a time-varying electric field

application of the laser to the future treatment

mimicking that of an infrared free electron laserof amyloidosis.

to clarify the destruction process and theReferences

structure of amyloid fibrils after destruction.

[1] H. Okumura, S. G. Itoh, J. Am. Chem. Soc.

We

performed

136 (2014) 10549-10552.

As a result, we have discovered a newmechanism by which water molecules destroy[2] T. Kawasaki, et al. Cellular and Molecular

the Aβ amyloid fibril. Intermolecular hydrogen

Neurobiology 38 (2018) 1039-1049.

245

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study on Complex Systems by Generalized-Ensemble Algorithms
Takuya HAYASHI and Yuko OKAMOTO
Department of Physics, Graduate School of Science, Nagoya University
Furo-cho, Chikusa-ku, Nagoya, Aichi 464-8602

We had two projects regarding generalized-

This estimate is in good agreement with theensemble algorithms applied to complex

results of several other research groups (seesystems.

Fig. 1).

The density of states (DOS) is one of themostimportantphysicalquantities

instatistical mechanics. Recently, we proposed asimulation protocol, REWL-MUCAREM [1],in order to obtain the DOS with high accuracy
in complex systems by combining the
Replica-Exchange

Wang-Landau(REWL)

Figure 1: The estimates of residual entropy ofmethod [2] and the Multicanonical Replica-

ice Ih by several research groups.

Exchange Method (MUCAREM) [3]. The
However, our previous results disagreed witheffectiveness of REWL-MUCAREM wasthe above results [5]. We found that thedemonstrated by using the 2-dimensional

discrepancy resulted from the choice of theIsing model in [1].

random number generators [4]. The present

We also applied the REWL-MUCAREM
protocol to the ice Ih system in order toestimate the residual entropy with highaccuracy. The residual entropy of ice has
become one of good examples to test theeffectiveness of sampling algorithms.
Our latest estimate of residual entropy
per one water molecule [4] is:

W0 = 1.507472 ± 0.000047
S 0 = kB lnW0

Figure 2: Generated random numbers by the= 0.815615 ± 0.000063 [cal/(mol K)].

Marsaglia generator (green) and Mersenne
Twister generator (purple).

246

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

work used Mersenne Twister generator [6],We see that the helix-coil transition

while our previous work used Marsaglia

temperature is higher for N=20 than for N=10.

generator [7]. In Fig. 2 we compare the twoItrandom number generators. Although thetemperature is higher for in vacuum than in

Mersenne Twister generator gives uniform

water.

is

By

distribution, Marsaglia takes on only nine

also

shown

calculating

that

the

this

transition

microcanonicalvalues in this narrow range. We haveentropy and its derivative with respect toreminded the reader that the choice of random

energy, we found that the latter has an

number generators is very important.

inflection point in vacuum but no inflection
point in water. This suggests that the helix-

In the second project, we studied thehelix-coiltransitionsofcoil transition is first-order-like in vacuum,

homo-alanine

but it is second-order-like in water [8].

polymers [8] based on the MicrocanonicalInflection-Point Analysis (MIPA) Method [9].
Two lengths of homo-polymers were taken,
N=10

and

20,

and

two

References

environment[1] T. Hayashi and Y. Okamoto, Phys. Rev. E.

conditions (in vacuum and in water) were100, 043304 (2019).

considered.

REWL-[2] T. Vogel, Y. W. Li, T. Wüst and D. P.

MUCAREM simulations. In Fig. 3, we

Landau, Phys. Rev. Lett. 110, 210603 (2013).

compare the specific heat.

[3] Y. Sugita and Y. Okamoto, Chem. Phys.

We

performed

theLett. 329, 261 (2000).
[4] T. Hayashi, C. Muguruma, and Y.
Okamoto, J. Chem. Phys. 154, 044503(2021).
[5] B. A. Berg, C. Muguruma, and Y.
Okamoto, Mol. Sim. 38, 856 (2012).
[6] M. Matsumoto and T. Nishiura, ACM
Trans. Modle. Comput. Simul. 8, 3 (1998).
[7] G. Marsaglia, A. Zaman, and W. W.
Tsang, Stat. Probab. Lett. 9, 35 (1990).
[8] T. Hayashi, Y. Sakae, and Y. Okamoto,submitted for publication.
Figure 3: Specific heat as functions of[9] K. Qi and M. Bachmann, Phys. Rev. Lett.

temperature for N=10 and 20.

120, 180601 (2018).

247

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical Diagonalization Study on the
Field-Induced Spin Nematic LiquidTôru SAKAI1,2 , Hiroki NAKANO1 , Rito FURUCHI1 , and Tokuro SHIMOKAWA3 ,1
Graduate School of Material Science, University of Hyogo,
Kouto, Kamigori, Hyogo 678-1297, Japan
2
Synchrotron Radiation Research Center, Kansai Photon Science Institute,
Quantum Beam Science Research Directorate,
National Institute for Quantum and Radiological Science and Technology (QST)
SPring-8, Kouto, Sayo, Hyogo 679-5148, Japan
3
Okinawa Institute of Science and Technology Graduate University, Onna,
Okinawa 904-0945, JapanThe quantum spin nematic state has attracted a lot of interest in the field of themagnetism. It is a kind of state between theconventional long-range antiferromagnetic order and the quantum spin liquid. This state
has been proposed as one of mechanisms of
the hidden order which was observed in somestrongly correlated electron systems. The spin
nematic state was theoretically predicted tobe realized in several frustrated systems; thesquare lattice model with the ferromagnetic
nearest-neighbor and antiferromagnetic nextnearest-neighbor interactions[1], the triangular lattice antiferromagnet with multi spin exchange interactions[2], and the ferromagnetic
and antiferromagnetic zigzag chain[3, 4]. The
previous density matrix renormalization group(DMRG) analysis[5] indicated that the fieldinduced spin nematic liquid phase appears in
the S = 1 antiferromagnetic chain with the biquadratic interaction. Thus it would be important to investigate this system using anothermethod, in order to confirm the spin nematic
liquid phase. We investigated the magnetization process of the S = 1 antiferromagnetic
chain with the biquadratic interaction, using
the numerical exact diagonalization of finitesize clusters[6]. The present analysis confirmed

248

the appearance of the field-induced spin nematic Tomonaga-Luttinger liquid phase andgives the ground state phase diagram whichis qualitatively consistence with the previous
DMRG study[5]References[1] N. Shannon, T. Momoi and P. Sindzingre,
Phys. Rev. Lett. 96 (2006) 027213.
[2] T. Momoi, P. Sindzingre and N. Shannon,
Phys. Rev. Lett. 97 (2006) 257204.
[3] A. V. Chubukov, Phys. Rev. B 44 (1991)
R4693.
[4] T. Hikihara, I. Kecke, T. Momoi and A.
Furusakai, Phys. Rev. B 78 (2008) 144404.
[5] T. S. R. Manmana, A. M. Lauchli, F. H.
L. Essler and F. Mila, Phys. Rev. B 83
(2011) 184433.
[6] T. Sakai, AIP Advances 11 (2021) 015306.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Symmetry Protected Topological Phase of the S=2
Antiferromagnetic Chain
Tôru SAKAI1,2 , Hiroki NAKANO1 , Rito FURUCHI1 , and Tokuro SHIMOKAWA3 ,1
Graduate School of Material Science, University of Hyogo,
Kouto, Kamigori, Hyogo 678-1297, Japan
2
Synchrotron Radiation Research Center, Kansai Photon Science Institute,
Quantum Beam Science Research Directorate,
National Institute for Quantum and Radiological Science and Technology (QST)
SPring-8, Kouto, Sayo, Hyogo 679-5148, Japan
3
Okinawa Institute of Science and Technology Graduate University, Onna,
Okinawa 904-0945, JapanThe spin gap of the integer-spin antiferromagnetic Heisenberg chain was proposed by
Haldane[1, 2] many years ago. Recently it has
been generalized as the symmetry protected
topological phase[3, 4], which is the gapped
phase of the odd-integer-spin antiferromagnetic chain. On the other hand, the numerical diagonalization and the level spetroscopy
analyses on the S = 2 antiferromagnetic chain
with the coupling anisotropy ∆ and the singleion anisotropy D, indicated that the symmetry
protected topological phase appears at a small
region in the ∆ − D phase diagram[5, 6]. This
phase corresponds to the intermediate D phasewhich had been predicted by Oshikawa[7]. In
the present study, the S = 2 antiferromagnetic
Heisenbergy chain with the biquadratic interaction JBQ and the single-ion anisotropy D isinvestigated using the numerical diagonalization and the level spectroscopy analyses. As
a result, it is found that the intermediate D
phase appears at a wide region in the JBQ − Dphase diagram.

References[1] F. D. M. Haldane, Phys. Lett. 93A (1983)
464.

249

[2] Phys. Rev. Lett. 50 (1983) 1153.
[3] F. Pollmann, A. M. Tuner, E. Berg and M.
Oshikawa, Phys. Rev. B 81 (2010) 064439.
[4] F. Pollmann, E. Berg, A. M. Turner and
M. Oshikawa, Phys. Rev. B 85 (2012)
075125.
[5] T. Tonegawa, K. Okamoto, H. Nakano, T.
Sakai, K. Nomura and M. Kaburagi, J.
Phys. Soc. Jpn. 80 (2011) 043001.
[6] K. Okamoto, T. Tonegawa and T. Sakai,
J. Phys. Soc. Jpn. 85 (2016) 063704.
[7] M. Oshikawa, J. Phys.: Condens. Matter
4 (1992) 7469.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ground-State Phase Diagram of the S=1/2 Heisenberg-G
model on a Honeycomb Lattice
Takafumi SUZUKI
Graduate School of Engineering,
University of Hyogo, Shosha, Himeji, Hyogo 670-2280
from the isolated dimer limit, we found that a

In this study, we investigated the ground-

triplet dimer phase can survive up to thestate phase diagram of the S=1/2 Heisenberg-G

isotropically interacting system in a large partmodel on a honeycomb lattice [1] by theof the phase diagram, where the Heisenberg

numerical exact diagonalization method andcluster-series

expansion

method[2].

and G interactions are ferromagnetic andWe

antiferromagnetic, respectively. Otherwise, afocused on the effects of the anisotropic

phase transition to a magnetically orderedinteraction; by tuning the coupling constants,

phase takes place before the interaction

the system changes between the spin-chain andbecomes isotropic. This means that theisolated dimer models. We found that, in thequantum spin liquid discussed in the G modelspin-chain limit, there are three kinds of states,[3] is unstable against the anisotropy of thenamely a Tomonaga-Luttinger liquid and twointeractions. The obtained results, namely themagnetically long-range-ordered states. All

unitability of this spin liquid and the stable

three states change two-dimensional long-range

triplet dimer phase, are the same as those of theordered states, when the interchain interaction

previous results for the Kitaev-G model on ais included infinitesimally except for the casehoneycomb lattice [4].

where the Heisenberg interaction is much
weakerthan

theoff-diagonal

symmetric

Referencesinteraction (G). When the antiferromagnetic G[1] T. Suzuki, T. Yamada, and S. Suga, ininteraction is large enough and the system

preparation.

locates near the spin chain limit, we observe[2] J. Oitmaa, et al., Series Expansion Methods

that there are no prominent peaks of the staticforstructure factor and the feature of the low-

Cambridge University Press, 2006.

energy excitation is quite similar to that in the[3] A. Catuneanu, et al., npj. Quantum

spin chain limit. We consider that two-Materials, 3 23 (2018).

dimensional true-long-range-ordered state is[4] T. Yamada, T. Suzuki, and S. Suga, Phys.

suppressed in such parameter region. Starting

Rev. B 102, 024415 (2020).

250

Strongly

Interacting

LatticeModels,Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical analysis for nonequilibrium dynamics inelectronic systems on quasicrystals & Study of newordered phase and nonequilibrium phenomena inquasicrystals

4

(a)

(b)

Akihisa Koga∆
Department of Physics, Tokyo Institute of Technology, Meguro, Tokyo
152-8551∆!"!
!"! "#!"

Recently, quasicrystals, which have no translational symmetry but have ordered lattice
structures, are attracting interests in the condensed matter physics. So far, their static
properties such as resistivity and specific heats
have been mainly focused on. Thus, it is important to reveal nonequilibrium features ofquasicrystal systems and understand how special lattice structures affect the dynamics.
Motivated by this, we studied nonequilibrium dynamics of the excitonic insulating (EI)
phase described by the two-band Hubbard
model on the Penrose lattice. The EI phase is
the condensation of the electron-hole pairs (excitons) in semiconductors or semimetals. The
EI phase is analogous to superconductors andis attracting much interests in the context of
nonequilbrium condensed matter physics. Bymeans of the real-space time-dependent meanfield theory for large systems, we revealed qualitatively different behaviors in the BCS and
BEC regimes, see Fig.1. Namely, in the BCS
regime, the order parameter is suppressed after
a single cycle pulse, while, in the BEC regime,
it is increased by the pulse. Such a behavior
has been reported in a previous work on thesquare lattice, and its origin was discussed in
the momentum space. However, in quasicrystals, one cannot define the momentum spaceand such argument does not apply. Our results indicate existence of a more fundamental
origin regardless of the momentum picture. In
addition, we revealed a characteristic dynamics in the BCS regime using the perpendicularspace analysis.

!
(a)

(b)
(c)

BCS

∆
∆ !"

!
(c)

4

BEC

!"∆
!

!"!

!"∆
! "#
!"

!"! "#!!

culatedin the area without edges [see appendix. A]. We define!
!NNB
those averaged MF parameters as |∆(τ)|NB = i=1|∆i (τ)|/NNB
!NNB
! "#
and 2nc (τ)NB = 2 i=1 nci (τ)/NNB , where NNB is the nubmerof sites away from the edge. We set NNB = 7936 in this study.
In Fig. 4, we plot |∆(τ)|NB and 2nc (τ)NB with dashed lines foreach F0 . Note that, for τ > 2π/ω, 2nc (τ) is conserved, but
2nc (τ)NB is not conserved. We find that the behavior of |∆(τ)|
and |∆(τ)|NB are qualitatively similar. The same can be said
about the relation between 2nc (τ) and 2nc (τ)NB . Therefore,
we can consider that the boundary eﬀect (finite size eﬀect) on
FIG. 4. (Color online) Time evolution of |∆| and 2nc for V = 1.95 andtheV ≃4.28 withistheconditionfor(N,qualitative
U, D, ω) = (11006,
4, 4, 0.4).
dynamics
negligible
discussions.
On(a)(b)theand 2nhand,≃ 4.28.
We plotthat|∆(τ)|
and 2nsize
with thedashedTime evolution of |∆| and 2nc for V = 1.95. (c)(d) Time evolution of |∆|otherc for Vwec (τ)NB
confirmed
theNBfinite
eﬀectsappears(|∆(0)|
line for each F0 . Horizontal black (dashed) lines represent |∆(0)| and 2ninc (0)the
NB and 2nc (0)NB ). in N = 11006 system used here
quantitative
aspects[see appendix B]. Therefore, it is hard to estimate the accuratequantitative values such as the frequency of the Higgs (ampli[see mode.[
Fig. 4(a)].
2nc (τ) slightly increases from 2nc (0) except
culated in the area without edges [see appendix. A]. We define tude)Θ͟Θ͟‫ݴ‬Θͳͯ͘΋͍͍‫͕͢ؾ‬Δɻͦ΋ͦ
!NNB−0.15. Note that the change in nc (τ) is] not
monoF0 =ϞʔυΒ͖͠΋ͷ͸‫͍ͯ͑ݟ‬Δͷ͔ʁthose averaged MF parameters as |∆(τ)|NB = i=1|∆i (τ)|/NNB ΋for
Higgs
Thus,
in
!NNB
tonic
againstthe fielddiscuss
strength
F0 . For example,
and 2nc (τ)NB = 2 i=1
nci (τ)/NNB , where NNB is the nubmer thispaper,
we mainly
qualitative
features. nc (τ) − nc (0)for F0 = −0.10 is smaller than that for F0 = −0.07 and nc (τ)
of sites away from the edge. We set NNB = 7936 in this study.
ForFV= 1.95 (the BCS region), |∆(τ)| is smaller than thefor
0 = −0.15 is smaller than the initial value. Therefore,
In Fig. 4, we plot |∆(τ)|NB and 2nc (τ)NB with dashed lines forequilibrium|∆(0)|isfor
the values
here
it is found valuethat there
thealloptimalvalueofofF0Fstudied
0 for increaseach F0 . Note that, for τ > 2π/ω, 2nc (τ) is conserved, but
ing 2nc (τ). For V ≃ 4.28 (the BEC region), both |∆(τ)| and2nc (τ)NB is not conserved. We find that the behavior of |∆(τ)|
2nc (τ) are increased from |∆(0)| and 2nc (0) for all the valand |∆(τ)|NB are qualitatively similar. The same can be saidues of F0 studied here [see Figs. 4(c) and (d)]. Again, one
about the relation between 2nc (τ) and 2nc (τ)NB . Therefore,
can see that the changes in nc (τ) and |∆(τ)| are not monotonic
we can consider that the boundary eﬀect (finite size eﬀect) on
against the field strength F0 . |∆(τ)|−|∆(0)| and nc (τ)−nc (0) for
the dynamics is negligible for qualitative discussions. On theF0 = −0.10 and −0.15 are smaller than those for F0 = −0.07.
other hand, we confirmed that the finite size eﬀects appears
Therefore, as in the case of V = 1.95, there is the optimalin the quantitative aspects in N = 11006 system used herevalueof F0 for increasing the MF parameters. It is found that[see appendix B]. Therefore, it is hard to estimate the accuratequantitative values such as the frequency of the Higgs (amplithe enhancements of |∆(τ)| and 2nc (τ) are prominent aroundtude) mode.[Θ͟Θ͟‫ݴ‬Θͳͯ͘΋͍͍‫͕͢ؾ‬Δɻͦ΋ͦ
F0 = −0.07.
΋ Higgs ϞʔυΒ͖͠΋ͷ͸‫͍ͯ͑ݟ‬Δͷ͔ʁ] Thus, in
These nonequilibrium features for the Penrose tiling arethis paper, we mainly discuss qualitative features.
qualitatively similar to those of the previous study on the
For V = 1.95 (the BCS region), |∆(τ)| is smaller than thesquare lattice19 . In particular, we observe the enhancement
equilibrium value |∆(0)| for all the values of F0 studied hereof the order in the BEC regime and the suppression of the or-

!"

!

!

phases in quasicrystals. We have clarified thenature of magnetic orders in several types ofquasi-periodic lattices [2].
Furthermore, we have also studied realspace dynamics and correlations in the Kitaev spin liquid states. We revealed peculiar
spin transport mediated by itinerant Majorana
fermions [3] and discuss how to modify the Majorana correlations using intrinsic degrees of
freedom of the Kitaev model [4].

References[1] K. Inayoshi, Master thesis (2021); K. Inayoshi, Y. Murakami, A. Koga, in prep.
[2] A. Koga, PRB 102, 115125 (2020):
Mater. Trans. 62, 360-366 (2021).
[3] T. Minakawa, Y. Murakami, A. Koga and
J. Nasu, PRL 125, 047204 (2020).
[4] A. Koga, Y. Murakami and J. Nasu, submitted to PRB.

251!

FIG. 4. (Color(d)online) Time evolution of |∆| and 2nc for V = 1.95 and V ≃ 4.28 with the condition (N, U, D, ω) = (11006, 4, 4, 0.4). (a)(b)Time evolution of |∆| and 2nc for V = 1.95. (c)(d) Time evolution of |∆| and 2nc for V ≃ 4.28. We plot |∆(τ)|NB and 2nc (τ)NB with the dashedline for each F0 . Horizontal black (dashed) lines represent |∆(0)| and 2nc (0) (|∆(0)|NB and 2nc (0)NB ).

Figure 1: Dynamics of the EI order parame∆!"ter∆ for the two-band Hubbard
model on the!"Penrose lattice. Horizontal lines indicate equilibrium values.

Another interesting topic is possible ordered!
(d)[see Fig. 4(a)]. 2nc (τ) slightly increases from 2nc (0) except
for F0 = −0.15. Note that the change in nc (τ) is not monotonic against the field strength F0 . For example, nc (τ) − nc (0)for F0 = −0.10 is smaller than that for F0 = −0.07 and nc (τ)
for F0 = −0.15 is smaller than the initial value. Therefore,
it is found that there is the optimal value of F0 for increasing 2nc (τ). For V ≃ 4.28 (the BEC region), both |∆(τ)| and2nc (τ) are increased from |∆(0)| and 2nc (0) for all the values of F0 studied here [see Figs. 4(c) and (d)]. Again, one
can see that the changes in nc (τ) and |∆(τ)| are not monotonic
against the field strength F0 . |∆(τ)|−|∆(0)| and nc (τ)−nc (0) for
F0 = −0.10 and −0.15 are smaller than those for F0 = −0.07.
Therefore, as in the case of V = 1.95, there is the optimalvalue of F0 for increasing the MF parameters. It is found thatthe enhancements of |∆(τ)| and 2nc (τ) are prominent aroundF0 = −0.07.
These nonequilibrium features for the Penrose tiling are
qualitatively similar to those of the previous study on thesquare lattice19 . In particular, we observe the enhancementof the order in the BEC regime and the suppression of the or-Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Rational computational design of proteins toward
drug discovery and industrial applications
Nao SATO1, Sairi MATSUMOTO1, Mizuki TERANISHI1, Katsuhisa IWAYA2,
Koji OOKA2, Masataka YOSHIMURA1, Shunji SUETAKA1, Yoshiki OKA1,
Yuuki HAYASHI1, and Munehito ARAI1,2
Department of Life Sciences, Graduate School of Arts and Sciences, and1

Department of Physics, Graduate School of Science,

2

The University of Tokyo, Komaba, Meguro, Tokyo 153-8902
Proteins have been extensively used intranscriptional

activator

mixed

lineageindustrial and pharmaceutical applications;leukemia protein (MLL) was used as a template.

many protein-based drugs are among the top

Theoretical design of the mutants of the MLL

selling drugs. However, these proteins have

TAD fragment that may bind KIX more tightly

been developed by experimental approaches

than the wild type was performed using Rosetta.

that require a lot of time and cost. Therefore,

Among the designed mutants, we could obtaintheoretical approaches to efficiently design

the mutant that binds KIX two-fold more

useful proteins are demanded. To solve thistightly than the wild type, suggesting that ourissue, we have been rationally designing

strategy is useful for designing PPI inhibitors.

variousproteins,

potentially

Severeacute

applicable to industry and medicine, using thecoronavirus

2

Rosetta 3.8 or 3.12 suite [1-3]. We have also

responsible for coronavirus disease 2019

performed experimental verification of the(COVID-19), infects human cells through thecomputational protein design.

PPI between the receptor-binding domain

Protein-protein

which

are

which

is

(RBD) of the viral-surface Spike protein andrelated to many diseases, and thus designing

the cell-surface receptor angiotensin-converting

PPI inhibitors is a promising way for drug

enzyme 2 (ACE2) [5]. To inhibit this PPI, we

discovery. We rationally designed inhibitors forhave computationally designed the antibodies

the interactions between the KIX domain of athat can bind the ACE2-binding region of thetranscriptionaland

RBD of SARS-CoV-2. We are currently

transcriptional activators, which are involved in

producing the antibodies and the RBD proteins,

many diseases including leukemia [4]. The

to experimentally verify the predictions.

coactivator

domain(PPIs)(SARS-CoV-2),

syndromearetransactivationinteractions

respiratory

CBP

(TAD)

of

the

Allergic asthma is known to occur through252

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

the PPI between interleukin-33 (IL-33) released

protein folding problem [9,10]. By extending

from damaged epithelial cells and the ST2

this model, we have previously developed a

receptor of type 2 innate lymphoid cells [6]. To

statistical mechanical model of protein folding

develop the IL-33–ST2 inhibitors, we rationallythat can explain the folding pathways of multi-

designed the IL-33 mutants that tightly bind to

domain proteins having multiple disulfide

one of the two IL-33 binding sites on ST2 but

bonds. To further extend this model for any

does not to another site. The interaction of ST2

types of proteins, here we applied this model towith one of the designed mutants of IL-33 wasa protein that does not have disulfide bonds andmeasured by fluorescence anisotropy. However,succeeded in predicting its folding mechanism.

the experiment did not support the theoreticalThus, our model may be useful for a unified

prediction,

theoretical description of protein folding

indicatingthenecessityofmechanisms.

improving protein design methods.
Alkane biosynthesis

hasgainedgreat

attention as an alternative to fossil fuels and is

References

expected as one of the promising ways to[1] B.J. Bender, et al.: Biochemistry, 55 (2016)

produce4748-4763.

carbon-neuralrenewableenergy.

Cyanobacterial alkane biosynthesis involves[2] R. F. Alford, et al.: J Chem Theory Comput.

two enzymes, an acyl-ACP reductase (AAR)

13 (2017) 3031-3048.

and an aldehyde deformylating oxygenase[3] J. K. Leman, et al.: Nat Methods, 17 (2020)(ADO) [7]. Interaction between these proteins665-680.

allows an efficient delivery of an aldehyde from

[4] P. E. Wright, et al.: Nat Rev Mol Cell Biol.

AAR to ADO [8]. To improve bioalkane

16 (2015) 18-29.

production, we rationally designed the mutants[5] J. Shang, et al.: Nature, 581 (2020) 221-224.

of ADO that have higher affinity with AAR.

[6] X. Liu, et al.: Proc Natl Acad Sci USA. 110

Our preliminary experimental results show that(2013) 14918-14923.

some of the designed mutants enhanced alkane[7] M. Arai, et al.: Adv Exp Med Biol. 1080

production as predicted.

(2018) 119-154.
[8] M. Chang, et al.: Biosci Biotech Biochem.

Finally, solving the protein folding problem
is important in improving rational design of

84 (2020) 228-237.

proteins. The WSME model can explain the[9] M. Sasai, et al.: Biophys Physicobiol. 13

folding pathways of small proteins and is(2016) 281-293.

considered to be a promising model to solve the[10] M. Arai: Biophys Rev. 10 (2018) 163-181.

253

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of Giant Thermal-property Databases for
Amorphous Polymer Materials
Yuxuan Liao, Yoshihiro Hayashi
The Department of Mechanical Engineering
The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, JAPANWe intended to develop a giant thermal-

compute the long-range Coulombic interaction.

property database for amorphous polymer

In equilibration MD, NPT calculations usingmaterials. This year, we have established an

Nose-Hoover thermostat and the barostat wereautomation framework for developing the giant

run for 5 ns annealing and 8 ns equilibration.

databases,

TheAll bonds and angles, including those of theautomation framework allows us to generatehydrogen atoms, were constrained by theamorphous polymer structures and calculate its

SHAKE algorithm, and the time step was set tothermal conductivity (TC) automatically. The

1 fs. The TC is calculated by performing thesteps are: 1) creation of polymer chain byreverse NEMD (RNEMD) simulation proposed

random walk algorithm, 2) assignment of theby Müller-Plathe, as shown in Figure 2.

as

shown

in

Figure1.

force field and atomic charge into each atom, 3)

We have calculated 500 amorphous polymer

generation of the amorphous polymer cell, 4)systems, with an experimental validation shown

running

in Figure 2(B). The results are organized into atheequilibration

simulationbypaper, which will be coming online soon.

molecular dynamics (MD), 5) checking theconvergence of total energy and density, etc. forMoreover, we also calculate the thermal

the equilibration MD, 6) if not converged,transport properties of amorphous materials,

restarting the equilibration MD, 7) running thewhich is published in Nano Energy 2021 [2].

non-equilibrium MD (NEMD) to compute theReferences

TC value, 8) collection of TC values for all[1] Yoshihiro Hayashi, Ruimin Ma, Yuxuan

polymers.

Liao, et al, Automated calculation system of

All MD calculations were performed using

physical properties with molecular dynamics

the corrected heat flux branch of LAMMPS

simulation for polymer informatics (Preparing

package. We used an AMBER type GAFF2

for submitting)forcefield. Atomic charges were derived by the[2] Yuxuan Liao et al, Heat conduction below

Gasteiger

diffusive limit in amorphous superlatticemethod.

The

particle-particle

particle-mesh (pppm) method was employed tostructures,

254

Nano

Energy84,105903.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 1 Automation framework for developing the giant thermal-property polymer
databases

Figure 2. (a) Schematic representation of the simulation box for reverse nonequilibrium
molecular dynamics (RNEMD). (b) Comparing the calculated thermal conductivity (κ)
and experimental κ for 13 polymers. A dots line indicates calculated κ equal toexperimental κ.

255

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of Giant Thermal-property Databases for
Amorphous Polymer Materials
Yuxuan Liao
The Department of Mechanical Engineering
The University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, JAPANin terms of the chain length.

We intended to develop a giant thermal-

Figure. 1 shows the thermal conductivity as

property database for amorphous polymer
materials. This year, we have 1) optimized theafunction

of

chain

lengths,

which

is

thermal conductivity calculation method and 2)

characterized by the number of atoms per chain.

investigated the influence of the classical size

The results show that 20000 atoms per chain

effect and the chain length of polymers on theare needed to obtain a converged thermal

thermal conductivity of amorphous polymers.

conductivity. The results indicate that heat

The motivation is that 1) Since thecarriers with long mean free paths (propagons)

calculation is computationally heavy, we needplay an important role in the heat conduction of

to find out the best NEMD method for ouramorphous polymers.

automation system. The Muller-Plathe (MP)To give a deeper insight into the underlying

method has the advantage of a rapidly

physics, we have explored the relaxation

converging quantity in temperature gradient

process and mean free path of propagons inrather than a slowly converging heat flux, thus,

amorphous materials. Here, we have used

it can speed up the calculation speed. The

amorphous silicon, amorphous silica, andresults from the MP method are validated byamorphous silicon nitride as examples. We

comparing them with the results from thefound that the Akhiezer mechanism dominates

Langevin thermostat, as shown in Fig. 1. Here,the relaxation process of propagons [1]. Thea polymer with the ID of P010080 is used as an

next step is how to generalize the analysis into

example. 2) Since the real polymer has

amorphous polymers, which is still under

extremely long chains consisting of over tens orinvestigation.

hundreds

Referencesofthousandatoms,

whichischallenging to be calculated with NEMD. The[1] Yuxuan Liao et al, Akhiezer Mechanism

thermal conductivity of polymers typically

Dominates

increases with the chain length. Thus, we need

Amorphous at Room Temperature, arXiv

to find out the converged thermal conductivity

preprint

256

RelaxationofPropagons

inarXiv:2006.07773.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

257

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Tensor renormalization-group study of spin glasses
Koji Hukushima
Department of Basic Science, University of Tokyo
3-8-1 Komaba, Meguro-ku, Tokyo 153-8902
One of the most important remaining problems in statistical physics is to clarify the
low-temperature thermodynamic properties ofIsing spin glasses in three dimensions. The
search for the ground states is computationallyintractable in the sense that it is one of the NPhard problems in the theory of computation,and the Markov-chain Monte Carlo (MCMC)
calculations at ﬁnite temperature have extremely slow relaxation phenomena, both ofwhich make large size calculations diﬃcult. Although many computational physical methods
derived from spin-glass research, such as the extended ensemble method, have aﬀected otherresearch ﬁelds, they have not yet solved thespin-glass problem.

We addressed two speciﬁc issues in Ising spinglasses.
(1) Vertically of ferromagnetic phase transition
and ferromagnetic limit on the Nishimori line
It is rigorously known that the ferromagnetic transition on the Nishimori line is theferromagnetic limit on disorder. MCMC calculations suggested that the phase boundary
is somewhat reentrant, but this is not deﬁnite.
The negative partition function problem is considered to appear at the point where the spinglassiness is strong. Therefore, it is expected tobe reduced by getting closer to the ferromagnetic side. Here, we determined the ferromagnetic transition temperature on the Nishimoriline with high accuracy by calculating the freeenergy diﬀerence under the twisted boundary
condition using TRG.
(2)Development of an algorithm to evaluate thespin-glass order parameter by TRG
Here, we developed a method to calculate thespin-glass order parameter by TRG, and performed the calculation for the Ising spin glassmodel. The spin-glass order parameter is an
overlap function, which is deﬁned using two independent systems with the same interactions.
There are two main ways to evaluate the expectation values of physical quantities using
the TRG method. One is to use the numerical derivative of the free energy, and the otheris to use the impurity tensor to construct themeasurement tensor of the observables. In any
case, it is necessary to devise a way to calculate
the spin-glass order parameter using TRG. We
constructed a tensor network for a replica coupled system that introduces an interaction between two systems, and succeeded in calculating the order parameter on the Nishimori line
as its derivative with respect to the coupling.

In this study, we aim to break the limitof computational size by applying the tensor
renormalization group (TRG) method, which
has attracted much attention in recent years,
to the spin glass system instead of the MCMC
method. We have previously applied TRG toa lattice glass model in two dimensions thatexhibits a glass transition in the mean-ﬁeld
limit[1]. There have been a few previous studies that have applied the TRG to spin-glass
systems, but they have not been studied extensively. One reason seems to be the problem of numerical accuracy. It has been pointed
out that, as a result of frustration, a “negative
partition function” appears even though it isoriginally positive deﬁnite, and there is anotherstudy showing that this can be solved by very
high precision ﬂoating-point arithmetic. However, it has been suggested that the numerical accuracy is not realistic for such calculations at low temperature. We proposed a numerical method to detect the ordered phase in
Ising spin glasses and explore the possibility of
performing the calculation while avoiding the [1] K. Yoshiyama and K. Hukushima:
negative partition function problem in TRG. J. Phys. Soc. Jpn. 89, (2020) 104003.

258

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Parallel Bayesian computation in material science
Koji Hukushima
Department of Basic Science, University of Tokyo
3-8-1 Komaba, Meguro-ku, Tokyo 153-8902
Recent development of various experimental and measurement technologies has allowed
us to obtain a large amount of high-precision
data, but the methodologies for data analysis have not yet caught up with the improvement of experimental techniques. On the other
hand, the development of machine learning,such as deep learning, has also been remarkable in recent years, and the practical application of machine learning to materials sciencehas attracted much attention. However, theblack-boxed application of deep learning to materials science is powerful for “prediction” but
not necessarily suitable for “understanding”.
In this project, we attempted to apply anddevelop Bayesian inference based on statistical models that incorporate physical laws asmuch as possible, using data obtained from experiments as input. Since Bayesian statisticalmodels using physical processes are nonlinear
in general, they cannot be computed analytically. In the 1980s, the Markov-chain Monte
Carlo (MCMC) method was found to be usefulfor Bayesian inference, and it started to be applied in large scale. In recent years, the amountof data to be analyzed has increased and theamount of computation per step has becomelarge, and Markov chains which are bound by
causality, are not necessarily easy to parallelize.
Therefor, we applied population annealing(PA), which is a population type Monte Carlo
method, not based on Markov chains, tothe problem of Bayesian statistics of materials science. PA, proposed by HukushimaIba(2003), has been introduced as a computational method for statistical mechanical models, and recently it has been working on largescale parallel computations including GPGPU.
This method has a large number of nearly independent computations and is compatible withparallel computation, which signiﬁcantly re-duces the computational time by parallel computation. In addition, an advantage of PA over
MCMC methods is that the partition function
in statistical mechanics, which is the normalization constant for the probability distribution,
can be obtained as a by-product of the calculation. The partition function, which is called
evidence in the context of Bayesian inference, isan important quantity that gives an indicatorof model selection.
Furthermore, since the leave-one-out crossvalidation (LOOCV), which is one of the crossvalidation methods, can be formulated by thereweighting method often used in statisticalphysics, its implementation is also carried out
at the same time in PA. By systematically comparing the evidence and LOOCV, we developed
a methodology for data analysis that integrates
hyper-parameter estimation and model selection.
The proposed method has been implemented
in linear regression models with noise. It has
been pointed out that L1 regularization-based
methods such as LASSO lead to bias, and in order to avoid this, a direct method of analyzing
sparsity as an L0 regularization problem has
been considered. However, the L0 regularization problem is known to be NP hard, and noeﬃcient algorithm is known. We successfully
solved this problem in a realistic time using PA,
and also succeeded in evaluating the magnitudeof the noise by computing the evidence. Thismeans that we have established a new dataanalysis method for sparse modeling, including
uncertainty evaluation. We believe that it candevelop materials science through our sampling
methods such as noise magnitude estimationand model selection, which are a step further
than conventional Bayesian estimation usually
attributed to optimization calculations.

259

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study on relaxations of fluctuation with theevent-chain algorithm
Y. Ozeki and Y. Osada
Graduate School of Informatics and Engineering, The University of Electro-Communications

X
i

Si

!2 +1/2

T = 2.214
T = 2.212
T = 2.210

0.5

T = 2.208
T = 2.206
T = 2.204
T = 2.200
T = 2.198
T = 2.196
T = 2.194
T = 2.192
T = 2.190
T = 2.188
T = 2.186
T = 2.184
T = 2.182

0.4
0.3

0.2

0.1

1

10

t
Figure 1: Relaxation of |m(t) for the 3D XY modelin 2.182 ≤ T ≤ 2.222 with the interval ∆T = 0.002.
10(1)

and confirmed the efficiency of it.
Let us show the result of dynamical scaling analysis. The relaxation of the order parameter |m(t|)
are calculated for 2.182 ≤ T ≤ 2.222 on a 3003 simple cubic lattice up to an observation time of 100
MCSs. About 864 samples are taken for statistical
averaging. The estimations are plotted in Fig. 1.
Using the improved dynamical scaling analysis for
the NER data [4], we analyze the dynamical scalingform,|m(t, T )| = τ −λ Y [t/τ ],(2)
where τ (T ) is the relaxation time and λ is a dynamical critical exponent. The result is shown in
Fig. 2 with Tc = 2.202 and z = 1.47.
The exponents estimated by dynamical scaling
is used to deviate slightly because of corrections toscaling. To estimate the exponent more precisely,

260

l

N

−1

T = 2.220
T = 2.218
T = 2.216

Y = t m(t,J)|m(t)| =*T = 2.222|m(t)|

We investigate the applicability of the event
chain algorithm [1, 2] to the relaxation of fluctuation for the nonequilibrium relaxation (NER)
method, [3,4] which has been an efficient numericalmethod to evaluate critical exponents. The eventchain algorithm has introduced for the Monte Carlo(MC) simulation with a multi-spin-flip algorithm,
and shows estimation of the dynamical critical exponent z ∼ 1 [1], which indicates a faster dynamics
as compared with those with a single-spin-flip algorithm such as the the Metropolis one.
Previously, we investigated it for its applicability to the NER method and estimated the dynamical exponent z by means of the dynamical scaling
analysis. The initial state of relaxation is preparedas an all-aligned state. As an example, we analyze the Pclassical XY model in three dimensions;
H = −J hiji Si · Sj , where summation for hiji istaken over all nearest-neighboring sites on a simple
cubic lattice. Since the relaxation is much fast in
the simulation with the event chain algorithm, we
proposed the relaxation of the absolute value of themagnetization as the dynamical order parameter,

1

0.1
0.1

1

X = t/tFigure 2: Scaling plot for the data in2.182 ≤ T ≤2.222 in Fig. 1

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo
104

2.60

fmm(T=2.202)zz(1/t0.704)

2.40
103

2.20

fmm

2.00

z

102

1.80
1.60

101

1.40
1.20

100

1.00
1

10

100

0

0.03 0.06 0.09 0.12 0.15 0.18 0.21

1/t0.704tFigure 3: Relaxation of fluctuation fmm calculated
at T = 2.202

Figure 4: Critical exponent z is estimated as t →∞.

we analyze the relaxation of fluctuation,h|m(t)|2 i
fmm (t) ≡ N−
1,
h|m(t)i2[2] M. Michel et. al., Europhys. Lett. 112
20003 (2015)(3)

at the transition temperature Tc = 2.202 estimatedabove. This function is expected to diverge as
fmm (t) ∼ tλmm ,(4)

where λmm = d/z. Calculations are carried out on
a 2003 simple cubic lattice up to the observation
time of 100 MCSs. About 645120 samples are taken
for statistical averaging. The result is plotted inFig. 3. We evaluate the numerical derivative
λmm (t) ≡d log fmm (t),d log t(5)and plot d/λmm (t) in fig. 4, where the horizontal axis is modulated as 1/t0.704 to show a precise
asymptotic value for t → ∞. The result is z = 1.67,
which is a little greater than the value obtained by
the dynamical scaling. Consequently, the eventchain algorithm can be used in the NER analysis
with an efficient relaxation performance, and would
be applicable to various slowly relaxing problems
such as frustrated and/or random systems.

References[1] Y. Nishikawa et. al., Phys. Rev. E92 063306(2015)

261[3] Y. Ozeki and N. Ito, J. Phys.: Math.
Theor. 40 R149 (2007).
[4] Y. Echinaka and Y. Ozeki, Phys. Rev. E94
043312 (2016).
[5] A. P. Aloysius and M. Harsenbusch,
Physica A201 593 (1993)

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical study of bulk-edge correspondence andtopological phases:
From quantum to classical mechanics
Y. Hatsugai
Department of Physics, University of Tsukuba
1-1-1 Tennodai, Tsukuba 305-8571, Ibaraki, JapanAs for standard topological phenomena, non trivial topology of the bulk is reflected in theboundary physics which can be, in principle, easily accessible by experiments. This is the bulkedge correspondence[1] that is widely used for various systems from quantum to classical ones.
In this project, we have tried to extend the universal feature of the bulk-edge correspondence byusing numerical methods. In this context, the adiabatic pump proposed by Thouless more than
30 years ago is quite special since the center of mass of the bulk, that has topological origin, isthe physical observable although the edge physics is not directly observed by a realistic finite
speed. Experimental realization the adiabatic limit including the gapless edge states is difficult
although it is quite useful for clear understanding of topological character of the pumping[2].
We have extended the bulk-edge correspondence of the topological pumping for various systems
with strong correlation[3, 4]. Another extension of the bulk-edge correspondence for the higher
order topological phases is the bulk-corner correspondence. We demonstrated its validity forclassical mechanical systems on a Kagome lattice[5]. We further applied numerical methods tovarious topological phenomena among quantum and classical ones. [6, 7, 8].

References[1] Y. Hatsugai, ”Chern Number and Edge States in the Integer Quantum Hall effect”, Phys. Rev. Lett.
71, 3697 (1993).
[2] Y. Hatsugai and T. Fukui, “ Bulk-edge correspondence in topological pumping”, Phys. Rev. B 94,
041102(R) (2016).
[3] Y. Kuno and Y. Hatsugai, “Interaction-induced topological charge pump”, Phys. Rev. Research 2,
042024 (2020)[4] K. Kudo and Y. Hatsugai, “Adiabatic heuristic principle on a torus and generalized Streda formula”,
Phys. Rev. B 102, 125108 (2020). Also K. Kudo, Y. Kuno and Y. Hatsugai in preparation.
[5] H. Wakao, T. Yoshida, H. Araki, T. Mizoguchi, and Y. Hatsugai, “Higher-order topological phases
in a spring-mass model on a breathing kagome lattice”, Phys. Rev. B 101, 094107 (2020).
[6] T. Mizoguchi, Y. Kuno, and Y. Hatsugai, “Detecting Bulk Topology of Quadrupolar Phase from
Quench Dynamics”, Phys. Rev. Lett. 126, 016802 (2021).
[7] T. Yoshida, K. Kudo, H. Katsura, and Y. Hatsugai, “Fate of fractional quantum Hall states in open
quantum systems: Characterization of correlated topological states for the full Liouvillian”, Phys.
Rev. Research 2, 033428 (2020).
[8] T. Yoshida, T. Mizoguchi, and Y. Hatsugai, “Mirror skin effect and its electric circuit simulation”,
Phys. Rev. Research 2, 022062(R) (2020).

262

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical study on low-energy statesof quantum spin systems
Hiroki NAKANO
Graduate School of Material Science, University of Hyogo

In condensed matter physics, we often haveto tackle many-body problems, in which it isdiﬃcult to estimate physical quantities precisely. Quantum spin systems are such typicalcases. To examine the systems, under circumstances, numerical approaches have widely andeﬀectively been employed in various studies. A
lot of computational investigations have been
carried out and gave us useful information of
the target systems.

we developed a hybrid-type parallelized codeof Lanczos diagonalization[1]. This Lanczosdiagonalization code enables us to treat various
large systems that have not been previously
treated yet within this method. We, thus,
study various quantum spin systems by thismethod as a primary approach in this project.

Within the field of quantum spin systems,
three methods are eﬀectively used. One is
the numerical diagonalization method. The
second is the quantum Monte Carlo (QMC)
method. The third one is the density matrix renormalization group (DMRG) method.
Each of the methods has advantages; at thesame time, it also disadvantages. In the QMC
simulations, large systems can be treated irrespective of the spatial dimensions of the systems although it is diﬃcult to precisely evaluate physical quantities in frustrated systems
due to the negative sign problem. When
spatial dimension of a target system is one,on the other hand, the DMRG method isvery useful irrespective of whether the target system includes frustration or not. For
the cases when the spatial dimension is larger
than one, however, this method is still under development. The numerical diagonalization method can be applied irrespective of thepresence of frustrations and the spatial dimension. However, this method has a serious weak
point that only very small system sizes canbe treated. To overcome this disadvantage,

In the project in 2020, we tackled theS = 1/2 Heisenberg antiferromagnet on theorthogonal-dimer lattice. This system was
examined based on the calculations of 36and 40-site systems of the same Lanczos
diagonalization[2], which pointed out that thethird characteristic ratio defined as J2 /J1 appears between the edge of the exact-dimer
phase and the edge of the Neel-ordered phase;
here, J1 is the amplitude of the exchange coupling on orthogonal-dimer bonds and J2 is theamplitude of the exchange coupling forming
the simple square lattice. In order to clarify
whether or not the behavior showing the presence of the third characteristic ratio of J2 /J1
survives when the system becomes larger, weadditionally calculated the 44-site cluster ofthis system, which has not been treated before.
As a result, our calculations for 44-site system show the behavior that is consistent withthose for 40-site system. Our examination contributes to our deeper understandings of thequantum antiferromagnets with frustrations.
Further investigations would clarify nontrivial
eﬀects of quantum nature and frustration.

263

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

References[1] H. Nakano and A. Terai: J. Phys. Soc.
Jpn. 78 (2009) 014003.
[2] H. Nakano and T. Sakai, J. Phys. Soc.
Jpn. 87 (2018) 123702.

264

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Thermal effects on quantum frustrated magnetisms
Tokuro SHIMOKAWA
Theory of Quantum Matter Unit, Okinawa Institute of Science and Technology Graduate University
Onna-son, Okinawa 904-0412

Quantum frustrated magnetism is wellknown as a source of exotic states of matter, but investigating the true nature, particularly at finite temperatures, is still a toughand challenging problem. In this fiscal year,
we investigated both the ground state andfinite-temperature properties of several twodimensional frustrated magnetism by means ofexact diagonalization (ED) and quantum typicality (QT) methods. We will here briefly report our numerical activities with the ISSP supercomputer.
1) S=1/2 breathing bilayer kagome(BBK) magnets for Ca10 Cr7 O28 magnet
Motivated by recent experimental results
on a new quantum spin liquid candidate,
Ca10 Cr7 O28 , we investigated the ground stateand finite-T properties of the S=1/2 BBK
model. We developed a new ED code specialized for high fields [1], which enables us totreat much larger system sizes at most 2000
spin clusters and compute spin dynamics without any bias in our quantum Hamiltonian. We
succeeded in reproducing bow-tie and ring-likefeatures in quantum spin dynamics, which inelastic neutron scattering (INS) measurements
reported as signatures of the quantum spin liquid state of this material. We also computed
the temperature dependences of specific heatand equal-time spin structure factors by meansof the QT method, and we found a realizationof a spiral spin liquid state at moderate temperatures having a ring-like structure in equaltime spin structure factors. [2]Recent experimental results under high pressures revealed the intermediate plaquettesinglet phase in SrCu2 (BO3 )2 compound. In
this intermediate phase, we naturally expect
to have a spontaneous mirror symmetry breaking at a finite temperature; however, detecting
the possible finite-T transition has been a challenging problem, such as in the traditional ED
method because of the smallness of accessible
system sizes. We used the quantum typicality(QT) method for this problem and succeededin capturing some clear signatures of the finiteT phase transition. For example, the temperature dependence of the real-space spin-spincorrelation is one of the valuable quantities to
see the signatures: we could see two possible
mirror symmetry broken correlation patterns
at low temperatures depending on the random
initial spin configurations used in QT method.
We also discussed the relationship to the material SrCu2 (BO3 )2 . These results are publishedin Phys. Rev. B. [3]References[1] H. Ueda, S. Yunoki, and T. Shimokawa,in preparation.
[2] T. Shimokawa, R. Pohle, and N. Shannon,
in preparation.
[3] T. Shimokawa: Phys. Rev. B 103 (2021)
134419.

2) Signatures of finite-T phase transition in S=1/2 Shastry-Sutherland model265

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Global thermodynamic functions extended tononequilibrium steady states
Naoko NAKAGAWA
Department of Physics, Ibaraki University
2-1-1 Bunkyo, Mito, Ibaraki 310-8512

We study spatially inhomogeneous systems,
such as liquid-gas coexistence and multicomponent systems, from the viewpoint of global
thermodynamics [1]. We conducted numericalresearch on the following two topics by utilizing the supercomputer at ISSP. In both topics,
we performed molecular dynamics simulation
using LAMMPS.
(1) Numerical experimental protocol to determine the standard entropy and free energyof two-component fluids:
The “standard” entropy or free energy plays
a fundamental role to describe the thermodynamic properties of pure substances. This isalso the case in mixtures to distinguish theirvariety and industrial applicability. We havedeveloped a numerical protocol for determining the standard free energy of mixtures fromthermodynamic measurements by using knowledge of fluctuating thermodynamics and information thermodynamics. The protocol is valid
to numerical experiments, especially to molecular dynamics. In order to verify the validityof our protocol, we organized the molecular dynamics simulation taking a simple example onwhich we can make a theoretical prediction.
We concluded the validity and the eﬃciencyof our protocol as a method to determine thestandard free energy, mixing entropy, solubility, and so on.
(2) Osmotic pressure in a binary mixture
separated by a semipermeable membrane:
We have applied global thermodynamics to abinary mixture in thermal conduction, which

is separated by a semipermeable membrane.
It predicts how the osmotic pressure changes
from equilibrium. One of the point to be examined is whether the osmotic pressure is deviated from a conventional expectation, whichcorresponds to the balance of local chemical
potential. To clarify this point, we start largescale numerical experiments. The resources
used were mainly the L9 CPU of System C(because LAMMPS has not been installed in
the new System B). The simulation was run
on 9 nodes in 360 parallel computation using
MPI. This allowed us to perform long calculations on a system with up to 105 particles tomeasure the local and global thermodynamic
quantities in the steady state with a suﬃcientrelaxation time and a suﬃciently large numberof samples. We are now checking the eﬀect of
the finite system size.

References[1] N. Nakagawa and S.-i. Sasa: J. Stat. Phys.
177 (2019) 825.
(NAL )eq(NAR )eq

NAL =?

Tm

Tm

等温

NAR =?

TL

TR

熱伝導

Figure 1: Configuration of the investigatedsystem with two component fluid and a semipermeable membrane. The distribution of particles is modified by heat current.

266

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Multiscale simulation of polymeric fluids and solids
Takahiro MURASHIMA
Department of Physics, Graduate School of Science, Tohoku University,
6-3, Aramaki-aza-Aoba, Aoba-ku, Sendai, Miyagi 980-8578
To develop multiscale simulation directly

problems. In this algorithm, the flow frame andconnecting macroscopic continuum system andthe simulation frame were separately treated. In

microscopic molecular particle system, we need

the similar way, we have developed a QR-

a suitable boundary condition for moleculardecomposition based deformation algorithm [2]dynamics

years,

and applied to a tensile deformation ofextensional flows were difficult problems inpolymeric solid. In this fiscal year, we extended

molecular dynamics simulation. Recently, we

this QR-decomposition based algorithm to be

have

[1]

applicable for rotational flow, rotational shear

applicable for the Langevin thermostat. Thisflow, pure shear flow, and so on. Fig.1 shows

new algorithm can solve the extensional flow

the rotational shear flow.

simulation.

developed

For

UEFEX

long

algorithm

Fig. 1: Snapshots of rotational shear flow. Non-symmetric deformation rate tensor applied.
Simulation box (the flow frame) is rotating clockwise. Black frame represents “the MD frame”.
The rotational shear flow is typical in cavity

References

flow and contraction and expansion flow. I[1] T. Murashima, K. Hagita, T. Kawakatsu, J.

would like to apply this technique to the ring-

Soc. Rheol. Jpn. 46 (2018) 207.

linear polymer blend [3], where the topological[2] T. Murashima, S. Urata, S. Li, Euro. Phys. J.

constraint of ring polymer causes uniqueB, 92 (2019) 211.

phenomena;[3] T. Murashima, K. Hagita, T. Kawakatsu,

forexample,theviscosity

overshoot in a biaxial elongational flow.

arXiv:2102.02452.

267

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ground state and dynamical properties of the
J1J2K-Heisenberg model on the square lattice
Matthias GOHLKE, Tokuro SHIMOKAWA
Theory of Quantum Matter Unit, Okinawa Institute of Science and Technology
1919-1 Tancha, Onna-son, Okinawa 904-0495

In the absence of conventional magnetic order of spin-dipolar moments, ordering withhigher-order moments like spin-quadrupoles
may occur. Such spin-quadrupolar—or spinnematic (SN)—order was found theoretically in spin-1 model with biquadratic spinexchange [1].
Magnets with spin- 12 degrees of freedom,
however, can only exhibit a SN states if two
spin- 21 are combined into an effective spin-1 [2].
In fact, such SN states on bonds has theoretically been observed in frustrated ferromagnets
on the square lattice with dominant ferromagnetic Heisenberg exchange, J1 , antiferromagnetic next-nearest neighbor exchange, J2 , andcyclic permutation, K. It was found that thecondensation of a two-magnon bound state, atstrong magnetic fields along the z-axis, can stabilize a phase with bond-nematic order [3].
Experimentally, the nature of such a groundstate is intrinsically difficult to verify, due tothe lack of probes that couple directly to thespin-quadrupole moments. Instead, it is necessary to examine the dynamics of a SN: A
continuous symmetry for the director of a spinquadrupole remains, that give rise to a gapless
Goldstone mode [4, 5].
We started by studying the square-latticefrustrated J1 -K model [2],H = J1

X

S·S

+ K

(i,j,k,l)References

(1)

hi,ji

X 

Heisenberg exchange between nearest neighbor spins, K the cyclic ring exchange aroundsquares, and hz the Zeeman coupling to a magnetic field along the z-axis.
Using iDMRG and the matrix product states(MPS) framework, we confirm the existenceof the bond-nematic phase in an extended
range of K/|J1 | while being sandwiched between the fully-polarized phase at high fields
and a long-range magnetically ordered phaseat low fields. A recently developed exact diagonalization method near saturation [6], showsa good agreement with iDMRG on cylindricalgeometries with circumference Lcirc ≥ 6 sites.
Given the ground state wave function as an
MPS, dynamical properties can then be studied by applying a time-evolution unitary U (dt)represented as a matrix product operator. In
doing so, we observe the condensation of twomagnon bound state at the corresponding wave
vector of the SN state. Within the SN phase,
we observe a gapless mode with vanishing spectral weight in the q → 0 & ω → 0 limit aspredicted by prior mean-field studies. We do,
however, observe some relevant qualitative differences, whose origin we are currently investigating.

−1
Pijkl + Pijkl
+ hz

X

Siz ,

i

where J1 represents dominant ferromagnetic[1] K. Harada and N. Kawashima, Phys. Rev.
B 65 (2002) 052403.
[2] A. Andreev and I. Grishchuk, Sov. Phys.
JETP 60 (1984) 267.

268

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo[3] N. Shannon, T. Momoi, and P. Sindzingre, Phys. Rev. Lett. 96 (2006) 027213.
[4] R. Shindou, S. Yunoki, and T. Momoi,
Phys. Rev. B 87, (2013) 054429.
[5] A. Smerald, H. T. Ueda, and N. Shannon,
Phys. Rev. B 91 (2015) 174402.
[6] H. Ueda, S. Yunoki, and T. Shimokawa,in preparation.

269

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of entanglement optimization method
Kenji HARADA
Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan

There are various interesting algorithms on
tensor networks to calculate the free energy
and critical properties of classical systems andthe ground state of quantum systems. In thesealgorithms, we often need to control the entanglement structure in a tensor network. For
example, we need to remove the short entanglement loop structure in grid tensor networks
to calculate a critical fixed point tensor.
In this project, we try to optimize an entanglement structure in a local tensor network
directly. In particular, we consider the development of a new optimization method fora branching operator[1]. To make a branching operator, we usually use the truncation
optimization for a local tensor network. Instead, we directly reduce the entanglement after applying a branching operator. Combining automatic differentiation and manifold optimization techniques, we can construct an iteration method to reduce the entanglement by
a branching operator.
Applying the new method to a tensor network representation of a Born machine[2, 3],
we can directly transform a MPS into a MERA
tensor network[4, 5]. In the case of the Bornmachine of the Ising model, we can constructa correct MERA tensor network from an exact
MPS of the Born machine. In two-dimensional
tensor networks, it is hard to transform the
PEPS into a tree tensor network. We needto transform the PEPS into the MERA tensor
network directly. It is also necessary to develop
a similar optimization method of a branching
operator for the two-dimensional network.

[2] Z.-Y. Han, J. Wang, H. Fan, L. Wang,and P. Zhang, “Unsupervised Generative
Modeling Using Matrix Product States,”
Phys. Rev. X, 8, 031012 (2018).
[3] S. Cheng, L. Wang, T. Xiang, and P.
Zhang, “Tree tensor networks for generative modeling,” Phys. Rev. B, 99, 155131(2019).
[4] G. Vidal, “Entanglement Renormalization,” Phys. Rev. Lett., 99, 220405(2007).
[5] G. Vidal, “Algorithms for entanglement
renormalization,”
arXiv:0707.1454v1(2007).

[1] K. Harada, “Entanglement branching operator,” Phys. Rev. B 97,045124 (2018).

270

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Kinetics of phase transition and polyamorphism
Kazuhiro Fuchizaki, Hiroki Naruta, and Katsumi Nakamura
Department of Physics, Ehime University, Matsuyama 790-8577

In FY2020, we mainly treated the structuralvariation during the amorphous–amorphoustransition in SnI4 . We conducted in situ
synchrotron x-ray measurements along theisotherm at room temperature from 30 GPa
down to 1.1 GPa, using a diamond anvil cellto obtain the structure factor required for the
analysis. We also succeeded in applying anidea of nonequilibrium relaxation to machinelearning (ML) for predicting the order-disordertransition temperature in a 2-dimensional (2D)
Ising system. The last project was unscheduled at the outset. We exploited System B in
the following scene.
Amorphous–amorphous transition in SnI4 [1]We decided to analyze the structure employing reverse Monte Carlo (RMC) simulation because it is much advantageous than a usual
Fourier inversion in the following respect: we
can extract 3D structural information, fromwhich partial radial distribution functions are
obtainable. Before conducting the RMC ﬁtof the experimental structure factor S(k), we
had to determine the system’s density and initial conﬁguration transferred to the ﬁt as input. For this purpose, we prepared a system,
which “mimics” the actual system at the measured thermodynamic conditions, using classical isothermal and isobaric molecular dynamics simulation for a system composed of 2744
rigid regular tetrahedral molecules conﬁned ina cubic box with periodic boundary conditions.
System B took care of this process.
We call the system, whose density is to be
determined, a target system. Our model system [2] was known to capture the real systembelow 1 GPa. Hence, we ﬁrst searched in a271

trial-and-error manner thermodynamic conditions at which the model system “looks like”−1 ,the real system, at least in the length scale km
where km denotes the principal-peak positionof S(k). The conditions thus found were listed
in Table 1 of Ref. [1]. The resultant model
systems after equilibration were all metastableliquids.
Our method for density estimation from
S(k) presumes the existence of a reference
state that has a similar structure on the length−1 . Let n be a trial number density.
scale of kmt
We redeﬁne the system’s length by multiply−1/3
ing ntand calculate the structure factor,
St (k), using the scaled length. If we denotethe principal-peak position of St (k) by kt , wecan deﬁne the diﬀerence, δk = kt − km , asa function of nt . The target’s number density, n, is then estimated by the condition,
δk/δnt |n = 0. After ﬁnalizing the density, we
resized the whole system uniformly so that not
only the length of sides of the system but also
the interatomic distances were updated. We
transferred the conﬁguration along with thedensity to the RMC program.
The RMC simulation (see Fig. 1 for an
example) could reveal that the high-density
amorphous (HDA) state is divided into twostates: the high-pressure HDA state beyond 14
GPa containing isolated Sn atoms and the lowpressure HDA state below 14 GPa consistingof deformed molecules connected by metallic I2
bonds. In the latter state, the molecular shape
becomes C3v -like just before the transition to
the low-density amorphous (LDA) state, inwhich molecules recover the original Td symmetry. This local symmetry change has been

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyodetected on the liquid–liquid transition of SnI4 ,suggesting the strong coupling between the local symmetry and the global order parameterof density.

Figure 1: The RMC-simulation result obtained
from S(k) at 3.3 GPa, just before the transition to the LDA state on decompression, isvisualized as an example. SnI4 units (not necessarily molecules) are depicted in red, green,and purple when they are regularly tetrahedral
shaped, severely deformed, and even dissociated, respectively.
Applying nonequilibrium-relaxation scheme toML for detecting a phase transition [3]There seems no need to explain the signiﬁcance of applying the ML technique toproblems across the various disciplines today.
One example in physics problems is detecting the phase transition without any information about the “answers” a priori, as intelligibly illustrated for a 2D Ising model [4].
Tanaka and Tomiya identiﬁed that the weights,
more strictly, their sum Wsum , in a convolutional neural network (CNN) can play a relevant order parameter [4]. The identiﬁcation
then readily prompted us to apply the idea of
nonequilibrium relaxation [5] to the detection.
We employed the same CNN with one hidden layer besides the input and output layers.
To investigate the learning processes in detail,we realized the CNN in-house. We used thesame 2D Ising system on an L × L lattice withperiodic boundary conditions imposed for the272

examination, where L = 32, 64, 128, and 256.
We used as training data the systems well equilibrated at the speciﬁed temperature. Here,the temperatures constituted the labels, whichwere one-hot encoded into the binary vector.
Initially, we set Wsum to zero, which corresponds to the completely “unlearned” state.
Wsum soon evolved into one of the two stateswith learning, depending on the pattern’s temperature, leaving Wsum at the transition temperature Tc unlearned. We could thus identify Tc as the ﬁxed point in the label space.
Because Wsum with labels on both sides of
the ﬁxed point soon bifurcates with learning,a CNN with proper ﬁlters implemented canjudge the location of a Tc at an early stage oflearning. In this context, the existence of hidden layers is practically relevant to eﬃciency.
However, such a Tc irregularly depends on
L; Tc does not follow the relationship, Tc (L) ∼L−1 , expected from the ﬁnite-size scaling. The
unusual L-dependence happened to make suchan L = 32 system predict the transition temperature remarkably close to the exact one,and large systems used as training data do notnecessarily bring about a better result for predicting Tc .

References[1] K. Fuchizaki, A. Ohmura, H. Naruta, andT. Nishioka, submitted to J. Phys.: Condens. Matter.
[2] K. Fuchizaki and Y. Asano, J. Phys. Soc.
Jpn. 84, 064601 (2015).
[3] K. Fuchizaki, K. Nakamura, and D. Hiroi,
J. Phys. Soc. Jpn. 90 (2021), in press.
[4] A. Tanaka and A. Tomiya, J. Phys. Soc.
Jpn. 86, 063001 (2017).
[5] N. Ito, Physica A 192, 604 (1993).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Investigation of the molecular origins of the mechanical andthermal properties of realistic bio-polymers using allatomistic molecular dynamics
Okazaki Susumu
Department of Advanced Materials Science,
The University of Tokyo, Kashiwa-no-ha, Kashiwa, Chiba 277-8581
We have studied the impact fractures ofat different temperatures, within the observation

amorphous glassy polymer materials using all-time of current MD simulation time scale. Thisatomistic molecular dynamics (MD) simulations

causes the volume, the order parameter usuallyfor the past few years [1, 2]. In the second halfused to define glass transition, to show a broadof the past year, we continued the pursuit of theglass transition over decades of kelvins. The

molecular scale understanding of the yielding

same phenomenon is believed to occur inand the glass transition phenomena using theexperimental conditions, although the impact ofprotocols employing large-scale parallel MD

the faster degrees of freedom are less.

simulations and analyses established earlier, by

References

utilizing the supercomputer resources at ISSP.
In the first half, we investigated the stress[1] K. Fujimoto, Z. Tang, W. Shinoda, S.

origins of the yielding process of the brittle

Okazaki, All-atom molecular dynamics study ofmaterial poly-(methyl methacrylate) (PMMA)

impact fracture of glassy polymers. I: Molecularusing the stress decomposition method wemechanism of brittleness of pmma and ductility

developed previously, and found that 1) theof pc, Polymer 178(12) (2019) 121570.

brittle materials share the same stress origins as[2] Z. Tang, K. Fujimoto, S. Okazaki, All-atomthe ductile materials; 2) the dense and bulky

molecular dynamics study of impact fracture ofsidechains of PMMA makes it a brittle material

glassy polymers. II: Microscopic origins of

by lowering its flexibility and increasing thestresses in elasticity, yielding, and strainstress strength. [3]hardening, Polymer 207(20) (2020) 122908.

In the second half, we thoroughly studied the[3] Z. Tang, K. Fujimoto, S. Okazaki, A

glass transition phenomenon by analyzing thecomparison of the brittle PMMA with the ductile

MD trajectories, and realized that various

PC on the elasticity and yielding from adegrees of freedom, including the translation

molecular

and rotation of polymer chains, the dihedral(2021), in press.

angle rotation, and some angle bending, defreeze

273

dynamics

perspective,

Polymer

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Global Optimization of Tensor Renormalization
Group using the Corner Transfer Matrix
Satoshi MORITA
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

To resolve this problem, we propose anotherapproximation for global optimization [5]. We
replace the environment tensor with the cornertransfer matrices (CTM) and the edge tensors,which can be updated by using the CTM renormalization group (CTMRG) [4]. Moreover, we
introduce additional decomposition, which reduces computational cost of tensor contraction for the coarse-grained tensor. The computational time of our algorithm (CTM-TRG)
in two dimensions scales as O(χ6 ) against
the bond dimension χ while the HOTRG and
HOSRG have O(χ7 ) scaling.
We perform benchmark calculations in the
Ising model on the square lattice and showthat the time-to-solution of the proposed algorithm is faster than that of other methods. As
shown in Fig. 1, our proposed method shows
better accuracy than HOTRG and compatible
to HOSRG.

Relative error in the free energy

Tensor network methods attract much attention as powerful tools for computing
strongly correlated many-body problems. The
tensor renormalization group method (TRG)[1] and the higher-order TRG (HOTRG) [2]provide a way to calculate coarse-grained tensor based on the singular value decomposition.
Both the methods do information compression
by solving local optimization problems. Approximations in these methods are locally optimal but not so for contraction of the wholetensor network. The second renormalizationgroup method (SRG) [3] and the higher-order
SRG method (HOSRG) [2] introduce global
optimization of tensor renormalization group.
Although these methods drastically improveaccuracy, calculation of the environment tensor requires performing the forward-backward
iterations.

10−7
10−8
10−9
10−10
10−11

HOTRG
χ=24
HOSRG
χ=24
HOTRG
χ=64

CTM-TRG
χ=24 FBC
χ=24 OBC
χ=64 FBC

10−12
2.24

2.25

2.26

2.27

2.28

2.29

2.3

Temperature

Figure 1: Relative errors in the free energy
measured in the Ising model on the square lattice.

References[1] M. Levin and C. P. Nave, Phys. Rev. Lett. 99,
120601 (2007).
[2] Z. Y. Xie, J. Chen, M. P. Qin, J. W. Zhu, L. P.
Yang, and T. Xiang, Phys. Rev. B 86, 045139(2012).
[3] Z. Y. Xie, H. C. Jiang, Q. N. Chen, Z. Y.
Weng, and T. Xiang, Phys. Rev. Lett. 103,
160601 (2009).
[4] T. Nishino and K. Okunishi, J. Phys. Soc. Jpn.
65, 891 (1996).
[5] S. Morita and N. Kawashima: Phys. Rev. B
103, 045131 (2021).

274

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Dynamics of Phonon Entanglement Creation
between Remote Electron-phonon Systems
Kunio ISHIDA
School of Engineering and Center for Optics Research and Education
Utsunomiya University, Yoto, Utsunomiya, Tochigi 321-8585
Coherent control of quantum mechanical stateselectrons and photons. In this case, theis important to realize various states of quantum

wavefunction|Φ⟩is described bymaterials. In particular, quantum entanglement|Φ⟩ = ∑ √𝜆𝑛 |𝜂𝑛 ⟩|𝜃𝑛 ⟩,is a measure for quantum mechanical features,nand thus we have focused on its control method

where |𝜂𝑛 ⟩ and |𝜃𝑛 ⟩ denote the phonon statesby photoirradiation[1-3]. In the present study,

and the electron-photon states, respectively.

we study the dynamics of entanglement
generation

betweenremotesystems

We calculated the dynamical behavior of 𝜆𝑛byand the entanglement entropy between phonons

irradiation of a quantized light pulse byin |𝜂𝑛 ⟩ as functions of time, and found that theemploying a model of coupled electron-phonon-

entanglement in the singular vector |𝜂0 ⟩ for thephoton systems described by[2]largest singular value 𝜆0 is weak, while |𝜂1 ⟩ and|𝜂2 ⟩ for the second and the third largest singularℋ = ∑3𝑖=1 𝛺𝑖 𝑐𝑖 † 𝑐𝑖 + ∑2𝑗=1 [𝜔𝑎𝑗† 𝑎𝑗 + {𝜇(𝑎𝑗† +𝑗

𝜎 +1

values 𝜆1 and 𝜆2 are strongly entangled. The
phonon entanglement is generated as 𝜆1 and 𝜆2

𝑗𝑎𝑗 ) + 𝜀} 𝑧2 + {∑3𝑖=1 𝜈𝑖 (𝑐𝑖 † + 𝑐𝑖 ) + 𝜆}𝜎𝑥 ].
Solvingthetime-dependent

increase, i.e., the entanglement generation

Schrödinger

process corresponds to the conversion of theequation by numerical calculation on the Systemphonon states from a pure decomposable state to

B at ISSP, we found that the quantum mutuala mixed state of entangled states.

information for phonons reveals the dynamics ofReferences

phonon entanglement generation[4].
In order to investigate the dynamical behavior[1] K. C. Lee, et al., Science 334, 1253(2011).

of phonon states in both material systems, we[2] F. Borjans, et al., Nature 577, 195 (2020).

performed a Schmidt decomposition on the[3] K. Ishida, Eur. Phys. J. D73, 117 (2019).

electron-phonon-photon states in which the[4]K.

entire system is divided into the phonons and the2005.14615.

275

IshidaandH.

Matsueda,

arXiv:

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

A Theoretical Study for Thermal Unfolding of Proteins with
Quite Similar Native Structure
Takashi YOSHIDOME
Department of Applied Physics, Graduate School of Engineering, Tohoku University,
6-6-05, Aoba, Aramaki, Aoba-ku, Sendai 980-8579

from difference in the length of the secondary

Recently, drug design for inhibiting thestructures among the two proteins.

folding of proteins has begun. This indicatesthe importance of the elucidation of the

The calculations were performed using themolecular mechanism of folding process of

F4cpu and L4cpu in the system B, and L4cpu inproteins for drug design.

the system C. We used Gromacs program suite

In the present study, we focused on the two[2] for the MD simulations. CHARMM22 force

proteins that have quite similar native structures

field [3] and TIP3P model [4] were used for thebut different structures at the transition state [1].

proteins and ions and for the water molecule,

They are goat alpha-lactalbumin and humanrespectively.

lysozyme,

respectively.

To

elucidatethemolecular mechanism of the difference in the

Referencestransition state structures among goat alpha-[1] T. Oroguchi, M. Ikeguchi, M. Ota, K.

lactalbumin

andKuwajima, and A. Kidera: J. Mol. Biol. 371

performed

molecularhumanlysozyme,
dynamics

we(MD)(2007) 1354.

simulations for their unfolding processes at 400[2] H. J. C. Berendsen, D. Van der Spoel, R.

K.

van Drunen: Comput. Phys. Commu. 91 (1995)

We

successfully

reproduced

theexperimental results for the transition state

43 (1995).

structures.

[3] A. D. MacKerell, Jr. et al.: J. Phys. Chem. B,

By

carefully

analyzingthesimulation results, we elucidated that the

102 (1998) 3586.

difference in the transition state structures arose[4] W. L. Jorgensen, J. Chandrasekhar, and J. D.

from the existence of the Ca2+ ion in the native

Madura: J. Chem. Phys. 79 (1983) 926.

structure of the goat alpha-lactalbumin, and276

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

A Method for Analyzing Protein Dynamics: A Hybrid of
Cryo-Electron Microscopy Experiment and Molecular
Simulation
Takashi YOSHIDOME
Department of Applied Physics, Graduate School of Engineering, Tohoku University,
6-6-05, Aoba, Aramaki, Aoba-ku, Sendai 980-8579
cryo-EM

Cryo-electron (Cryo-EM) microscopy is one

microscopy

experiments

wereof the methods for analyzing the three-performed. In computing the maps, the protein

dimensional structures of biomolecules like

was rotated by assigning the polar coordinates

proteins. In this method, the three-dimensionalz=(θ, ϕ) as follows: the variable θ was fixed toelectronis0°; and the variable ϕ was randomly assigned inreconstructed using a lot of two-dimensional

the range of 0°≤ϕ≤360°. It was found thatelectron density maps of the protein projected

estimating the projection angle for eachfrom several projection angles. To reconstructprojection image was successful using thethe three-dimensional electron density map, theGTM method. In future, our method will be

projection angle for each map is necessary to

improved in order to apply to actual cryo-

estimate. A method is the “common-line

electron microscopy experimental data.

density

map

of

a

proteinmethod” [1], but verification method for the

The calculations were performed using theestimation using the common-line method has

F4cpu and L4cpu in the system B, and L4cpu inbeen lacking.

the system C. We used our custom-madeprograms for the calculations. The program of

In the present study, we investigatedwhether

generative

topographic

the GTM method was implemented using the

mapping

Python3 program language.

(GTM) method [2] can be used for an
estimating method. The method enables us toestimate the function describing the two-

References

dimensional electron density maps as the[1] S. J. Ludtke, P. R. Baldwin, and W. Chiu: J.

function of the projection angle. Thus, theStruct. Biol. 128 (1999) 82.

estimation of the projection angle can be[2] C. M. Bishop, M. Svensén and C. K. I.

possible with the GTM method. To demonstrate

Williams: Neural Comput. 10 (1998) 215.

the possibility of the estimation, simulations for277

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Large-Scale Metadynamics Simulations for Water andAqueous Solutions
Hiroki NADA
National Institute of Advanced Industrial Science and Technology (AIST),
16-1 Onogawa, Tsukuba, Ibaraki 305-8569

Phase transitions in water and aqueousconsisting of 2880 water molecules using

solutions, such as crystallization and

ISSP system C with high efficiency.

amorphous formation, have been studied

Following a previous study [1], two

in fields of physics and chemistry fromdiscretelong ago. Nevertheless, there still exist a

distribution functions represented by

lot of unresolved issues concerning phase

Gaussian window functions were used astransitions of water and aqueous solutions.

collective variables.

For example, some of metastable phaseoxygen-oxygenradialA free energy landscape obtained bytransitions that are postulated to occur inthe

MTD-MD

simulation

for

the

water at a large supercooling, such as

TIP4P/Ice model at 233 K indicated two

liquid-liquid phase separation (LLPS),

local minima. One of the minima

have not yet been demonstrated.

corresponded to a low-density water

Molecular dynamics (MD) simulations

phase, and the other corresponded to ahave often been used to study thehigh-density water phase. The highstructure of water at a large supercooling.

density water phase had a structure

However, evidence for the occurrence of

resembling the structure of high-density

LLPS can hardly be obtained by standard

ice VII. At present, it is difficult to judge

MD simulations.

whether the observed two different water

In this study, a metadynamics (MTD)

phases corresponded to water phases

method was introduced to search forformed by the postulated LLPS ofmetastable phases of water at a large

supercooled water. More detailed studies

supercooling. An MD simulation inare needed to elucidate it in the future.

which

the

MTD

methodwas

implemented (MTD-MD simulation) was

References

performed for a liquid water phase[1] H. Nada: Sci. Rep. 10 (2020) 4708

278

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Metadynamics Simulation Analysis of Various Cluster
Structures Appearing in Calcium Carbonate Supersaturated
Solution
Hiroki NADA
National Institute of Advanced Industrial Science and Technology (AIST),
16-1 Onogawa, Tsukuba, Ibaraki 305-8569

Terrestrial water on the Earth contains

structures that may stably appear in amineral components, such as calcium
carbonate(CaCO3),withasolution.

high

In this study, a metadynamics (MTD)

concentration and, hence, the formation

method was introduced to overcome theof CaCO3 crystals occurs ubiquitously.

timescale problem of MD simulation [1].

Industrially, the control of CaCO3 crystal

An MD simulation in which the MTD

nucleation is crucial in connection withmethod was implemented (MTD-MD

issues concerning the formation of scales,

simulation)

causing blockage of drainage pipes andsupersaturated CaCO3 aqueous solution.

reduction of thermal efficiency of boilers.

The simulation was performed efficiently

However, the control of it is quite

by parallel computing with multiple

difficult. This is because the mechanism

nodes of ISSP system B.

of CaCO3 crystal formation from a

A

was

free

energyperformed

landscape

for

a

(FEL)

supersaturated solution still has remained

obtained with the MTD-MD simulationunclear.

indicated

Atomistic

simulations,suchstableandmetastableasaggregates formed in the solution, each ofmolecular dynamics (MD) simulations,which correspond to a local minimum on

are helpful to elucidate the structure andthe FEL). The results are helpful tothermodynamic stability of precursors.

consider the mechanism of CaCO3 crystal

However, the timescale of phenomenon

nucleation via precursors.

that can be analyzed by an MD
simulation is normally on the order ofReferences

microsecond or shorter. This timescale is[1] A. Laio and M. Parrinello: Proc. Natl. Acad.

too short to pursue all possible precursor

Sci. USA 99 (2002) 12562.

279

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Transport properties of multiple-q states infrustrated magnets
Kazushi AOYAMA
Department of Earth and Space Science, Graduate School of Science, Osaka University
Machikaneyama-cho, Toyonaka-shi, Osaka 560-0043

Transport phenomena in magnetic systems
reflect dynamical properties of interacting
spins, such as magnetic excitations and fluctuations. In this work, we theoretically investigate transport properties of two-dimensional
antiferromagnetic insulators, putting emphasis
on how nature of spin textures characterizedby more than one ordering wave vectors Q’s(multiple-Q states) is reflected in spin transport. In the J1 -J3 classical Heisenberg modelon the triangular lattice in a magnetic field,
the Hamiltonian is given by
X
1X
H=
Jij Si · Sj − H
Siz
(1)
2
i,j

i

with Jij = J1 δj∈N 1(i) +J3 δj∈N 3(i) , where N n(i)denotes the nth nearest neighbor sites of site
i. For ferromagnetic J1 and antiferromagnetic
J3 , it was shown by Okubo, Chung, and Kawamura [1] that single-Q, double-Q, and tripleQ states are stabilized in the low, middle, andhigh field regions, respectively. In particular,
the triple-Q state is known to be the skyrmion
lattice phase, and its higher-temperature region is another phase, the so-called Z phase, inwhich there are randomly distributed domainsof the skyrmion and antiskyrmion lattices.
The spin current and the associated spins are respectively given by
conductivity σµνJzs (t)
s
σµν

1X
= −
Jij rij (Si × Sj )z ,
2
i,j
Z ∞
1
z
z
=
dt hJs,ν(0) Js,µ(t)i, (2)
T L2 0where rij and L denote a vector connecting two

280

sites i and j and the linear system size, respectively. We numerically integrate the semiclassical equation of motion with initial equilibrium spin configurations generated by Monte
Carlo simulations and calculate the time correz (0) J z (t)i at each time step [2, 3].
lations hJs,ν
s,µIt is found that the longitudinal spin-currents is significantly enhanced at
conductivity σxx
the transition temperature between the tripleQ and Z phases, whereas at the highertemperature transition between the Z andparamagnetic phases, such an anomalous behavior is not obtained. This enhancement ofs is quite similar to the divergent behavior ofσxx
s at the Kosterlitz-Thouless-type topological
σxxtransition [2, 3] in which long-lifetime vortex
excitations play a crucial role. In the present
case, the topological object of the skyrmion
may be relevant to the spin transport, but further analysis is necessary to understand theorigin of the significant enhancement of thespin-current conductivity at the transition into
the skyrmion lattice phase.

References[1] T. Okubo, S. Chung, and H. Kawamura,Phys. Rev. Lett. 108, 017206 (2012).
[2] K. Aoyama and H. Kawamura, Phys. Rev.
B 100, 144416 (2019).
[3] K. Aoyama and H. Kawamura, Phys. Rev.
Lett. 124, 047202 (2020).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1/N bias of the hump of Binder parameter for Potts
Model
Hiroshi WATANABE
Department of Applied Physics and Physico-Informatics, Keio University
Yokohama, Kanagawa 223-8522, Japan

from the strong 1/N bias of the Binder parameter as it is a function of the expected value.
Therefore, this bias can be removed by the
jackknife resampling method. However, sincethe 1/N bias is removed and the N -infinity
limit still exhibit system-size-dependence, thefinite size scaling function appears to be system size dependent. The size-dependence ofthe peak position is stronger for larger valuesof Q, and the peak value is expected to be
infinite at N infinity for systems involving thefirst-order transition. The existence of the universal finite-size scaling function in the limit of
infinite system size for systems involving thecontinuous transitions is still non-trivial, andtherefore, the further study is required.
1.6

L= 64
L=128
L=256
L=512

1.58
1.56
1.54
1.52
Ulow

The Binder parameter has been widely used
to analyze critical phenomena [1]. Since theparameter is the dimensionless, the parameters for different system sizes are collapsed
into a single curve by scaling only horizontal
axis. The Binder parameter is usually a monotonic function, but it sometimes peculiar behavior. A typical example of this is the Potts
model. The Binder parameter of the Potts
model is non-monotonic function and exhibits
a hump near the criticality. Since the hump
has the system-size dependence, the Biner parameter of Potts model cannot be collapsed
into a single curve by scaling only horizontal
axis. The humps become larger as the system size increases and these humps interferewith the finite-size scaling analysis especiallyfor the high-temperature side of the criticalpoint. We also found that the peak value ofthe hump strongly depends on the MCs as
well as the system size. In order to identify
the origin of the hump, we study the Binder
parameter of Q = 3 Potts model. We foundthat the Binder parameter can be decomposed
into a high- and a low-temperature components, and that the humps originate from thelow-temperature one. THe system size andMCs dependence of the peak value of the lowtemperature component of the Binder parameter Ulow is shown in Fig. 1. One can see that
the MCs dependence becomes large as the system size increases. These MCs dependence arefound to be almost independent of the relaxation time. The MCs dependence originate

1.5
1.48
1.46
1.44
1.42
1.4

0

0.0005

0.001
1/MCs

0.00150.002

Figure 1: The system size and MCs dependence of the peak value.

References[1] K. Binder, Z. Phys. B Cond. Matt. , vol.
43, pp. 119-140 (1981).

281

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Magnetism in the Multiple-Spin Exchange Modelon the Honeycomb Lattice
Chitoshi YASUDA
Department of Physics and Earth Sciences, Faculty of Science,
University of the Ryukyus, Okinawa 903-0213, Japan
3 He atoms adsorbed on graphite form theto a metastable state. When the external
magnetic ﬁeld is zero, the ground state in
the region where the contribution of the sixbody exchange interaction is small becomesan antiferromagnetic state. This is the sameground state as the antiferromagnetic Heisenberg model on the honeycomb lattice. On theother hand, in the region where the contribution of the six-body exchange interaction
is large, the eight-sublattice structure with anearest-neighbor correlation function and aﬁnite sublattice scalar chirality is stabilized
as the ground state. When an external magnetic ﬁeld is applied, the antiferromagnetic
state becomes the canted state at very smallﬁelds, while the eight-sublattice structure canbe maintained up to a certain ﬁnite ﬁeld.
When the applied magnetic ﬁeld is increased,
the eight-sublattice structure changes to thelarge sublattice structure, the four-sublattice
structure, and the canted state, sequentially.
In this project, we also research thermodynamic properties of the classical MSE modelusing the Monte Carlo simulation with theexchange Monte Carlo method. We conﬁrm
its usefulness in the classical MSE model on
the honeycomb lattice.

commensurate solid layer regarded as the
spin-1/2 quantum spin system on a triangular lattice at a certain density of 3 He.
There are not only an exchange of 3 He atoms
between two neighbor atoms but also thatamong three or more neighbor atoms. In relation to the solid 3 He, the multiple-spin exchange (MSE) model on the triangular lattice has been extensively studied. Groundstates and thermodynamic properties of themodel have been investigated using various
methods [1,2,3]. In particular, the model has
attracted attention owing to the existence ofnovel states such as the quantum spin liquid and the spin-nematic state, and owing to
the eﬀects of ﬂuctuations on ordered phaseswith chirality. Recently, a new quantum spin
liquid is experimentally observed in the solid
3 He layer. This layer is a monolayer 3 He adsorbed on graphite preplated with atomic layers of deuterium hydride. At low density of
3 He, it was suggested that there exists thequantum spin liquid with novel dependencesof the heat capacity and the magnetic susceptibility on temperature. The details of thisexperimental work are not yet clear, however,
it is suggested that the solid 3 He layer forms
a honeycomb lattice.

References[1] C. Yasuda, D. Kinouchi, K. Kubo: J.
Phys. Soc. Jpn. 75 (2006) 104705.

In this project, we research the classical
MSE model with the two-spin and six-bodyring exchange interactions on the honeycomb
lattice using numerical methods. The groundstate is investigated using the conjugate gradient method. In this method, we need toprepare many random spin states as the initial states because of avoidance of the trap[2] C. Yasuda, Y. Uchihira, S. Taira, K.
Kubo: J. Phys. Soc. Jpn. 87 (2018)
104704.
[3] S. Taira, C. Yasuda, T. Momoi, K.
Kubo: J. Phys. Soc. Jpn. 88 (2019)014701.

282

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Microwave transmission through a Josephson
junction array
Tsuyoshi YAMAMOTO
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

Recent technological development enables us
to perform quantum simulation using artiﬁcial
quantum systems . Its use for solving quantum many-body problems is one of hot topics in condensed matter physics. The superconducting circuits are one of promising platforms for such an attempt. However, background random charge in superconducting circuits hinders a “good” simulation. Our study
facilitates the opposite view. Namely, randomness in a circuit provides to simulate quantum
disordered systems [1].
In one-dimensional systems, localization occurs no matter how the disorder is weak.
While disorder in the one-dimension systemwith long-range interactions induces a transition into an insulating phase, its properties
is known little. In this study [2], we show
microwave transmission through a Josephson
junction array which represents one of the simplest one-dimension disordered systems with
the Coulomb interaction.
A one-dimensional nature of the system allows for the most comprehensive analytical andnumerical approaches. We ﬁnd signatures of
the insulating modes in the microwave transmission for a wide frequency range. At highfrequencies, the high accurate numerics reveals
that the localization property aﬀects the microwave transmission, which has been missedin the previous work [3], by the detailed comparison with the analytics (Fig. 1). At low
frequencies, by performing the parallel computation with respect to conﬁgurations to take a

Figure 1: The frequency dependence of thetransmission. The green line is the numerics
and the black dashed line is the analytics.
disorder average, we gather several non-trivial
pieces of information about statistics of thetransmission.
The versatility of the design of Josephsonjunction arrays motivates their further development for quantum simulation.

References[1] R. Kuzmin et al., Nat. Phys. 15, 930(2019).
[2] T. Yamamoto, L. I. Glazman, and M.
Houzet, Phys. Rev. B 103, 224211 (2021).
[3] M. Houzet and L. I. Glazman, Phys. Rev.
Lett. 122, 237701 (2019).

283

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Molecular dynamics simulation of liquid BaTiO3
T. Hashimoto
National Institute of Advanced Industrial Science and Technology (AIST),
Tsukuba Central 2, 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, JapanThe structure of oxides in a liquid state
at high temperature is being studied by thecontainerless method using a floating furnace. The field strength is expressed as F =ZM /(rMO − rO )2 , where ZM , rMO , and rO are
the cation charge, the bond length of the cationand oxygen, and the ionic radius of oxygen. In
SiO2 , which has a large F , the coordination
number of oxygen around Si, whether solid or
liquid, is 4, but in ZrO2 , Y2 O3 , etc., where F
is small, the coordination number of oxygenaround the cation drops significantly in thecase of liquids[1]. Ti has an F value in the
middle of them, but in the case of BaTi2 O5 , it
has been reported that nTiO drops significantly
from the crystalline case to the liquid case[2].
Furthermore, it has been reported that thetemperature dependence of rTiO and nTiO is∂rTiO /∂T < 0 and ∂rTiO /∂T < 0. In the caseof BaTiO3 , it was reported by X-ray scatteringand neutron scattering by 46 Ti-rich and 48 Tirich samples that nTiO is reduced from 6 forcrystals to about 4.4 for liquids at 2073 K[4].
However, the temperature dependences of rTiO
and nTiO are not known. In addition, the validity of the partial radial distribution function
obtained by the empirical potential structurerefinement (EPSR) method using experimental
data has not been fully investigated. We calculated the structure of liquid BaTiO3 by firstprinciples molecular dynamics simulations.
The calculations were performed using
the plane wave pseudopotential method(QUANTUM-ESPRESSO), ultrasoft pseudopotential (GBRV), and GGA (PBE). The
density data from Paradis et al.[4] was ex-

trapolated to the high temperature side andlow temperature side. We calculated at 3500,
3000, 2500, 2000, 1500, 900 K using 135
atoms, using the (N, V, T ) ensemble and thevelocity scaling method.
The partial radial distribution functions of
the liquid BaTiO3 at 2000 K obtained bythis study[5] were compared with those by the
EPSR method at 2073 K[3]. The Ti-O results were in good agreement with each other,but Ba-Ba and Ti-Ti results were inconsistent.
The reason for this is that the pair weighting
factor contained in S(Q) is small for both neutron scattering and X-ray scattering, especiallyfor Ti-Ti, so there is a possibility that the interatomic interaction cannot be obtained correctly by the EPSR method. However, rTiO
and nTiO were in good agreement with the experiment. Liquid BaTiO3 had the same temperature dependence of rTiO and nTiO as liquid
BaTi2 O5 .
[1] L. Skinner et al., Phys. Rev. Lett. 112,157801 (2014).
[2] O. L. G. Alderman et al., J. Phys. Chem.
C 120, 26974 (2016).
[3] O. L. G. Alderman et al., J. Phys.: Condens. Matter 31, 20LT01 (2019).
[4] P.-F. Paradis et al., Appl. Phys. A 79,
1965 (2004).
[5] T. Hashimoto et al., J. Phys. Soc. Jpn 90,
044604 (2021).

284

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Tensor-Network Renormalization Study ofFinite-Size Conformal Spectrum
Atsushi Ueda and Masaki Oshikawa
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581
April 30, 2021

We have studied the finite-size effects of classical 2D systems, using Tensor Network Renormalization(TNR). Based on the finite-size scaling theory of conformal field theory(CFT) [1],we demonstrated that it is possible to reconstruct an effective quantum Hamiltonian
from the spectrum of the renormalized tensors. Tracking the effective Hamiltonian ateach scale allows to numerically construct therenormalization group (RG) flow. We performed it for the classical Ising and XY model
as concrete examples, as shown in Figs. 1
and 2.
Figure 1: The numerically computed RG flowof the Ising model. t and h denote the deviations from the fixed point, corresponding to
the reduced temperature T − Tc and the magnetic field. The RG flows away from the fixed
point induced by the relevant perturbations t
and h are visualized.

285

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

of Physics C: Solid State Physics 7, 1046
(1974).
[3] Frank Pollmann, Subroto Mukerjee, Ari
M Turner, and Joel E Moore, Theory of finite-entanglement scaling at
one-dimensional quantum critical points,
Physical Review Letters, 102(25):255701,(2009).
[4] A. Ueda and M. Oshikawa, in preparation.

Figure 2: The numerically computed RG flowof the XY model. yK and yV are the perturbations corresponding to the spin-wave stiffness
and the vortex fugacity, respectively. Our numerical construction gives a quantitative verification of the celebrated Kosterlitz RG flow [2].
Throughout the study above, we also investigated the effect of the finite bond cutoff,which had been often overlooked previously.
We showed that there emerges an effective correlation length ξD = Dκ that is observed for
Matrix Product State(MPS) [3], by mapping
renormalized tensors to a reduced density matrix. As the exponent κ becomes smaller when
the central charge c is large, the focus of ourstudy (c = 2) turns out to call for a massive
calculation. Thus, we are in attempt to implement a parallel computation of TNR with thesupercomputer. More details of our study will
be reported elsewhere [4].

References[1] J. L. Cardy, Conformal invariance anduniversality in finite-size scaling, Journalof Physics A: Mathematical and General
17, L385 (1984).
[2] J. M. Kosterlitz, The critical propertiesof the two-dimensional xy model, Journal286

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Magnetic field dependence of the thermal Hall eﬀect
based on the augmented quasiclassical equations
Takafumi KITA
Department of Physics, Hokkaido University
Sapporo, 060-0810

Charging of vortices in the equilibrium superconducting state was studied before calculating linear responses such as the thermal Halleﬀect. The results are reported below.
Vortices in type-II superconductors have not
only a single magnetic flux quantum but also
accumulated charge. It is known that thevortex-core charging is caused by three forces:(i) the Lorentz force [1], (ii) pair-potentialgradient (PPG) force [2], and (iii) the pressure diﬀerence arising from the slope in thedensity of states (SDOS) [3]. Recently, augmented quasiclassical (AQC) equations withthese forces were derived by incorporating thenext-to-leading-order contributions in the expansion of the Gor’kov equations in terms of
the quasiclassical parameter δ ≡ 1/kF ξ0 [4],where kF is the Fermi wavenumber and ξ0 is
the coherence length. Numerous studies on
the charging in an isolated vortex were performed [4], but the magnetic field dependenceof the vortex-charging has not been fully calculated. To this end, we calculated the vortexcore charging in two-dimensional s-wave superconductors with the Abrikosov vortex lattice
due to the Lorentz and PPG forces by using the
AQC equations. The SDOS pressure is now
absent for this case with the cylindrical Fermi
surface. The fixed parameters are the magnetic penetration depth as λ0 = 5ξ0 , Thomas–
Fermi screening length as λTF = 0.03ξ0 , andquasiclassical parameter as δ = 0.03.
Figure 1 plots the spatial variation of thecharge density due to the Lorentz and PPG

forces at temperature T = 0.2Tc and the average flux densities B̄ = 0.15Bc2 , 0.42Bc2 , and
0.88Bc2 , respectively, where Tc is the transition temperature and Bc2 is the upper critical field. Figure 2 shows the spatial variationof the charge density due to the PPG force attemperatures T = 0.2Tc and 0.5Tc , respectively.
The charge caused by the Lorentz force has astrong field dependence with a peak and canbe enhanced substantially from the value of an
isolated vortex as shown in our previous work[5]. Moreover, we show in this report that the
charge caused by the PPG force monotonicallydecreases as the magnetic field increases.
These calculations require a fine mesh ofspace and momenta when diﬀerentiating theGreen’s functions and self-energies numerically. Therefore, we performed parallel calculations using the ISSP supercomputer.

References[1] F. London, Superfluids (Dover, New York,1961), Vol. 1, p. 56.
[2] N. B. Kopnin, J. Low Temp. Phys. 97(1994) 157.
[3] D. I. Khomskii and A. Freimuth, Phys.
Rev. Lett. 75 (1995) 1384.
[4] H. Ueki, M. Ohuchi, and T. Kita, J. Phys.
Soc. Jpn. 87 (2018) 044704.
[5] W. Kohno, H. Ueki, and T. Kita, J. Phys.
Soc. Jpn. 85 (2016) 083705.

287

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo(a) Lorentz, B̄ = 0.15Bc2(b) Lorentz, B̄ = 0.42Bc2(c) Lorentz, B̄ = 0.88Bc2(d) PPG, B̄ = 0.15Bc2(e) PPG, B̄ = 0.42Bc2(f) PPG, B̄ = 0.88Bc2

Figure 1: Spatial dependence of the charge density ρ(r) due to the Lorentz force ((a), (b), and(c)), and the PPG force ((d), (e), and (f)) at temperature T = 0.2Tc in units of ρ0 ≡ ∆0 ϵ0 d/|e|ξ02
on a square grid with x and y ranging from [−2ξ0 , +2ξ0 ] for the average flux densities B̄ =0.15Bc2 , 0.42Bc2 , and 0.88Bc2 from left to right, respectively. ∆0 is the energy gap at zerotemperature and zero fields, ϵ0 is the the vacuum permittivity, d is the thickness, and e < 0 is
the electron charge.
(a) T = 0.2Tc(b) T = 0.5Tc

70

2

Total

Total
1.5

50

ρ(0)/ρ0ρ(0)/ρ060

Lorentz
40

Lorentz
1

30
20

PPG

0.5

PPG

10
00

0.2

0.4

0.6

0.8

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0.2

0.4

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Figure 2: Magnetic field dependence of the charge density at the vortex center ρ(0) due to theLorentz force (green circular points), the PPG force (blue square points), and the total force(red triangular points), in units of ρ0 ≡ ∆0 ϵ0 d/|e|ξ02 as a function of the magnetic field, attemperatures (a) T = 0.2Tc and (b) 0.5Tc from left to right.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Calculation of ordered structures, dynamics and opticalproperties of soft materials
Jun-ichi FUKUDA
Department of Physics, Kyushu University, Motooka 744, Nishi-ku, Fukuoka 819-0395
We studied the structural properties offree energy with the variation of the direction

cholesteric blue phases, three dimensionalof the alignment imposed by the surface. We

ordered structures exhibited by a chiral liquidconsidered two cases commonly observed

crystal. We particularly focused on how theexperimentally: BPI with its (110) planes

cubic lattice of blue phases (BPI with O8

parallel to the surface(s) and BPII with its (100)symmetry and BPII with O2 symmetry) is

planes parallel to the surface(s). In both cases,

oriented when in contact with confining

the blue phase lattice adopts one specific latticesurface(s) that impose unidirectional surface

orientation that minimizes the free energy. The

alignment of the liquid crystal (unidirectionalsurface anchoring strength of 10-5 Jm-2, easily

surface anchoring). Our study was motivatedachievable experimentally, was shown to be

by a recent experimental study [1] thatsufficient to lock the lattice orientation. Ourdemonstrated specific lattice orientation of blue

finding is consistent with some of thephases in contact with such surfaces.

experimental observations, but unfortunately

Our study [2] was based on a continuum

not all. Our study provides a starting point fortheory describing the orientational order of athe understanding of how the blue phase latticeliquid crystal by a second-rank tensor (Landau-

is oriented in response to the surface anchoring,de Gennes theory). The free energy of thewhich is strongly desired for practical opticalliquid crystal was given as a functional of theapplication of blue phases that requires thetensor order parameter, and the profile ofpreparation of large-scale monodomain lattices.

orientational order was obtained by minimizing
the free energy numerically. The discretization

Referencesof the liquid crystal system by a regular grid[1] M. Takahashi et al.: J. Phys. D: Appl. Phys.

allows an efficient use of OpenMP (Our system

51, 104003 (2018).

was not large enough to require the use of MPI).

[2] J. Fukuda and S. Zumer: Phys. Rev. Res. 2,

We carried out systematic evaluation of the033407 (2020).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Molecular simulation of colloidal particles
Takamichi TERAO
Department of Electrical, Electronic and Computer Engineering,
Gifu University, Yanagido 1-1, Gifu, 501-1132
Structural formation of colloidal particles

in aggregates were also quantitatively clarified.

have been studied both theoretically andFrom these studies, we have been able toexperimentally for many years. In previous

clarify the behavior of patchy particle systems

studies, spherical colloidal particles with

with respect to the formation of various

isotropic

structures.

interparticle

interaction

wereinvestigated. Recently, there has been a great
deal of research on colloidal systems withanisotropic interactions. A typical example isthe so-called patchy particle system, in whichanisotropic interparticle interaction exists.
The aggregation phenomena of colloidal
particles have been a long-standing interest [1].
In

this

study,

we

performed

computerFig. 1: Snapshot of patchy particles.

simulations of the aggregation phenomenon inpatchy particles and clarified their structureformation. In Fig. 1, an example of thesnapshot of patchy particles with four patches
is shown. In particular, we have quantitatively
clarified the sol-gel transition and the phase
diagram of the system (Figure 2). In this figure,the abscissa and the ordinate denote therescaled dimensionless temperature and theFig. 2: Phase diagram of patchy particles.

volume fraction of the system, respectively. In
this figure, the red squares show that the patchy

References

particles form a gel network with these sets

[1] N. E. Valadez-Pérez, Y. Liu, and R.

volume fraction and temperatures. The cluster

Castañeda-Priego: Phys. Rev. Lett. 120 (2018)

size distribution and the static structure factor

248004.

290

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

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292

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Coarsening mechanism in mass-conserved
reaction-diﬀusion systems
Michio Tateno and Shuji Ishihara
Graduate School of Arts and Sciences, The University of Tokyo
Universal Biology Institute, The University of Tokyo
Komaba 3-8-1, Meguro-ku, Tokyo 153-8902

Reaction-diﬀusion systems (RDs) are central
mathematical scheme that comprehensively
describe molecular assemblies driven by chemical reactions, and have tremendously contributed to our understanding of pattern formation observed in nature, particularly thosein biological systems. Nearly 14 years ago, it
was reported that in RDs satisfying the massconservation law (MCRDs), patterns exhibit
coarsening and result in formation of single isolated domain, unlike usual behavior of RDs [1].
MCRDs were originally introduced and havebeen discussed as models for molecular localization such as membrane-bounded GTPases
which are responsible for the formation of cell
polarity [1]. Recently the relevance of MCRDs
has been recognized in a broad range of biological phenomena such as oscillatory motion
in min-Protein and chemical turbulence (see,e.g,[2]. Despite its uniquity and fundamental importance, the physical mechanism underlying coarsening behavior in MCRDs remains
elusive. This is partially because most of earlier studies only investigated one-dimensional
systems. Considering the fact that morphology of the patterns is strongly inﬂuenced byspatial dimensions, an intensive study in highdimension is highly desirable.
In this project, we realize a large-scale
MCRD simulation in both two and three dimensions using multiple GPUs, and successfully capture coarsening dynamics of MCRDs
in high dimension with statistical signiﬁcanceFigure 1: A spatial pattern obtained from athree-dimensional simulation. A contour surface indicates the interface between bistablestates. The color is labeled according to
the value of chemical-potential-like quantity in
MCRDs. The numerical simulation was performed in a cubic lattice of 10243 .

for the ﬁrst time (see Fig. 1). We havean eye on similarity between coarsening dynamics in MCRDs and classical phase separation systems, and apply analysis methods
established in thermodynamic phase transition (dynamic scaling law, nucleation-growth
process, etc.)
to the simulation results.
We reveal that droplets forming in MCRDs
obey the Young-Laplace law and coarsen following the evaporation-condensation (LifshitzSlyosov-Wagner) mechanism (see Fig. 2).
These outcomes indicate that in the presenceof conserved variable, a physical quantity similar to surface tension is relevant to RDs,

293

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 2: a Droplet-radius distribution ρ(R)for various time t. b. Dynamic scaling of
ρ based on Lifshitz–Slyozov–Wagner theory.
The symbol shows the same simulation results
as in panel a. The red dashed lines represent
theoretical predictions for the scaled distribution N (R/Rc ) [4], where Rc is critical radius.
which provides new insight into molecular selfassembly driven by chemical reactions. The
result is now under review in an international
peer reviewed journal, and the preprint is uploaded in an online paper repository [3].

References[1] M. Otsuji, S. Ishihara, et al.: PLOS Comput. Biol. 3, (2007) 1.; S. Ishihara, M. Otsuji and A. Mochizuki: Phys. Rev. E 75,(2007) 015203.
[2] E. Frey, J. Halatek, et al.: Physics of Biological Membranes, Springer International
Publishing, pp.229-260 ; J. Halatek and E.
Frey: Nat. Phys. 14, (2018) 507.
[3] http://arxiv.org/abs/2010.03900[4] J. H. Yao, K. R. Elder, et al.: Phys. Rev.
B 47, (1993) 14110.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Multicellular simulation by phase ﬁeld method
Michio Tateno and Shuji Ishihara
Graduate School of Arts and Sciences, The University of Tokyo
Universal Biology Institute, The University of Tokyo
Komaba 3-8-1, Meguro-ku, Tokyo 153-8902

The central aim of this project is to establish a multicellular simulation method thatcan capture multiscale dynamics, ranging fromintracellular chemical concentration, shapechanges of cells, to their collective motions in
a tissue scale. To realize this, we adopted thephase ﬁeld (PF) model, which can express cellswith arbitrary shape. In this method, an auxiliary ﬁeld (phase ﬁeld) which obeys a bistableenergy functional is introduced to distinguishthe inside and outside of a cell. This procedure allows us to describe the time evolutionof cell shape via interfacial dynamics without
suﬀering from moving boundary problems.
One of the authors (SI) and coworkers combined PF model with a reaction-diﬀusion system, in which a bistable and excitable chemical network is incorporated to model cell migration driven by F-actin. They demonstrated
that this model can precisely reproduce complex motion of amoebic cells (Dictyostelium atearly starvation stage) as well as intracellularchemical waves related to actin polymerization[1]. In this term, we have made an attempt toextend this PF model to multicellular systems.
In PF model for a single cell, a square moving frame with lattice size L2 is provided tocompute the phase ﬁeld. Here L should be
suﬃciently larger than the cell size (typically L
being hundreds of order) to capture the complex morphology of a cell and avoid the cellfrom overhanging the frame. When increase
the cells, of course, the computational cost is
not simply scaled by the number of cells N ;one need to deal with overlap regions among

Figure 1: a. Adaptive moving frame (gray areas) is used in our PF model. This largely reduces the computational cost for intercellularinteractions (the region surrounded by a dotted line). The white and blue regions represent
the distributions of PIP3 and PTEN, respectively. b. A snapshot of multicelluar simulation with 100 cells.
the frames for diﬀerent cells, to compute intercelluar interactions such as steric eﬀect or celladhesion, which is a computation bottleneck.
The resulting computational cost was roughly
the order of 10 × N L2 .
To overcome this problem, we improve thecomputational eﬃciency by updating the moving frames to adapt to the shape of cells. Figure 1a show the computational regions for twocells (gray rectangle areas). The area surrounded by a dotted line represent the region
required to compute the intercelluar interaction between the cells. Using this algorithm
and GPU, we have speeded up the computation by four times and realized simulation withorder of 100 cells as shown in Fig. 1b. In thefurther, we plan to apply our program to speciﬁc problems such ﬂuidity transition or cell295

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

sorting of a epithelial tissue.

References[1] D. Taniguchi, Ishihara, et al.: Proc. Natl.
Acad. Sci. USA 110, (2013) 5016.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Universal properties of dissipated many-bodyquantum systems
Tatsuhiko Shirai
Department of Computer Science and Communications Engineering, Waseda University
Ookubo, Shinjuku-ku, Tokyo 169-8555

We have studied two diﬀerent types of nonequilibrium quantum systems: bulk-dissipatedsystems and boundary-dissipated systems.

1

Bulk-dissipated systems

In the bulk-dissipated systems, the dissipativeenvironments are uniformly coupled to the system of interest. We consider that the systemenvrionment coupling is weak and the environment is nonequilibrium (i.e., the detailed balance condition is broken). The reference [1]has argued that the Gibbs state at an eﬀective temperature gives a good description of
the nonequilibrium steady state provided thatthe system Hamiltonian obeys the eigenstate
thermalization hypothesis and the perturbation theory in the weak system-environment
coupling is valid in the thermodynamic limit.
The numerics are based on the exact diagonalization method, which restricts the system sizestudied. We have developed a tensor-network
approach that directly studies not only thesteady states but also the relaxation dynamics in the thermodynamic limit [2]. The study
reveals that when an initial state is given by athermal Gibbs state, the states during the relaxation dynamics are well described by Gibbs
states with a time-dependent eﬀective temperature.

2

Boundary-dissipated
tems

sys-

We discussed the relaxation time of theboundary-dissipated systems, where the environments with diﬀerent thermodynamic potentials (e.g., temperature and chemical potential) are coupled to the edges of the nonintegrable systems. The presence of the diffusive transport indicates that the relaxation
time τ is proportional to the square of thesystem size L (i.e., τ ∼ L2 ). The relaxation time is naively related to the gap of thetime-evolution operator called the Liouvillion,
but the previous studies have shown that thegap closing is slower than L−2 [3]. We have
solved this discrepancy by numerically showingthat the relaxation time is not determined by
the lower-lying eigenvalues of the Liouvillion
but by superexponentially large expansion coeﬃcients for Liouvillion eigenvector with nonsmall eigenvalues at an initial state [4].

References[1] T. Shirai, and T. Mori: Phys. Rev. E 101(2020) 042116.
[2] H. Nakano, T. Shirai, and T. Mori:arXiv:2012.12274.
[3] M. Žnidarič, Phys. Rev. E 92 (2015)
042143.
[4] T. Mori, and T. Shirai: Phys. Rev. Lett.
125 (2020) 230604.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Quantum annealing in transverse-ﬁeld Ising chainswith a correlated disorder
Tatsuhiko Shirai
Department of Computer Science and Communications Engineering, Waseda University
Ookubo, Shinjuku-ku, Tokyo 169-8555

We have studied disordered Ising chains under transverse ﬁelds to examine the eﬀects ofa correlated disorder on quantum phase transitions. The Hamiltonian is given by
H=−

N
−1
∑
i=1

z
Ji σiz σi+1−N∑

Γi σix ,(1)

i=1

where ⃗σi = (σix , σiy , σiz ) are Pauli spin matrices, and Ji and Γi denote nearest-neighbor coupling strength and transverse-ﬁeld strength,
respectively. Ji is chosen from two diﬀerent
types of distribution: weak disorder and strong
disorder. The distribution in the weak disorder case is uniform over (J (0) , 1] and gapped(i.e., J (0) > 0), and thus given as{(1 − J (0) )−1 for J (0) < Ji ≤ 1,
πw (Ji ) =0 otherwise.
(2)
On the other hand, the distribution in thestrong disorder case is a gapless power-law distribution over (0, 1] given as
1 1 J −1+ D for 0 < J ≤ 1,iiπs (Ji ) = D(3)0 otherwise,
where D > 0 denotes the disorder strength.
In the correlated disorder case, the transverseﬁelds are given byΓ1= (1 − s) ln J1 ,
ln


Γ




 ln Γi = s ln J
i−1 + (1 − s) ln Ji
Γ
(4)


for
2
≤
i
≤
N
−
1,






 ln ΓN = s ln JN −1 ,Γwhere s ∈ [0, 1] is a parameter for tuning thetransverse ﬁelds.
In. [1], we analytically show that the dynamical critical exponents z in the system with thecorrelated disorder are ﬁnite: z = 1 in the
weak disorder case and max(D(1/2+|s−1/2|+
1/2), 1) ≤ z ≤ D + 1 in the strong-disordercase. We numerically estimate z in the strong
disorder case. The numerics is based on the
Jordan–Wigner transformation and an exact
diagonalization method [2]. The ﬁnite z is incontrast to inﬁnite z obtained in the uncorrelated disordered Ising chains (i.e., no correlation between the transverse ﬁelds and nearestneighbor couplings) [2, 3]. The suppression ofz is useful to enhance the performance of adiabatic quantum computations including quantum annealing with an argument based on the
Kibble–Zurek mechanism.

References[1] T.
Shirai,andS.
arXiv:2007.07439 (2020).

Tanaka:[2] A. P. Young and H. Rieger: Phys. Rev. B
53 (1996) 8486.
[3] D. S. Fisher: Phys. Rev. Lett. 69 (1992)
534.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Study of superstructure induced novel phenomena: stacking
of atomically thin materials
Toshikaze KARIYADOInternational Center for Materials Nanoarchitectonics,
National Institute for Materials Science, Namiki, Tsukuba, Ibaraki 305-0044
The purpose of this study is to propose ashift dependence of layer-layer distance, which

new design for van der Waals heterostructures

is derived by computing the binding energy as aof atomically thin materials to realize novel

function of layer-layer distance with rev-vdW-

phases or phenomena. Particularly, we focus on

DF2 type functional to take account of the van

twisted bilayers, where two layers are stacked

der Waal force. Once the layer-layer distance iswith angle mismatch. When the relative angle

fixed, the electronic structure is computed

is small, the system shows a long-range

using PBE-GGA type functional.

structure called moiré pattern that can induce

Overall, we have to scan over the possible

novel physics. With the small relative angle, a

relative in-plane shift, and therefore, it is

twisted bilayer system locally resembles to aimportant to make a calculation for eachbilayer system without twist, but globally, theparameter as light as possible. In that

relative in-plane shift between two layers

perspective, MPI parallelization implemented

depends on position due to the twist. Then, it isin Quantum Espresso package helps us a lot if

a powerful scheme to analyze crystalline andit is used on a massively parallel computational

electronic structures for untwisted bilayers andsystem.
In addition to the above project, we havescan over the possible relative in-plane shift.

analyzed

In this project, we have applied the above

diamagnetic

responses

inanprocedure on several candidate materials,

antiperovskite type Dirac electron system [1].

including graphene relatives and group-IV

The

monocalcogenide monolayers. For the analysis

compares well with the experimental result.

numericallyobtainedsusceptibilityof crystalline and electronic structures, we haveused the first-principles density functional

References

theory method implemented in Quantum[1] S. Suetsugu, K. Kitagawa, T. Kariyado, A.

Espresso package. One of the key quantities in

W. Rost, J. Nuss, C. Mühle, M. Ogata, and H.

crystalline structure analysis is relative in-plane

Takagi: Phys. Rev. B 103 (2021) 115117.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Numerical Study of One Dimensional Frustrated
Quantum Spin Systems
Kazuo HIDA
Professor Emeritus, Division of Material Science,
Graduate School of Science and Engineering,
Saitama University, Saitama, Saitama 338-8570

τl

(1)

1

S=τ =1/2

λ

Sl

Sl+1

1

(2)

τ =1

1
τl

p=1

1
msp

(1)

1

0.5

(2)

p=2
~0.807λc(∞)−

Figure 1: Structure of the diamond chain investigated in this work.
We investigate the ground-state phases of
mixed diamond chains described by the following Hamiltonian [1]:
H=

L [
∑

(1)

S l (τ l(2)+ τl )

l=1
]
(1)
(2)
(1) (2)+ (τ l + τ l )S l+1 + λτ l τ l ,
(1)

(1)

(2)

where S l , τ l and τ l are spin operators with(1)
(2)
magnitudes Sl = τl = 1/2 and τl = 1. The
number of the unit cells is denoted by L. Here,the parameter λ controls the frustration as depicted in Fig. 1. Deﬁning the composite spin
(1)(2)
operators T l as T l ≡ τ l + τ l , it is evident that ∀l [T 2l , H] = 0. Thus, we have L
good quantum numbers T 2l ≡ (Tl + 1)Tl whereTl = 1/2 and 3/2. The total Hilbert spaceof the Hamiltonian (1) consists of separated
subspaces, each of which is speciﬁed by a definite set of {Tl }. For large λ, ∀l Tl = 1/2.
Hence, the ground state is equivalent to thatof the uniform spin 1/2 chain, namely a gapless spin liquid. For λ ≤ 0, ∀l Tl = 3/2.
Hence, the ground state is a Lieb-Mattis ferrimagnetic phase with spontaneous magnetiza-

300

p≤38
0
0.6

0.7

p=3

p=4
λ

0.8

Figure 2: λ-dependence of msp calculated by
the inﬁnite size DMRG method.
tion msp = 1 per unit cell. For intermediate
λ, we ﬁnd a series of ferrimagnetic phases with
msp = 1/p where p takes positive integer values as shown in Fig. 2 based on the inﬁnitesize DMRG calculations for various conﬁgurations of {Tl }. The calculations for many different {Tl } are independent from each other.
Hence, they are suitable for the massively parallel system of the ISSP supercomputer center. The phases with p ≥ 2 are accompaniedby the spontaneous breakdown of the p-foldtranslational symmetry. It is suggested thatthe phase with arbitrarily large p, namely inﬁnitesimal spontaneous magnetization, is allowed as λ approaches the transition point to
the gapless spin liquid phase.

References[1] K. Hida, arXiv:2102.02116, to be published in J. Phys. Soc. Jpn.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of observation-noise estimation methodby machine learning
Ryo TAMURAInternational Center for Materials Nanoarchitectonics,
National Institute for Materials Science,
1-1 Namiki, Tsukuba, Ibaraki, 305-0044

To know the Hamiltonian of target materials, a data-driven approach is useful, in whichmodel parameters of Hamiltonian are determined so as to ﬁt the experimentally measured
data[1, 2, 3, 4]. In a data-driven approach, theposterior distribution is deﬁned, and the appropriate parameters are searched by a maximum a posteriori (MAP) estimation. Thus,
the Hamiltonian, which can well explain theexperimental results, is obtained by the framework of MAP estimation. However, by MAP
estimation, observation noise cannot be evaluated. The Hamiltonian estimation method
based on Bayesian inference is formulated under the assumption of ﬁnite observation noise.
Then, there must be errors in the estimatedparameters. Therefore, we proposed a method
to evaluate the error of the parameters by estimating the observation noise[5]．
In our framework, the noise amplitude σ isconsidered to be a hyperparameter, and a plausible value is determined by minimizing theBayes free energy F (σ), deﬁned as
F (σ) = − log Z(σ),(1)

where Z(σ) is the normalization of the posterior distribution given by(Z(σ) =

1
2πσ 2

)L ∫
2

dx exp [−E(x, σ)] . (2)ΩxHere, Ωx is the support of the posterior distribution determined by the prior distribution.
In addition, x is the model parameters in the

Hamiltonian and E(x, σ) is the energy function to be minimized in our model estimation.
To evaluate F (σ) , it is convenient to extend
the normalization factor with a “ﬁnite temperature”, which is deﬁned as(

Zβ (σ) =

1
2πσ 2

)L ∫
2

dx exp [−βE(x, σ)] , (3)Ωxwhere β is the inverse temperature. By usingZβ (σ), the Bayesian free-energy is deﬁned as
∫ 1

(

)

d
dβ
F (σ) = −log Zβ (σ) − log Z0 (σ)
dβ
0
∫ 1
)
(
L
dβ⟨E(x, σ)⟩β + log 2πσ 2
=
2
0
∫
− log

dx,

(4)

Ωx

where the ensemble average ⟨E(x, σ)⟩β can beobtained by the MCMC method. Here, thethird term on the right-hand side does not depend on σ and can be omitted. The noise amplitude of the experimental data σ ∗ is evaluated as the value where F (σ) is minimized.
This noise estimation method is applied forthe eﬀective model estimation of KCu4 P3 O12 .
As a result, we obtained the noise amplitude,
and the magnetic interactions with error bars
can be estimated as J1 = −8.54 ± 0.51 meV,J2 = −2.67 ± 1.13 meV, J3 = −3.90 ±0.15 meV, and J4 = 6.24 ± 0.95 meV, by using
our noise estimation method.
This work is the collaboration work withKoji Hukushima, Akira Matsuo, Koichi Kindo,and Masashi Hase.

301

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

References[1] R. Tamura and K. Hukushima, PLoS
ONE 13, e0193785 (2018).
[2] H. Takenaka, K. Nagata, T. Mizokawa,and M. Okada, J. Phys. Soc. Jpn. 83,
124706 (2014).
[3] R. Tamura and K. Hukushima, Phys. Rev.
B 95, 064407 (2017).
[4] H. Fujita, Y. O. Nakagawa, S Sugiura, and M. Oshikawa, Phys. Rev. B 97,
075114 (2018).
[5] R. Tamura, K. Hukushima, A. Matsuo,
K. Kindo, and M. Hase, Phys. Rev. B
101, 224435 (2020).

302

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Systematic Investigation on Phonon Transport at
Nanoscale Interfaces
Susumu FUJII
Nanostructures Research Laboratory, Japan Fine Ceramics Center
Mutsuno, Atsuta, Nagoya 456-8587

Grain boundaries and hetero interfaces are
known to suppress lattice thermal conductivity of a material dramatically, because of theirdisordered structures diﬀerent from the corresponding crystal structure(s). Recently, there
is an increasing demand for revealing the mechanisms of interfacial thermal conduction at thenanoscale, as electronic devices have become
miniaturized and nanostructuring techniques
have been extensively developed. However,there is a few studies that investigate the impact of interface atomic structures or interfacial scattering mechanisms of phonons that aredeﬁned in the reciprocal space, making it diﬃcult to obtain a guideline for controlling thermal conductivity on the basis of interfaces.
In the present study, we have mainly investigated the interfacial thermal conduction
across silicon grain boundaries (Fig. 1). We
chose silicon as a model material because it has
many technologically important applications
such as electronic devices and thermoelectrics.
We performed two types of molecular dynamics simulations: (1) perturbed molecular dynamics and (2) phonon wave packet. The former adds a small magnitude of perturbation toatoms and calculate thermal conductivity fromthe average of heat ﬂux of the system. The
latter introduces an phonon wave packet generated from a single phonon mode from phonon
dispersions and simulate its scattering process
at the interface. The necessary codes weredeveloped by the author and implemented to
the Large-scale Atomic/Molecular Massively

Parallel Simulator (LAMMPS) [1]. In addition, we used a machine learning potential
for Si distributed in MACHINE LEARNINGPOTENTIAL REPOSITORY [2], which aremuch less computationally demanding compared with density functional theory calculations but more demanding than the empiricalinteratomic potentials such as Stillinger-Weberand Tersoﬀ potentials.

Figure 1: An example of silicon grain boundary structure derived from the machine learning potential.
The perturbed molecular dynamics simulations require a large number of timesteps
more than one million and large computational
cells with a few thousands of atoms. On theother hand, phonon wave packet simulations
require a smaller number of timesteps less than
100000 but the computational cells must bevery long for the direction perpendicular to thegrain boundary plane and thus contain tensof thousands of atoms. The former were per-303

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

formed with ﬁve diﬀerent magnitudes of perturbations, and the latter were performed for
40 - 60 diﬀerent phonon modes for each grainboundary. Each of these calculations was performed in a single node.
The results perturbed molecular dynamics simulations show that thermal conductivity of Si grain boundaries signiﬁcantly correlates with their microscopic atomic structures rather than their energies. On the other
hand, our phonon wave packet simulations reveal that the phonon transmission (or reﬂaction) at the grain boundaries does not depends
on the grain boundary structures much, especially for the acoustic phonons that transfer most of heat. This contradicting trends
obtained from two kind of molecular dynamics simulations suggest that anharmonic eﬀect
of atomic vibrations at the grain boundaries,
which is naturally included in the perturbed
molecular dynamics while is intentionally neglected in the phonon wave packet simulations,is one of the dominant factors for determinig
interfacial thermal conduction.
In additon, comparisons of grain boundary structures, phonon properties and thermal conductivity between the machine learning potential and a classical interatomic potential (Tersoﬀ potential) demonstrate the highpredictive power of the machine learning potential. By combining machine learning potentials with supercomputers and advanced computational programs, it is becoming possible toquantitatively analyze interfacial thermal conduction.

References[1] S. Plimpton, J. Comput. Phys. 117 (1995)
1.
[2] A. Seko, arXiv:2007.14206.

304

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Developing numerical tool for open quantum dynamics basedon neural networks
Nobuyuki YOSHIOKA
Department of Applied Physics,
The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan, 113-8656.
In this project, we have planned to use neural

have shown that, the thermodynamic limit of the

networks to study the property of open quantum

strongly correlated hydrogen chain can be

many-body systems which are subject tocomputed within chemical accuracy.

dissipations that give rise to competition similar

In the second work, we have developed two

to “frustration” in closed quantum many-bodyalgorithms

that

simulates

systems. While the proposed project is currently

equilibrium of an isolated quantum many-bodyon-going, we have achieved some other works

system using deep neural networks. In one

regarding scalable simulations using neural

method, we exploit the quantum-to-classicalnetworks. In the following, we report the resultscorrespondencein such two works [1, 2].

representation of Gibbs state using the deep

toconstruct

the

the

thermalexact

In the first work, we have successfully

Boltzmann machine (DBM). This demonstrates

demonstrated a novel simulation algorithm thatthe expressibility of the DBM. In the otherperform first-principles calculation of solid-statemethod, we approximate the imaginary-timesystems. Namely, we have shown that theevolution to generate finite-temperature density

expressive power of neural networks arematrix starting from the infinite-temperaturesufficiently high so that the essential properties

Gibbs state. We have numerically demonstratedof solids, the ground state and the quasiparticle

that the second approach opens a door toband spectra, can be simulated both efficiently

scalable simulation even in frustrated systems

and accurately. The ground states are computed

where the thermal property is still under debate.

by the standard variational Monte Carlo manner,

Referencessuch that the imaginary-time evolution is[1] N. Yoshioka, W. Mizukami, and F. Nori,

realized approximately. This enables us toarXiv:2010.01358 (2020).

simulate the potential curve of various real[2] Y. Nomura, N. Yoshioka, and F. Nori,

solids including polymers, non-organic crystals,

arXiv:2103.04791 (2021).

or strongly correlated systems. In particular, we

305

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Quantum Monte Carlo study of theantiferromagnetic Ising model on a square latticewith longitudinal and transverse magnetic fields
Ryui KANEKO
Department of Physics, Kindai University
Higashi-Osaka, Osaka 577-8502, Japan
Analog quantum simulations have attracted
much interest recently. Ground-state properties and nonequilibrium dynamics of quantum
spin, SU(N) Heisenberg, and SU(N) Hubbard
systems have been extensively studied. It is
important to verify how far the simulation of
the experiment is correct by comparing numerical simulations on classical computers. It is aninteresting challenge to investigate the properties of complex models in static systems andthose in nonequilibrium systems using numerical methods such as tensor network algorithms.
On the other hand, it is also indispensable tostudy static properties in simple systems because it is much easier to compare the experiments and numerical simulations.
The Rydberg-atom systems are suitable forrealizing the fundamental spin models. The
quantum Ising models are frequently experimented with. The Hamiltonian is given as
XXXH=
Jij Siz Sjz − h
Siz − ΓSix . (1)
i,j

i

i

The longitudinal (transverse) field h (Γ) can
be controlled by the frequency detuning (theRabi frequency) of the laser [1]. The Ising interaction is given as van der Waals interaction,
whose long-range part is often ignored for simplicity [2].
Although the ground-state phase diagram of
the quantum Ising models on complex lattices
have been extensively investigated, the simple
model on a square lattice has yet to be ex-plored. The ground-state phase diagram was
obtained only for few dozen sites using the exact diagonalization method [3]. We investigate
the ground-state phase diagram of the modelon the square lattice using the quantum Monte
Carlo method with the DSQSS library [4]. We
typically choose 105 Monte Carlo steps for calculation of physical quantities and for thermalization. We use the system sizes Ns = L2
with L ≤ 32 and consider the periodic-periodic
boundary condition.
To determine the phase boundary, we calculate the staggered susceptibility defined ashM̂ z (Q)2 i, Q = (π, π),
(2)
βLd
Z β X
dτ
Ŝjz (τ )e−iq·rj , (3)and M̂ z (q) =χzzstag =

0j

where rj is the real space coordinate at site j,d(= 2) is the spatial dimension, and β is theinverse temperature.
We perform the finite-size scaling analysis
to determine the phase boundary between theantiferromagnetic and disordered phases. The
scaling form of χzz
stag is given as2−ηχzz
F(δL1/ν ),stag ∼ L(4)

where F is a scaling function, η is the anomalous dimension, and ν is the correlation length
exponent. The difference between the field andthe critical point is given as δ. Since the dynamical exponent would satisfy z = 1 for the306Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Disorder

h/J

2

1

0

AF order
0

0.5

1

1.5

Γ/J
Figure 1: Phase diagram of the antiferromagnetic Ising model on a square lattice with longitudinal and transverse magnetic fields.
Ising universality class, we choose the inverse
temperature β to be proportional to L during
the simulation.
Figure 1 shows the ground-state phase diagram of the mixed-field Ising model on thesquare lattice. When the transverse field Γ ∼0, the transition longitudinal field hc is nearly
intact as a function of Γ. On the other hand,when h ∼ 0, hc drops nearly vertically as afunction of Γ. The latter behavior is consis-

tent with the phase boundary obtained by themean-field approximation [5].
By scrutinizing the phase diagram near Γ ∼0, we have also uncovered the narrow region where the disordered phase exhibits reentrance. Our phase diagram [6] would be usefulfor examining the accuracy of the analog quantum simulation in the Rydberg-atom systems.

References[1] F. Robicheaux and J. V. Hernández,
Phys. Rev. A 72, 063403 (2005).
[2] A. Browaeys and T. Lahaye, Nat. Phys.
16, 132 (2020).
[3] V. Lienhard et al., Phys. Rev. X 8, 021070(2018).
[4] Y. Motoyama et al., Comput. Phys. Commun. 264, 107944 (2021).
[5] A. A. Ovchinnikov et al., Phys. Rev. B
68, 214406 (2003).
[6] R. Kaneko et al., arXiv:2103.12364

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical study for caged compound and its
conjugate acid/bases
Miyabi HIYAMA
Graduate School of Science and Technology, Gunma University,
Tenjin-cho, Kiryu, Gunma 376-8515

Caged luciferins, which can generate luciferin by UV photolytic reaction, would be
useful to understand the firefly bioluminescence. We synthesized the new caged luciferin named coumarin caged luciferin and obtained its absorption spectra [1]. When we use
this caged-luciferin for spectroscopic studies,
we need the detail of electronic states of thismolecule in aqueous solutions.
The optimization structure of ground state
for coumarin caged-luciferin anion expected
to be main component in the pH 8 aqueous solutions was obtained from the density
functional theory. The time dependent DFT(TDDFT) calculations were carried out to estimate the theoretical absorption spectra forthis structure. These theoretical spectra wereused to assign the experimental spectra measured at pH 8 [2]. However, these theoreticalresults cannot explain the diﬀerence between
the shape of absorption spectra of coumarin
caged luciferin at pH 3 and those at pH 8. We
expect that the main chemical species in theacidic experimental condition would be neutral
coumarin caged luciferin molecule of which total charge is 0.

of water solute molecules. We found thatthe absorption energy for neutral coumarin
caged luciferin is larger than that for coumarin
caged luciferin anion. It was also found thatthe shape of absorption spectra for neutral
coumarin caged luciferin has a large main
peak, while that for coumarin caged luciferin
anion has a double peak.
All calculations were performed using the
GAUSSIAN09 program [3] on system B and
C of Super Computer Center in ISSP.

References[1] Kurata et al. , J. Photochem. Photobiol.
B, 189 (2018) 81.
[2] Usukura et al. Photochem. Photobiol.
(2020) Photochem. Photobiol. (2020) 96,
805.
[3] Gaussian 09, Revision D.01, M. J. Frischet al.

In this year, we performed the DFT calculations for the neutral coumarin caged luciferin
molecule. The excitation energies and the oscillator strengths at the ground state were obtained using TDDFT calculations for the optimization structure of the neutral coumarin
caged luciferin molecule. The polarized continuum model was used for the description

308

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Exact diagonalization calculations of density of statesand dynamical structure factor for the
spherical-kagome spin-system {W72V30}
Yoshiyuki Fukumoto
Department of Physics, Faculty of Science and Technology, Tokyo University of Science
2641 Yamazaki, Noda, Chiba 278-8510

For the spherical-kagome cluster with thirty
spin-1/2s, as well as for the 2D kagome lattice,many low-energy singlet excitations have been
expected to exist in the energy region below
spin gap [1], which has been actually confirmed
by Kihara et al. in their specific heat measurements at low temperature in {W72 V30 } [2].
However, the experimental curve of the specific heat can not be reproduced by the theoretical curve in the Heisenberg model H =∑J ⟨i,j⟩ S i · S j , where ⟨i, j⟩ denote nearest
neighbors and the exchange parameter was estimated as J = 115K [1]. The experimental
curve does not have the peak around 2K, although the theoretical one has the 2K peak[1,2].
In last year, incorporating DzyaloshinskiiMoriya (DM) interactions and bond randomness into our model Hamiltonian, both ofwhich were originally proposed to explain theluck of the step-wise behaviour in the lowtemperature magnetization curve of {W72 V30 }[3,4], we used the method of thermal purequantum (TPQ) state [5] to calculate the specific heat. Then, we found that 10% of randomness collapse the 2K peak.
In this year, we calculate density of states,
entropy, and specific heat at low temperaturesby using the Lanczos method [6]. In particular,
we aim to understand low-temperature specificheat qualitatively via observation of the density of states. We find that DM interactions do
not significantly aﬀect the energy distribution309

of a dozen or so singlet states above the groundstate, which are involved in the peak structureof the specific heat around 2K. On the other
hand, we find that 10% randomness disperses
this distribution to collapse the 2K peak, whichis consistent with the above-mentioned TPQ
result.
In conclusion, we have clarified the similarities and diﬀerences between the eﬀects of
the DM interaction and bond randomness: theDM interaction breaks the conservation of thetotal spin and cause magnetic components tomix dense singlet states at low energies, while
the bond randomness disperses the energy distribution of singlets and triplets without breaking the conservation of the total spin, whichleads to similar eﬀects on the magnetization
process but does to diﬀerent eﬀects on the specific heat.

References[1] N. Kunisada et al., PTEP 2014, 41I01(2014).
[2] T. Kihara et al., PRB 99, 064430 (2019).
[3] Y. Fukumoto et al., J. Phys. Soc. Jpn. 87,
124710, 2018.
[4] J.
Schnacketmat/1304.2603v1.

al.,

arXiv:cond-[5] S. Sugiura and A.Shimizu, Phys. Rev.
Lett. 108, 240401(2012).
[6] H. Otsuka, Phys. Rev. B 51, 305 (1995).

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Building Algorithms for Ising Machines
Shu TANAKA
Department of Applied Physics and Physico-Informatics, Keio University
Hiyoshi, Yokohama, Kanagawa, 223-8522

We have constructed an algorithm for the
Ising machines. Ising machines are expected tobe highly eﬃcient solution machines for combinatorial optimization problems, but a signiﬁcant challenge is to develop an algorithm
that can exploit its potential and expand its
range of applications. With this background,
we have studied the following three topics.
(I) Minor-embedding algorithm forsimulated-annealing-based Ising machines
To input the Ising model, which represents
the objective function and constraints, into theactual Ising machine to solve the combinatorial
optimization problem using the Ising machine,
an operation called embedding is required.
The accuracy of the solution depends on thevalue of the hyperparameters in embedding algorithms. Therefore, appropriate hyperparameter tuning is necessary to obtain a highly accurate solution using the Ising machine. We
have proposed an appropriate method for adjusting this hyperparameter based on the viewpoint of statistical mechanics. We also veriﬁed
the properties of the proposed method by simulation. The results suggest that the proposed
method is superior to the commonly used hyperparameter adjustment method for embedding algorithms [1]. The work was done incollaboration with Tatsuhiko Shirai (Waseda
Univ.) and Nozomu Togawa (Waseda Univ.).
(II) Quantum annealing with correlateddisorder transverse ﬁelds
When solving a combinatorial optimization
problem in conventional quantum annealing, a
uniform transverse magnetic ﬁelds are applied

to all spins, and the transverse ﬁelds are gradually weakened on the same schedule. It wasrecently reported that the solution accuracy isimproved by introducing inhomogeneity in thetransverse ﬁelds. We have succeeded in obtaining rigorous inequalities for the upper andlower bounds of the dynamical critical exponents for the disordered one-dimensional transverse ﬁeld Ising model, which can be analyzed
rigorously through the free-fermion representation [2]. In addition, the dynamic criticalexponents are conﬁrmed by numerical calculations to see the ﬁnite size eﬀect. The work
was done in collaboration with Tatsuhiko Shirai (Waseda Univ.).
(III) Development of black-box optimization using Ising machines
We have previously proposed a method forblack-box optimization using Ising machinesand demonstrated it for automated metamaterial design [3]. We are currently working on
expanding the scope of this method and arepreparing a paper on it. The work was done incollaboration with Ryo Tamura (NIMS/Univ.
of Tokyo).

References[1] T. Shirai, S. Tanaka, and N. Togawa: IEEE
Access 8 (2020) 210490.
[2] T. Shirai and S. Tanaka: Annals of Physics,
Accepted.
[3] K. Kitai, J. Guo, S. Ju, S. Tanaka, K.
Tsuda, J. Shiomi, and R. Tamura: Physical Review Research 2 (2020) 013319.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Diversity in memory effects of flow in paste
Akio NAKAHARA
College of Science and Technology, Nihon University
7-24-1 Narashino-dai, Funabashi, Chiba 274-8501
A dense packed colloidal suspension, called

When NaCl is added to CaCO3 paste, thea paste, remembers the direction of its motion,

paste gets the ability of remembering flow

and its memory is visualized as a morphology ofdirection due to the screening effect by Cl - ions.

desiccation crack patterns. When a paste

Recently it is experimentally found that byremembers the direction of its vibrational

adding filtered starch solution into CaCO3 paste,motion, desiccation cracks propagate in thethe paste also gets the ability of remembering

direction perpendicular to the direction of theflow direction. However, if we add more filteredvibration, while, when a paste remembers its

starch solution into the paste, the paste loses theflow motion, cracks propagate along the flow

ability of remembering flow direction. To

direction, as are shown in Fig. 1 [1].

explain this phenomenon, the adsorption ofHere, CaCO3 paste remembers the direction

starch polymer onto colloidal particles should beof vibrational motion but cannot remember flow

included into the model, and numericaldirection. Note that CaCO3 particles are charged

simulations based on the model are inin water. Numerical simulations of shear motion

preparation.

of colloidal suspension using LAMMPS show
that, for the emergence of memory of flow, theattractive interaction should be dominant inshort

range interaction between colloidal

particles. In numerical simulations, colloidal
particles attract each other via Lennard-Jones
potential and receives Stokes’s drag force from

Fig. 1: Desiccation crack patterns induced bysurrounding fluid. Elongated clusters are formed

memory effect of vibration in (a) and flow in (b).

along flow direction, but when attractive
interaction is eliminated in the model, colloidal

References

particles could not form any elongated clusters[1] A. Nakahara, T. Hiraoka, R. Hayashi, Y.

along flow direction and that is why CaCO3

Matsuo, S. Kitsunezaki, Phil. Trans. R. Soc.

paste cannot remember flow direction.

A377:20170395 (2018).

311

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Magnetic structures under the non-equilibrium stateof the magnetic thin films with the dipolarinteraction
Hisato KOMATSU, Yoshihiko NONOMURA, and Masamichi NISHINONational Institute for Materials Science, Namiki, Tsukujba, Ibaraki 305-0044

Magnetic structure of spin systems is an important subject of solid-state physics and statistical mechanics, which aﬀects the various
behaviors of systems. In particular, magnetic
friction, the frictional force caused by the magnetic interaction between spins, is an example
of non-equilibrium phenomena that the magnetic structure have an important role[1, 2].
We already introduced the model of magnetic friction which shows the crossover ortransition from the Dieterich-Ruina law to the
Stokes law in our previous study [3]. Spinsof this model interact with each other by theshort-range interaction, and we have not considered whether the behavior of the frictionchanges in the case of the long-range interaction system. However, consideration on general long-range interaction systems, including
the dipolar interaction system, is diﬃcult, because they make complicated magnetic structures depending on the condition[4] and needO(N 2 ) computational complexity. Hence, weshould first consider a relatively simple example of the long-range interaction system.
In this study, we introduce a model where
the spins interact with each other by theinfinite-range interaction. This model resembles that of our previous study, except for theinteraction range. The reason why we choose
the infinite-range interaction systems is thepoints that the computational complexity of
the numerical simulation is O(N ), and the behavior at the thermodynamic limit can be investigated by mean field analysis.

312

According to the numerical and theoretical study, this model always obeys the Stokes
law when the temperature is higher than thecritical value, Tc , whereas the short-range
model shows a crossover or transition from theDieterich-Ruina law to the Stokes law evenwhen the temperature is higher than the equilibrium transition temperature. This is because the frictional force of the present model
depends directly on the long-range order anddisappears when the order becomes zero. It is
the large diﬀerence between two models. In thecase that the temperature is lower than Tc , themodel shows a crossover or transition similar
to that of the short-range model when N < ∞,whereas it shows hysteresis dependence whenN → ∞. This seemingly contradictory behavior is caused by the divergence of the relaxation
time in the large-N limit.

Result of this study is published as Ref. [5].
Systems with realistic long-range interaction
such as the dipolar interaction should be studied in future works.

The numerical calculations of this study
were mainly performed on the Numerical Materials Simulator at National Institute for Materials Science. We applied for the usage of the
ISSP Supercomputer in preparation for transfer of aﬃliation. However, we have ended without any transfer, and have not used the ISSP
Supercmputer.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

References[1] D. Kadau, A. Hucht, and D. E. Wolf:
Phys. Rev. Lett. 101 (2008) 137205.
[2] M. P. Magiera, L. Brendel, D. E. Wolf,and U. Nowak: Europhys. Lett. 87 (2009)
26002.
[3] H. Komatsu: Phys. Rev. E. 100 (2019)052130.
[4] K. De’Bell, A. B. MacIsaac, and J. P.
Whitehead: Rev. Mod. Phys 72 (2000)
225.
[5] H. Komatsu: Phys. Rev. E. 102 (2020)
062131.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Establishment of new analysis method
for extend X-ray absorption fine structurewith sparse modeling
Hiroyuki KUMAZOE
Institute of Industrial Nanomaterials, Kumamoto University
Kurokami, Chuo-ku, Kumamoto, 860-8555

Measurement of extended X-ray absorption
fine structure (EXAFS) is one of the primarymethods to obtain local structure information
around a specific element with atomic scale.
We are building a new method for the analysis
of EXAFS by the sparse modeling [1]. This
year, we focused on using new basis function
based on the multiple scattering theory.
To perform the sparse modeling on the EXAFS signals, we employed a new model of the
EXAFS formalism based on the multiple scattering theory [3]. we consider two-body terms
which are the main contribution of the EXAFS:Z ∞χ(k) =γ 2 (r, k)n(r) dr,(1)0

where, χ(k) is the EXAFS signal as a function of the photoelectron wavenumber; n(r) is
the coordination number of the distance r andγ 2 (r, k) contains the two-body scattering term
corresponding to the same geometrical configuration. We use a complex Hedin–Lundqvist
potential for inelastic loss effects in the framework of the multiple scattering theory. To obtain the local structure information, we solve
Eq. (1) with L1 regularization.
12ŵ = arg min ky − Xwk2 + λkwk1 , (2)2wwhere the regression coefficient is w. The response vector, y comes from the target data
and the predictor matrix, X incorporates other314

terms in Eq. (1). In this method, some elements of the coefficient, w is are suppressed toexactly zero with the moderate value of λ.
Let us consider the sparse regression
problem for the LASSO estimations within
Bayesian inference to choose the regression parameter, λ. In Bayesian inference, this linear
regression problem is optimized by maximizing
the posterior probability. Here, we introduce
the Bayesian free energy [2] as an information
criterion to optimize a regularization parameter and to extract the physical model appropriately. As a result, we estimated the radial
distribution function with fewer bases than inprevious studies [1].
This work was supported by JST CREST
Grant Number JPMJCR 1861, Japan.

References[1] I. Akai, K. Iwamitsu, Y. Igarashi,
M. Okada, H. Setoyama, T. Okajima, and
Y. Hirai, J. Phys. Soc. Jpn. 87, 074003(2018).
[2] Y. Igarashi, H. Takenaka, Y. NakanishiOhno, M. Uemura, S. Ikeda, andM. Okada, J. Phys. Soc. Jpn. 87, 044802(2018).
[3] F. Iesari, H. Setoyama, Y. Igarashi,
M. Okada, H. Kumazoe, K. Iwamitsu,
I. Akai, Y. Seno, and T. Okajima,
arXiv:2104.01805 [physics.data-an].

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Nonequilibrium phase transition and slow dynamics
in the dense hard sphere systems
Masaharu ISOBE
Nagoya Institute of Technology
Gokiso-cho, Showa-ku, Nagoya, 466-8555

As one of the simplest models, the hard
disk/sphere systems have been investigatedin the field of both equilibrium and nonequilibrium statistical physics. In this project,
we investigated non-equilibrium phenomenain the hard disk/sphere model system withmodern algorithms, especially for Event-Chain
Monte Carlo(ECMC) [1] and Event-Driven
Molecular Dynamics(EDMD) [2], where we
propose the “Hybrid Scheme”, namely, ECMC
for equilibration and EDMD for calculation of
dynamical properties [3].
Direct Evidence of Void-Induced Structural
Relaxations in Colloidal Glass Formers:
The mystery of the microscopic origin of kinetic arrest and slow relaxation mechanismsof glass-forming materials has puzzled scientists for decades in condensed and statisticalphysics. In general, when a liquid is rapidly
cooled (compressed), its molecular arrangement remains disordered, and its motion becomes frozen, resulting in a glassy state. This
causes “slow relaxation” due to the increase inviscosity. Most of the particles are frozen anddo not move. Still, in rare cases, it is known
that “active particles” that cause large displacements are generated in a spatially heterogeneous manner and move cooperatively. The
cooperative motions of these “active particles”
are roughly classified into two types: cooperative motions as a core-like domain region andstring-like hopping chain motions, which havebeen observed in simulations at first. In thelatter type of hopping chain motion, a voidwith a size of diameter is required for the initial hopping. However, in high densities, sucha void does not exist, which is a paradox. Oneof the crucial issues is understanding whether
the essential properties of glass forming materials are fundamentally thermodynamic or dynamic in origin. One perspective that favors
a dynamic origin is called Dynamic Facilitation (DF) theory [4, 5]. However, the microscopic origin of structural (so-called α) slow
relaxation in deeply supercooled liquids at an
atomic scale has remained elusive due to thelimitation of electron microscopy experiments
and computer simulation.
Recently, we devoted to investigating theapplicability of DF theory to athermal systems, i.e., systems of hard particles where therelevant control parameter is pressure, under“super-compressed” conditions, using “Hybrid
Scheme” [6]. Besides, the optical microscopy
experiments on colloidal glass former system
play an important role because detailed motions of individual particles can be accessible.
International collaboration project with Hong
Kong, we precisely traced the movement of
individual colloidal particles for a long timein experiments As a result, (A) the colloidal
particles undergo a transition from collective“creeping” to the string-like “hopping” motion
on approaching the glass transition, and thestructural relaxation of the supercooled glass
is just caused by string-like escape hopping
motion. (B) In the supercooled glassy states,
small fragmented voids distributed over a few

315

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

particle distances, called quasi-voids, cooperatively promote the formation of large voids.
(C) The voids are transported like particles,
which drive a string-like hopping chain motion. In addition, we found (a) the cooperative
motion of the core-like domain regions of the“active particles” observed in previous studies
can be decomposed into a hopping chain motion with a higher temporal resolution, and (b)the hopping chain motion is reversed with highprobability and causes a string-repetition motion, which is proved to be the leading contribution to the kinetic arrest for slow relaxation.
These new findings provide fundamental insights into the structural relaxation of glassforming materials and may pave the way for a
full understanding of the microscopic mechanism [7].
Non-equilibrium response and slow equilibration in hard disk systems
The “equilibration” (relaxation toward equilibrium states) from initial non-equilibrium
states in the molecular simulations is one of the
crucial preliminary tasks to obtain the physical properties in “true” equilibrium. The issue such as crystallization and glass/jamming
transition have been actively studied recently.
It often requires a large-scale simulation indense molecular systems, which needs a longcomputational cost for equilibration. In general, the equilibration of particle positions indense systems is much diﬃcult due to the excluded volume eﬀect being dominant. To obtain the equilibrium states, it is a reasonablechoice to use ECMC for positional relaxation
at first, which is the central idea of a hybrid
scheme [3]. To elucidate the microscopic originof equilibration in a hard disk system, we investigate the relaxing process toward the liquidstates as a non-equilibrium response inducedby the disturbance of the homogeneous expansion. After such disturbance around the Aldertransition is induced, we performed EDMD
and estimated the relaxation time of four physical properties. As the preliminary results, we

do not expect, an anomalous slow equilibration
toward the liquid states to emerge when starting from the co-existence phase in large-scale
EDMD. To identify the physical mechanism of
anomalous slow equilibration, we found thatthe spatial inhomogeneity of the initial equilibrated phases would contribute to the relaxation time, which was confirmed by the probability distribution of local density and orientational order parameter[8]. We plan to investigate further by changing methodologies systematically.

References[1] E. P. Bernard, W. Krauth, and D. B. Wilson: Phys. Rev. E 80 (2009) 056704.
[2] M. Isobe: Int. J. Mod. Phys. C 10 (1999)
1281.
[3] M. Isobe: Mol. Sim. 42 (2016) 1317.
[4] D. Chandler and J. P. Garrahan: Annu.
Rev. Phys. Chem. 61 (2010) 191.
[5] A. S. Keys, L. O. Hedges, J. P. Garrahan,
S. C. Glotzer, and D. Chandler, Phys.
Rev. X, 1 (2011) 021013.
[6] M. Isobe, A. S. Keys, D. Chandler, and J.
P. Garrahan: Phys. Rev. Lett. 117 (2016)
145701.
[7] C.-T. Yip, M. Isobe, C.-H. Chan, S. Ren,
K.-P. Wong, Q. Huo, C.-S. Lee, Y.-H.
Tsang, Y. Han, and C.-H. Lam: Phys.
Rev. Lett. 125 (2020) 258001.
[8] D. Mugita and M. Isobe: EPJ Web Conferences, in press.

316

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Quantum liquid crystals in the finite-field KΓ modelfor α-RuCl3
Masahiko G. YAMADA and Satoshi FUJIMOTO
Department of Materials Engineering Science, Osaka University
Toyonaka, 560-8531, Japan

We study the extended Kitaev model called
the KΓ model, using a perturbative expansion. From the Kitaev limit K = 0, thethird-order perturbation in Γ leads to interacting Majorana models, which are solved by awell-controlled mean-field approximation anda cutting-edge exact diagonalization. In theexact diagonalization we use a thread parallelization up to 112 threads. By this large-scalecalculation, the exact diagnolization up to 54
sites of Majorana fermions in the symmetrichoneycomb geometry is possible, while usually
the exact diagonalization has been done in thesmall system size up to 24 or 32 sites.
From the exact diagonalization combinedwith the mean-field theory, we found the following phases [1].

high-field state with zero Chern number in αRuCl3 [3]. This observation leads to a potential control of quantum states by a domain wallmotion in quantum liquid crystals.

References[1] M. G. Yamada, and S. Fujimoto:preparation.

in[2] S. Vijay, T. H. Hsieh, and L. Fu: Phys.
Rev. X 5 (2020) 041038.
[3] O. Tanaka et al.:(2020).

1. a Kekulé Kitaev spin liquid.
2. a non-Abelian chiral spin liquid.
3. an Abelian chiral spin liquid.
4. a nematic Kitaev spin liquid.
5. a Vijay-Hsieh-Fu surface code [2].
Especially, a Kekulé Kitaev spin liquid with a
Chern number 0 and a Vijay-Hsieh-Fu surface
code are new phases discovered in this largescale calculation.
The results imply the existence of a vast region of quantum liquid crystal states (a nematic Kitaev spin liquid and a Kekulé Kitaev
spin liquid). Both phases break the threefold rotation symmetry of the system, and potentially explains the experimentally observed

317

arXiv:2007.06757

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Crowding Movement of Cells
Katsuyoshi Matsushtia
Depertment of Biological Science, Graduate School of Science, Osaka University
Machikaneyama, Toyonaka, Osaka 560-0043

Cells are indispensable constituents of theorganism’s body. Cells are distributed toproper positions to function in the various organs in the developmental processes of organisms [1]. In this distribution, cells sometimes
take a crowding state and move spontaneously.
This crowding movement is expected to finallylead to a jamming state of cells through theirsteric interactions [2, 3]. In contrast to thisexpectation, cells smoothly move, similarly to
fluid, and, further, enhances their motility as
shown in the observations of Dictyostelium discodeum, neuron, and blood cells [4]. The understanding of this crowding movement is a basic common issue in the fields of soft matterphysics and developmental biology.
Some of the eukaryote cells including Dictyostelium discodeum use the persistent memory of cell trajectory to stabilize their movements [5]. We additionally showed that the
memory induces the collective movement ofcells [6, 7]. The formation of collective movements is expected to have the same origin of
the self-propelled disks [8]. To get hints to clarify the mechanism of the crowding movement,
the comparison to the self-propelled disks is effective. The self-propelled disks have been wellconfirmed to stabilize collective movement in
the sparse condition through the inelastic multiple collisions. In this case, the memory of trajectories aligns movement directions of disks
in the collisions. In contrast, the investigation of the crowding self-propelled disks so far
has clarified the destabilization of the crowding movements and take a disordered state [9].
This result is contradictory to the crowding

movement of cells and implies that the crowding movements have an uncovered necessary
condition.
To clarify the condition of the cellular
crowding movement, we investigate the crowding movement on the basis of the cellular Potts
model [10]. At the first step of this investigation, we attempt to confirm that the crowding
model cells can stabilize their collective movements. To this end, we develop the model extension for dealing with the general polarity ofcells [11, 12] and by using this extension remodels the memory of cell trajectory [13, 14].
By using Monte Carlo simulation based on ourmodel, we successfully reproduced the collective movements even in crowding cells [15].
Further, the models show that the crowding
state rather stabilizes the collective movementof cells. More concretely, we show that thethreshold propulsion of the collective movement is reduced as the concentration of cells
increases. This result at least shows that thecrowding movement is possible for cells andclearly indicates that the model cells satisfies
the aforementioned necessary condition of thecrowding movements.
The key to clarify the condition is the originof ordering, namely the memory of trajectories.
To deeply examine effects of the memory, we
try to evaluate the relation between the memory and the stability of collective movement in
the crowding cells [15]. In a case, the crowding cells with movement show a solid to fluid
transition, and then their configurations highly
fluctuate. By using this transition, we confirm
the stability in the order of movement in the318Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

crowding model cells. We can show that evenat the transition point, the cells exhibit theordering of the movement under the high fluctuation of cell configurations. To further approach the origin of this stability [16], we consider memory time dependence of this movement order. We show that the stability depends highly on the memory time. Namely,
the long memory time is the origin of the stability of movements in the crowding cells.
Based on the comparison of this result andthat of the self-propelled disks, we attempt toshed light on the uncovered necessary condition. For the case of the self-propelled disks,
the movement has an intrinsic fluctuation. In
contrast to these disks, the model cells reduce the intrinsic fluctuation in their setting
to resemble the cells with the memory of celltrajectory. In the disks, the intrinsic fluctuation shortens the memory time of the disk
trajectory. Thus, the disks have a possibility
that the disks lose the stabilization propertyof the collective movements. This differencein the intrinsic fluctuation of movements reflects the difference in the stability in crowding
movements between the model cells and selfpropelled disks. Thus, we speculate that the
reduction of intrinsic fluctuation is the necessary condition of crowding movements.
These successes of the works are attributed
to kind cooperation with Prof. H. Kuwayama,
Prof. S. Yabunaka, Prof. K. Fujimoto, Dr.
H. Hashimura, Prof. H. Yoshino, and Prof.
M. Kikuchi. The author deeply thank them.

[5] H. Takagi, PLoS ONE 3 e2648 (2008).
[6] K. Matsushita, et al., Proc. Sympo. Traffic Flow Self-driven Parti. 24, 5 (2018a).
[7] K. Matsushita, et al., J. Phys. Soc. Jpn
88, 103801 (2019).
[8] C. A. Weber, et al., Phys. Rev. Lett. 110,
208001 (2013).
[9] T. Hanke, C. A. Weber, and E. Frey Phys.
Rev. E 88, 052309 (2013).
[10] F. Graner and J. Glazier, Phys. Rev. Lett.
69, 2013 (1992).
[11] K Matsushita, Phys. Rev. E 95, 032415(2017).
[12] K Matsushita, Phys. Rev. E 97, 042413(2018).
[13] B. Szabó, et al., Phys. Rev. E, 74, 061908(2006).
[14] A. J. Kabla J. Royal Soc. Interface 9, 3268
(2012).
[15] K. Matsushita, et al., , Proc. Sympo. Traffic Flow Self-driven Parti. 25 5 (2019).
[16] K. Matsushita, S. Yabunaka, K. Fujimoto
J. Phys. Soc. Jpn 90, 054801 (2021).

References[1] C. J. Weijer, J. Cell Sci. 122, 3215 (2009).
[2] S. Henkes, Y. Fily and M. C. Marchetti,
Phys. Rev. E 84, 040301(R) (2011).
[3] L. Berthier Phys. Rev. Lett. 112, 220602(2014)[4] P. Rørth, Ann. Rev. Cell Develop. Biol.
25, 407 (2009).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Multiple helical spin density waves ininversion-symmetric itinerant magnets
Takashi UCHIDA
Hokkaido University of Science
4-1, 7-15, Maeda, Teine-ku, Sapporo 006-8585

Since the discovery of magnetic skyrmions in
B20 transition metal compounds, multiple helical spin density waves have attracted attention because the magnetic skyrmions emerge
as 3Q multiple helical spin density waves
in these materials. Typically, the magnetic
skyrmions are realized in the DzyaloshinskiiMoriya (DM) interaction driven systems under magnetic field. Recently, frustrated systems without the DM interaction have beenfound to reveal magnetic skyrmions [1, 2]. In
order to explore theoretically the possibility ofvortex-type multiple helical spin density waves
such as magnetic skyrmions in the inversionsymmetric itinerant systems, we have applied
the molecular spin dynamics (MSD) method[3] to the triangular-lattice single-band Hubbard model.
The MSD method is based on the functional
integral method for the spin fluctuation theories and the isothermal molecular dynamics
method. The method allows us to find automatically the magnetic structure of a large system with thousands of atoms in a unit cell at
finite temperatures. Starting from the Hamiltonian expressed in terms of the locally rotated coordinates and by adopting the static
approximation to the functional integral technique, the MSD method reduces to the generalized Hartree-Fock approximation at the
ground state.
In the numerical calculations the most timeconsuming process is the magnetic force calculation at each time step, where the lo-cal electronic structures are calculated in real
space by means of the recursion method. We
have adopted the automatic parallel calculation scheme and found it to be eﬀective in saving both computing time and CPU resources.
We have performed the magnetic structure
calculations on the supercell with 20×20 triangular lattice, which is embedded in a large cluster consisting of 3 × 3 supercells, each of which
are connected by the periodic boundary condition. Under zero magnetic field and the fixedvalue of the temperature T /t = 0.0005, wehave explored the magnetic structures changing the Coulomb interaction strength U/t andthe electron number n along the antiferromagnetic (AF)-ferromagnetic (F) boundary (n =1.3 ∼ 1.4) . We have performed rather
long-step MSD calculations (more than 15000
steps ) to find the thermodynamically stablestates among the various metastable multipleQ states and have found that for U/t = 5.0 ∼8.0 the 1Q helical spin density waves are stabilized in the vicinity of the AF-F boundary.
To explore the possibility of 3Q multiple helical spin density waves, the MSD calculations
for U/t < 5.0 are now in progress.

References[1] T. Okubo, S. Chung, and H. Kawamura:Phys. Rev. Lett. 108 (2012) 017206[2] Y. Kakehashi: J. Phys. Soc. Jpn. 89 (2020)
094710.
[3] Y. Kakehashi, S. Akbar, and N. Kimura:Phys. Rev. B57 (1998) 8354.

320

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Robustness of cluster states and stabilizer states forsurface codes against random local ﬁelds

By using the ISSP supercomputer, we numerically solve a time-dependent Schrödinger
equation of a many-qubit system and theoretically describe how random local ﬁelds affect cluster states and stabilizer states for surface codes [1]. While there are already several
known sources of decoherence in gate operationand measurement processes, we here focus ona new source of decoherence due to eﬀects ofﬁeld ﬂuctuations on idling qubits which should
become increasingly more serious as quantum
computers scale up. We ﬁnd similar temporal ﬁdelity degradation for both cluster statesand stabilizer states of surface codes for up
to ten qubits. We also ﬁnd that the eﬀect of
local-ﬁeld ﬂuctuations is greatly mitigated if
the magnitude of the ﬂuctuations can be suppressed to below 10% of the energy gap ∆ forboth cluster states and stabilizer states of thesurface codes. If the magnitude of the ﬂuctuations exceeds ∆/2, the state ﬁdelities forboth states deteriorate dramatically. A simple estimate based on the average ﬁdelity up
to time t ∼ 2h̄/∆ shows that the maximum
number of qubits that can suppress the system inﬁdelity below the 1% is less than 28 forthe surface code stabilizer states and 21 for thecluster states when the initial states are groundstates (Fig.1).

We have also used the ISSP supercomputer
to calculate the sucess probability of our proposed pulse sequence in the quantum annealingmechanism [2].

Average δ/∆ at fidelity=0.99

Tetsufumi Tanamoto
Department of Information and Electronic Engineering, Teikyo University
Utsunomiya 320-8511, Japan.

0.25

0.25

(a)

0.2

(b)

0.2
Cluster

Cluster

0.15

0.15

0.1

0.1

0.05

Surface

Surface

0.05
0

0
4

6
8
10
Number of qubits N

4

6
8
10
Number of qubits N

Figure 1: Average variation δ/∆ at which theﬁdelity is 0.99 for the cluster states and thesurface-code states. The error bars are calculated from the standard deviation of δ/∆.
The extrapolation equations for the cluster
states and surface-code states in (a) are givenby δ/∆ = −0.0053N + 0.1079 and δ/∆ =−0.0033N + 0.0924, respectively. Those in (b)are given by δ/∆ = −0.0004N + 0.0567 andδ/∆ = −0.0014N + 0.0732, respectively. The
extrapolation of these data points to the horizontal axis gives a rough estimate for the maxcsand Nmax, forimum number of qubits Nmax
which the errors can be corrected.

References[1] T.
Tanamoto
ArXiv:1910.05649

and

M

Ueda:

[2] T. Tanamoto: J. Appl. Phys. 84 (2015)
31415.

321

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of integrated interface of eigensolvers
Rokko and application to quantum spin systems
Tatsuya Sakashita
Center for Quantum Information and Quantum Biology, Osaka University
1-2 Machikaneyamachō, Toyonaka, Osaka 560-0043

To establish universal exact diagonalization
package for quantum lattice models including the Heisenberg-Kitaev model, we focusedon developing integrated interfaces for eigensolvers, “Rokko”[1].
In Rokko, we implemented the integrated interfaces for the following types:• Serial solvers for dense matrices (Eigen3,
LAPACK)• MPI parallelized solvers for dense matrices (EigenExa[2], ELPA[3], Elemental[4],ScaLAPACK)• MPI parallelized solvers for sparse matrices (Anasazi in Trilinos[5], SLEPc[6]) tocover matrix representations below:– CRS (Compressed Row Storage)– Matrix-free method (the method togive matrix-vector product routines
to solvers)• Unit and integrated test programs by
GoogleTest• Install scripts of eigensolvers for various
architectures
We prepare a paper to report design policy, software structure, and usage examples ofRokko.

References[1] T. Sakashita, R. Igarashi, Y. Motoyama,
T. Okubo, and S. Todo.
Repository of Rokko.
https://github.com/
t-sakashita/rokko.git, 2012.
[2] T.
Imamura,T.
Hirota,andT. Fukaya.
EigenExa web page.
https://www.r-ccs.riken.jp/labs/
lpnctrt/projects/eigenexa/, 2021.

Rokko has the following features:[3] ELPA Consortium. ELPA (Eigenvalue
soLvers for Petaflop Applications webpage). http://elpa.rzg.mpg.de, 2013.

• Integrated interfaces for eigensolvers andmatrices, independent of individual eigensolver libraries[4] J. Poulson. Distributed-memory dense linear algebra Elemental web page. https://github.com/elemental/Elemental, 2013.

• Rokko’s interfaces are implemented byutilizing factory. It enables the user todynamically select a solver.

[5] M. A. Heroux, R. A. Bartlett, and V. E.
Howle. Trilinos Project web page. https://trilinos.github.io, 2003.

• C, Fortran, and Python bindings of Rokko[6] V. Hernandez, J. E. Roman, and V. Vidal.
SLEPc web page. http://slepc.upv.es,
2002.

• Automatically detecting libraries by using
CMake in building Rokko

322

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Comparison of rocking curves of 4 2 2 Bragg-reflected X-rays
from thin silicon crystals calculated based on the conventional
method and by solving the eigenvalue problem
Kouhei OKITSU
Institute of Engineering Innovation, School of Engineering,
The University of Tokyo, 2-11-16 Yayoi Bunkyo-ku Tokyo 113-8656

Fig. 1 Rocking curves of 4 2 2 Bragg-reflected X-rays from thin (14, 21 and 30 mm thick) silicon
crystals. (a), (b) and (c) were calculated based on the conventional method. (d), (e) and (f) wereobtained by solving the eigenvalue problem. (g), (h) and (i) were experimentally obtained [1].
The experiments were performed with the temperature carefully stabilized with the incidence ofhighly collimated and monochromatized X-rays generated from a Cu K source.

The present author has worked on the n-beam

Professor H. Hashizume kindly taught theEwald-Laue (E-L) and Takagi (T-T) X-ray

present author the existence of rocking curves

dynamical diffraction theories and numericalexperimentally obtained in 1970 [1]. He is one of

method to solve them for over twenty years [2,3].

theHowever, this report describes two-beam rocking

diffraction theory of X-rays. He also taught the

curves calculated based on the E-L theory andpresent author that the description of theexperimentally obtained over fifty years ago.

dynamical theory as the eigenvalue problem is not

323

rankingauthorities

of

the

dynamical

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

general and is not widely recognized.

dynamical diffraction theory.

The E-L theory was developed by Ewald (1917)

The conventional method to solve the X-ray two-and Laue (1931). The fundamental equation given

beam dynamical theory has two steps. At first, theby Laue is described as follows:

dispersion surfaces are calculated to give the𝐤 2𝑖 − 𝐊 2
𝐃𝑖 = ∑ 𝜒ℎ𝑖 −ℎ𝑗 [𝐃𝑗 ]⊥𝐤𝑖
𝐤 2𝑖

condition that the amplitudes of Bloch wave has(1)𝑗nonzero values. Next, for cross points (tie points)

Here, 𝐊 is the wave vector of the incident X-rays,of the dispersion surfaces and the downward

𝐤 𝑖 and 𝐤𝑗 are the wave vectors of the Bloch wave,

surface normal of the crystal, the amplitudes of𝐃𝑖 and 𝐃𝑗 are amplitude vectors of the 𝑖th and 𝑗th

Bloch wave are calculated to obtain the rocking

numbered Bloch wave, 𝜒ℎ𝑖 −ℎ𝑗 is the 𝐡𝒊 − 𝐡𝒋 order

curves.

Fourier coefficient of the electric susceptibility.

However, eq.(2) for n=2 (two-beam case) can beis the vector component ofsolved directly without calculating the dispersion[𝐃𝑗 ]⊥𝐤𝑖

𝐃𝑗perpendicular to 𝐤 𝑖 .

surfaces. The eigenvalue problem can be solved

By applying an approximation that 𝑘𝑖 + 𝐾 ≈e.g. by using the LAPACK to calculate the rocking

2𝑘𝑖 , the following equation is obtained [2,3]:
𝑛−1
1
𝐾
(𝑙)
(𝑙,𝑚) (𝑚)𝜉𝑖 𝐷𝑖 = ∑ 𝜒ℎ𝑖 −ℎ𝑗 ∑ 𝐶𝑖,𝑗 𝐷𝑗 .
2
𝑗=0
𝑚=0

curves of Bragg-reflected X-rays as found in Figs.
1 (d), (e) and (f). They are in excellent agreement(2)with those experimentally obtained [Figs. 1 (g), (h)(𝑙)is theand (i)] and calculated by the conventional way(𝑙,𝑚)is the[Figs. 1 (a), (b) and (c)].

Here, 𝜉𝑖 = 𝑘𝑖 − 𝐾 (the eigenvalue), 𝐷𝑖
scalar amplitude of Bloch wave and 𝐶𝑖,𝑗The present author is indebted to Mr. T. Sasaki(𝑙)polarization factor. The scalar amplitudes 𝐷𝑖(𝑚)

and 𝐷𝑗of Bloch wave are defined as follows:

who graduated from Tokyo Gakugei University in(0) (0)(1) (1)(3𝑎)2021 for his assistance when coding the program.

(0) (0)+ 𝐷𝑗 𝐞𝑗 .

(1) (1)(3𝑏)References

𝐃𝑖 = 𝐷𝑖 𝐞𝑖 + 𝐷𝑖 𝐞𝑖 ,𝐃𝑗 = 𝐷𝑗 𝐞𝑗

are unit vectors defined such that[1] H. Hashizume, K. Nakayama, T. Matsushita

they are perpendicular to 𝐤 𝑖 and mutually

and K. Kohra: J. Phys. Soc. Jpn. (1970) 29 806-

perpendicular to each other.

807.

(0)

𝐞𝑖

(1)

and 𝐞𝑖

Joko and Fukuhara pointed out [4], for the first[2] K. Okitsu, Y. Imai, and Y. Yoda: Recent

time, that eq. (2) can be described as an eigenvalue

Advances in Crystallography, (2012) pp. 67-86.

problem of a matrix for an n-beam dynamical

InTech Open. http://dx.doi.org/10.5772/47846.

theory. When n is 2, eq.(2) is nothing but the E-L[3] K. Okitsu: J. Jpn. Soc. Synchrotron Rad. Res.
33 (2020) 61-80 [Invited].

two-beam dynamical theory that is the most widespread X-ray dynamical theory. This fact has been

[4] T. Joko and A. Fukuhara: J. Phys.Soc. Jpn.
(1967) 22 597-604.

almost completely overlooked even by Ewald,
Laue and many other authorities of the X-ray324

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Non-uniform thermal transport properties in proteins
Takahisa YAMATO
Graduate School of Science,
Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8602
We have studied thermal transport properties(https://youtu.be/zCXmIXskBFE)

in proteins using molecular simulations [1-5].

is

under

development.

Within protein molecules, tightly packed amino

We implemented an accelerated CURP codeacid residues interact with each other throughvia GPU computing with the OpenACC library.

heat and energy exchanges. We illustrate non-

As a test calculation, this program was applied

uniform heat flow with our own model based on

to a sensory domain of an oxygen sensor protein,“local heat/energy conductivity” between each

FixL. As a result, the computation time of theresidue pair.

auto-correlation function of heat currents in

Native contacts in proteins are classified into

FixL was accelerated by 98.4%.

nonpolar, polar, and charged types. Harmonic

Human superoxide dismutase (SOD1) isspring picture applies to energy transfer (ET)known to bind metal ions for its function. To

through nonpolar and polar contacts, and ET

study the selective binding metal binding

rates vary inversely with the variance of themechanism of SOD1, QM/MM molecular

contact length: whereas diffusion picture is

dynamics simulation using Gromacs/DFTB is

relevant to ET through charged contacts and ET

under progress. We plan to analyze therates correlate inversely with the mean-square-fluctuations the metal binding sites using the

distance between charged atoms of a residue pair.

CURP program.

The CURP program permits to computeinter-residue flow or energy/heat and atomic

References

stress tensor in a protein, given atomic[1] P. Humanath, K. M. Reid, T. Yamato, D. M.

coordinates and velocity trajectories obtained

Leitner: J. Phys. Chem. B 124 (2020) 9852.

through molecular dynamics (MD). Energy flow[2] K. M. Reid, T. Yamato, D. M. Leitner: J. Phys.

data permit to picture an inter-reidue Energy

B. 124 (2020) 1148.

Exchange Network (EEN) as a graph. For[3] T. Yamato: Seibutsu Butsuri 60 (2020) 94.

interactive analysis of EEN graphs using[4] D. M. Leitner, T. Yamato: Biophys. Rev. 12

pointing devices, a new visualization tool, EEN(2020) 317.

VIEWER, with JavaScript and Python codes[5] T. Yamato: Biophys. Rev. 12 (2020) 291

325

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.5

SCCMS Projects

326

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of molecular simulation framework forstudying mesoscale liquid dynamics
Hayato SHIBA
Information Technology Center, University of Tokyo
Kashiwanoha, Kashiwa, Chiba 277-0882

I now work on a large-scale molecular simulation of the dynamics of liquids. This year
was in the phase of developing new code. The
achievements are described in two parts in thefollowing, in which simulations on the scale ofmillions of atoms (particles) are enabled.

1

Development for large-scale electrolyte simulators

Dilute electrolytes, water with a small amountof dissolved ions, are indispensable for functional properties in, for example, biological
function and batteries. For the purpose of
elucidating many-body properties produced bycorrelated ions, million-atom scale molecular
dynamics simulations may provide valuable insights by directly incorporating the cooperative eﬀects induced by electrostatics.
In this year, I have developed molecular simulation code for TIP4P/2005 water + ions,based on Framework for Developing Particle
Simulator (FDPS) [1], FDPS provides a librarythat automatically produces spatial decomposition by the recursive multi-section method
associated with tree construction for for fastcommunication between diﬀerent MPI processes, which means that the users can concentrate on implementing force ﬁelds and time development schemes. Importantly, tree method
ensures scaling with O(N log N ), bypassing thenecessity for using FFT that prevents parallel scalability. Currently, I have achieved the
speed of 12,000 steps per day for a systemwith 192,000 atoms. Further application tuning is ongoing, targeting 50,000 steps per day

on ISSP System B (Ohtaka).

2

Development simulators for longtime correlations in glasses

When a liquid is rapidly cooled down, it turns
into a glass with solidity, keeping the random
atomic conﬁgurations. About two years ago,
I have revealed power-law correlations in thelong-time behavior of the velocity autocorrelation function in such a supercooled liquidin two dimensions. In order to fully address
such a long-time correlations both in two andthree dimensions, it is necessary to calculate
time-dependent trajectories of each individual particle. This brings about diﬃculties in
MPI parallelization using the spatial decomposition, because particles are no longer boundto the memory of a speciﬁc CPU. In FY2020,
I have added some time-series analysis codefor shared memory environment to my existing distributed parallel code for a LennardJones binary mixture with Kob-Andersen parameters. The whole codes are also extended
to equip CUDA routines, enabling us to calculate the autocorrelations on shared memory
environment by accelerating the force-ﬁeld calculation on GPUs. I am currently using thisfor studying space and time correlations in 2D
and 3D glass-forming liquids with O(107 ) particles.

References[1] http://fdps.jmlab.jp327

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Creating a Wannier function database toward material design
Kazuyoshi YOSHIMI
Institute for Solid State Physics, University of Tokyo, Kashiwa 277-8581
As a numerical scheme for non-empirical

ESPRESSO (QE) [4] and Wannier90 [5]. In

analysis of electronic

states in strongly

order to create a dataset, we have modified a toolcorrelated materials, the development of a

cif2qewan [6] made by T. Koretsune group at

calculation method based on first-principles

Tohoku Univ. to output the input files for QE

calculations has been actively studied in recent

calculation from cif files containing crystal

years. In this method, the effective Hamiltonian

structures. By downloading cif files from thedescribing the low-energy degrees of freedom isMaterials Project [7] under certain conditions

derived from the band structure obtained by theand using them with this tool, we performed

first-principles calculation [1]. The derived ab-comprehensive

initio effective Hamiltonian can be analyzed

functions and created a dataset.

with high accuracy using low-energy solvers

First, we performed exhaustive calculations forsuch as numerical exact diagonalization [2] andabout 1000 substances as a trial calculation. As

multivariate variational Monte Carlo methods

a result, the calculation was successful for about[3] to reveal the electronic states of real solids

400 materials, and about 10 Wannier functions

in a non-empirical manner. On the other hand,were generated for each material. In order tothese analyses require a high level of expertiseincrease the efficiency of data generation, it wasand experience in the generation of the Wannierfound that it could be reduced to about 10% byfunction, which is required in the derivation ofcontrolling the parameter values. We also foundthe effective Hamiltonian. If this task can bethat the bottleneck area, which takes a lot of

automated, it will be possible to automaticallycomputation time in Wannier90, could be

generate model analyses for various materials,

speeded up by MPI parallelization, and we

which will greatly expand the framework ofsucceeded in achieving a 10-times speedup aftermaterial design.

making changes.

In this project, we have developed a tool for

In future research, we plan to perform high-automatic generation of Wannier functions andthroughput calculations using the tools createdmade dataset for machine learning. The Wannier

and accelerated in this project to create datasets

functions can be calculated using the first-of Wannier functions, and also to try toprinciples

automatically generate Wannier functions using

calculation

softwareQuantum

328

calculationsofWannier

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

machine learning such as deep learning. This

[2] M. Kawamura, K. Yoshimi, T. Misawa et

research was done by collaboration with T.

al., Comp. Phys. Commun. 217, 180 (2017).

Koretsune, K. Kurita, and T. Oikawa of Tohoku[3] T. Misawa, S. Morita, K. Yoshimi et al.,Univ., T. Misawa of Beijing Academy ofComp. Phys. Commn. 235, 447(2019).

Quantum Information Sciences, K. Ido of[4] P. Giannozzi, O. Andreussi, T. Brumme et al.,Institute for Solid State Physics, and TOYOTA

J. Phys.: Condens. Matter 29, 465901(2017).

MORTOR CORPORATION.

[5] http://www.wannier.org[6]https://github.com/wannier-utils-

References

dev/cif2qewan[1] K. Nakamura, Y. Yoshimoto, Y. Nomura et[7] https://materialsproject.org

al., Comp. Phys. Commun. 261, 100781(2021).

329

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Computational Investigation of Charge
Photogeneration in Organic Solar Cells by
Fragment-Based GW/BSE Method
Takatoshi Fujita
Institute for Molecular Science
Myodaiji, Okazaki, Aichi 444-8585

Accurate calculations of electronic states
are essential for computational studies of organic materials which are directed toward understanding of fundamental processes in organic electronic devices. We have recently
developed the large-scale GW method basedon the fragment molecular orbital method.
The fragmentation approximation for the total polarization function and the ∆COHSEX
approximation have been employed for eﬃcient evaluations of GW quasiparticle energies
from localized molecular orbitals. More recently, we have proposed the novel large-scale
excited-state methods based on the FMO, exicton model, and GW/BSE with Tamm-Dancoﬀ
approximation (TDA). In this method, theexcited-state Hamiltonian matrix elements at
the GW/TDA-BSE level is calculated in thebasis of fragment conﬁguration state functions
which describe intrafragment excitations or interfragment charge-transfer excitations. The
excited-state Hamiltonian is then diagonalized
to approximate the adiabatic excited states ofan entire system. We have conﬁrmed thatfor molecular clusters, the novel fragmentbased GW/TDA-BSE can reasonably reproduce the excited states obtained from conventional GW/TDA-BSE method. Our developments enables the applications of GW/TDABSE method to large molecular assemblies,
which will be useful for investigating charge
separation in condensed phase.

energy levels and charge-transfer states ofthe face-on and edge-on orientations of pentacene/C60 bilayer heterojunctions. FMOGW/BSE calculations were performed for the
local interface structures in the face-on andedge-on bilayer heterojunctions, which containapproximately 2000 atoms. Calculated energy levels and charge-transfer state absorption spectra are in reasonable agreements withthose obtained from experimental measurements. We found that the dependence ofthe energy levels on interfacial morphology is
predominantly determined by the electrostatic
contribution of polarization energy, while theeﬀects of induction contribution in the edgeon interface are similar to those in the faceon. Moreover, the delocalized charge-transfer
states contribute to the main absorption peakin the edge-on interface, while the face-on
interface features relatively localized chargetransfer states in the main absorption peak.
Our results indicate that optimizing the molecular orientation and interfacial morphologies isessential for improving the power conversion
eﬃciency of organic solar cells.

References[1] T. Fujita, Y. Noguchi, T. Hoshi, Materials, 13 (2020) 2728.

As recent applications [1], we explore the330Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo!"#$%&%'()*+,-#./)0+,/"%+1&)2#")3#.%4$5%#')6/7-+"(/+81/)
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H8*% 5-8*/% >.% .-5+4% ./*% 8"11*,% 25/% +5/*%($"# 2%("1+%69# !"# /1-&"*# ($"# /-6%1-3# 0-12%(+-3#7)./"2"7.-"5,$!"#%%3*#($"#/-6%1-3#+'#/1"0"1%76.#5-)/6+34#,+($#=%"#%&%5%35.E+-3# %(# ($"# ($+1*# 3"%1"'(# 3"+4$7-1# '+("'9#!"! #$!%&'"()$*+,+-(./0-+((P,-# "6"2"3(%1.# *+00)'+-3# /1-5"''"'G# +356)*+34#:;# 6%."1"*# -<+*"# =%!>3?!# "<$+7+(# %#/%1%66"6#%3*#51-''+34#/1-5"''"'G#%'#'$-,3#+3#Q+49#&-6(%4"# ,+3*-,# 01-2# ;9@# (-# A9BC# %3*# $+4$#

LG#5-)6*#-55)1#%3*#1"R)+1"#%3#%5(+&%(+-3#"3"14.#'/"5+0+5# 5%/%5+(.# )/# (-# ;;@# 2D$E49# F-,"&"1G#-0# S;A# 2"C# TBLU# 2"CV# %(# $+4$# =%#331

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

concentration and 273 meV (327 meV) at low

meV in the Na-rich and poor contents,

Na content by GGA+U (HSE06) method.

respectively. Therefore, the proposed cathodeCompared to olivine phosphate, the Na+ ion

can be expected to exhibit significantly fasterwould diffuse better in NaxMnO2 than in

Na-ion diffusion than that in popular cathodespolyanionic framework like LiFePO4 due to thesuch as NaVOPO4 (627 meV).[2]significantly lower activation energy.[1]2. NaxVPO4F
A new orthorhombic phase of tavorite-like
NaxVPO4F cathodes (0 ≤ x ≤ 1) applicable for
Na-ion battery was proposed using density
functional theory. We have explored the phasestability, electronic structures, electrochemical
properties, and diffusion mechanisms of Na
ions/vacancies of NaxVPO4F. No imaginary

Fig. 2: Possible elementary diffusion processes offrequency in phonon dispersion provides

an Na vacancy (vc) accompanying by a positive

evidence that the proposed material is thermallypolaron (pp) along the [010] direction instable. It is suggested that the material can be

NaVPO4F. O (red), F (blue), V (brown), P (grey),

synthesized from the reaction: NaF + VPO4 à

Na (cyan), and vc (black) are shown by balls, and

NaVPO4F because of the negative formation

polyhedral structural units of V1NNO4F2 (brown),

energy. The material NaVPO4F would undergo

V2NNO4F2 (green), AO4F2 (yellow) octahedra, andbi-phase reactions upon the Na deintercalation

NaO3F (purple) tetrahedra are shown. When vc

in the ranges of 0.125 ≤ x ≤ 0.5 and 0.5 ≤ x ≤ 1,

moves along a path from vcOA to vcOB via vcTand show high voltages of 3.80 V and the highsites, pp can jointly hop from A to C sites (parallel

theoretical capacities of 143 mAhg−1. The

process indicated by a green arrow), from A to B

polaron migration effect on the Na+ ion

sites (crossing process indicated by a blue arrow),

diffusion mechanism was precisely investigated.

or remain at a same site (single process).

Three elementary diffusion processes, including
single, crossing and parallel processes, are

Referencesindicated in Fig. 2. The parallel and crossing[1] H. D. Luong, V. A. Dinh, H. Momida, T.

processes require much higher activation

Oguchi, Phys. Chem. Chem. Phys. 22, 18219

energy for Na+ diffusion, implying a substantial(2020).

polaronactivation[2] H. D. Luong, V. A. Dinh, H. Momida, T.

barriers of Na ion diffusion gain 323 and 530

Oguchi, J. Alloys Compd. (2021) accepted.

migrationeffect.

The

332

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Ab initio study toward abundant element
nanocatalysts with less precious metals
Tetsuya TAKETSUGU
Faculty of Science, Hokkaido University
N10W8, Sapporo, Hokkaido 060-0810

DFT computations with QuantumEspresso(QE) are used to gain chemical insights andto design novel catalysts with abundant elements such as hexagonal boron-nitride (h-BN)
for reducing costs and dependences on precious
metals used in various heterogeneous catalysts.
We have shown that gold clusters supportedon h-BN/Au(111) are highly active catalysts
for hydrogen evolution reaction (HER) [1]. It
is demonstrated that the most stable gold clusters on the h-BN/Au(111) support are not necessarily the most reactive; stabilization on thesurface gold clusters with the diﬀerent geometries and orientation with respect to the support can form a large variety of energeticallyfavorable H adsorption sites considerably promoting HER activity. The charge transfer between the supported gold clusters and the hBN/Au(111) surface promotes the catalytic activity of the Aun @h-BN/Au(111) system for
HER. Therefore, h-BN/Au(111) can be considered as promising support for gold clusters
as electrocatalysis [1].
Another application of BN is for oxidative
dehydrogenation (ODH) of light alkanes suchas olefin. Olefins are key feedstocks for rangeof commercially important chemicals such as
polymers, fibers, and their derivatives, which
are important for the energy and day to day
applications. Therefore, a deeper insight into
the mechanism and ways to explore catalysts
for eﬃcient oxidative dehydrogenation reaction is needed. We have proposed that oxygen functionalized h-BN with B-O-O-B sites

at the zigzag edges is active catalyst for ODH.
This suggestion is consistent with experimentally reported concentration of B and N atoms(high B:N ratio) to explore the ODH mechanism in a series of light alkanes [2]. DFT
calculations are performed to verify our proposal. We have explored the catalytic activity of the newly proposed oxygen functionalized edges of h-BN sheets for oxidative dehydrogenation of ethylbenzene. It is demonstrated that oxygen functionalized highly defective boron-nitride can demonstrate extraordinary catalytic activity for the above reaction[2].
We have elucidated the mechanism of thenovel ”heterocyclic segregation” reaction of
one pyrazine ring with two nitrogen atoms
into two quinoline rings with one nitrogen
each. Our DFT calculations showed that the
intramolecular ring-forming and -opening of
nitrogen-heterocycles are strongly aﬀected by
the initial hydrogen-substrate interaction [3].

References[1] M. Gao, M. Nakahara, A. Lyalin, and T. Taketsugu, J. Phys. Chem. C 125, 1334-1344 (2021).
[2] R. Han, J. Diao, S. Kumar, A. Lyalin, T. Taketsugu, G. Casillas, C. Richardson, F. Liu, C. W.
Yoon, H. Liu, X. Sun, Z. Huang, J. Energy Chem.
57, 477-484 (2021).
[3] K. Sun, K. Sugawara, A. Lyalin, Y. Ishigaki,
K. Uosaki, T. Taketsugu, T. Suzuki, and S. Kawai,
Angew. Chem. Int. Ed. 60, 9427-9432 (2021).

333

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of high-performance permanent
magnets by large-scale simulation and data-driven
approach
Takashi MIYAKE
CD-FMat, AIST
Umezono, Tsukuba, Ibaraki 305-8568

We have applied the scheme to (Nd1−α−β−γPrα Laβ Ceγ )2 (Fe1−δ−ζ Coδ Niζ )14 B [1]. In thefirst step, we prepared 119 experimental samples, and measured the magnetization at 3-7
temperatures within a range from 300 K to473 K. The magnetization at zero temperature (µ0 M ) and Curie temperature (TC ) areevaluated from these data by Kuzmin’s formula. Independently, we performed systematic first-principles calculation for 2869 compositions using the KKR-CPA method. The
saturation magnetization at zero temperature

is calculated in the local spin density approximation. The intersite exchange couplings
are calculated using Liechtenstein’s method,from which the Curie temperature is evaluated in the mean-field approximation. We thenadopted the data assimilation, and obtainedµ0 M and TC at arbitrary composition. The
magnetization at arbitrary temperature is obtained using Kuzmin’s formula. Figure 2 shows
the magnetization at 0 K, 300 K and 400 K.
We see that the magnetization monotonicallydecreases with increasing Co concentration (δ)
at 0 K, whereas small amount of Co doping
enhances the magnetization at 400 K.

5
4
3

y

High-throughput first-principles calculation
is a powerful tool for developing functional materials. However, systematic errors containedin computational data often prevent us fromquantitative evaluation of physical properties.
In order to overcome this problem, we have developed a data assimilation method in which asmall number of experimental data are integrated with a large number of computational
data [1]. Figure 1 is a schematic illustrationof the method. Here, open circles denote accurate but a small number of data, whereas
open squares are a large number of data that
contain a systematic error. If we consider theformer data only, we cannot estimate the target variable accurately for large x where thedata do not exist, whereas accurate estimationis possible if we consider both the data. Basedon this framework, we have developed a practical scheme for evaluating finite-temperaturemagnetization.

true model (i)sample (i)OLS (i)assimilation (i)true model (ii)sample (ii)
OLS (ii)
assimilation (ii)

2
1
0
1
0.0

0.2

0.4

x

0.6

0.8

1.0

Figure 1: An example of the data assimilation.

334

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo(Nd 1 − α − β − γ Pr α La β Ce γ ) 2 (Fe 1 − δ − ζ Co δ Ni ζ ) 14 B,
1.0

0.5

(α, ζ): (0.00, 0.00)

γ = 0.00

1.0

0.5

δ

δ = 0.00

δ

γ

0K

1.0

β = 0.00
1.8
1.7

0.5

1.6

β

0.0
0.0

1.0

0.5

β

0.0
0.0

1.0

1.0

1.0

0.5

0.5

0.5

δ

1.0

0.5

γ

1.0

1.5
1.4
1.3
1.2
1.1

0.5

β

0.0
0.0

1.0

0.5

β

0.0
0.0

1.0

1.0

1.0

0.5

0.5

0.5

0.0
0.0

0.5

β

1.0

0.0
0.0

δ

1.0

δ

γ

0.0
0.0

400 K

0.5

δ

γ

300 K

0.0
0.0

0.5

β

1.0

0.0
0.0

0.5

1.0

0.5

1.0

γ

γ

1.0

Figure 2: Magnetization of (Nd1−β−γ Laβ
Ceγ )2 (Fe1−δ Coδ )14 B.

References[1] Yosuke Harashima, Keiichi Tamai,
Shotaro Doi, Munehisa Matsumoto,Hisazumi Akai, Naoki Kawashima,
Masaaki Ito, Noritsugu Sakuma, Akira
Kato, Tetsuya Shoji, and Takashi Miyake,Phys. Rev. Materials 5, 013806 (2021).

335

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Optimized design of magnetic materials based on the
integration between quantum beam experiment andfirst-principles calculation
Kanta Ono
Institute of Materials Structure Science, High Energy Accelerator Research Organization
Oho 1-1, Tsukuba 305-0801

We have been working on characterization and material design of rare-earth permanent magnets (REPMs) which is one of themost important materials for traction motorsof vehicles and robotics. Quantification of
REPMs has to be done on multiple lengthscales and energy scales, where our scope liesin the microscopic thermal equilibrium andoff-equilibrium magnetization reversal process
closer to the mesoscopic scales [1]. Since themain-phase ferromagnets in REPMs are typically made of multiple sublattices and eachsublattice contributes to the bulk magnetic
properties differently, it is an important problem to quantify the site-resolved contribution
from the microscopic measurements to understand which sublattice can be more improved [2]. Based on the measured data fromthe neutron diffraction experiments, the Rietveld analysis can give us such information
which so far has needed expertise of experienced practitioners. Still, unphysical solutions
can be given as a metastable solution in theoverall landscape of the cost function in thedata fitting. In order to quickly select a physically meaningful solution and eliminate human bias as much as possible, we have beendeveloping a data analysis technique combining Rietveld analysis and theoretical calculations [3, 4]. Ab initio electronic structure calculations for metallic ferromagnets can addresssite-specific magnetic moments based on the
crystal structure data yielded by the Rietveld

336

analysis. The output of the ab initio calculation can be fed back into the Rietveld analysis and such hybrid process between measured data analysis and ab initio calculations
can be iterated until the overall convergence isreached.
While the convergence in the hybrid analysis
is quite fast in the ThMn12 -type ferromagnets,
feasibility for the Nd2 Fe14 B-type ferromagnets
has been seen only recently with the new system B where the 128 cores can shorten the
ab initio part based on AkaiKKR in less thanan hour. This is in strong contrast to otherelectronic structure calculations for Nd2 Fe14 B
which can take weeks on older machines. With
the new hardware, the good ab initio calculation framework, and our new hybrid data
analysis methodology, further developments of
REPMs will be accelerated.

References[1] H. Tsukahara, K. Iwano, T. Ishikawa,
C. Mitsumata, K. Ono, NPG Asia Materials 12, 29, (2020).
[2] K. Saito, S. Doi, T. Abe, K. Ono, J. Alloys
and Compounds 721, 476 (2017).
[3] M. Matsumoto, T. Hawai, K. Ono,
Phys. Rev. Applied 13, 064028 (2020).
[4] T. Hawai, M. Matsumoto, K. Ono, in
preparation.

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Evaluation of the polymer blend miscibility by using
chain-increment method with all-atom molecular
dynamics simulation
Kazuo YAMADA and Nobuyuki MATUBAYASIDivision of Chemical Engineering, Osaka University, Toyonaka, Osaka 560-8531
PE

PVDF, 423K

PVDF, 553K

PVA

PVP

70

80

70

80

0

(kcal/mol)

Polymer blend, a mixture of polymers, may

-2
-3

∆µi

incr

have distinct structural and dynamical features-1

from the component polymers and is employed

-4
-5
30

in a wide variety of applications including

40

50

60

monomer index i-5<u>i (kcal/mol)

home appliances, biomedical devices, andautomotive products. The mutual miscibility of

-10
-15
-20

polymer species is determined by the free

30

40

50

60

energy of mixing. The mixing free energy is

Fig 1: Incremental free energy ∆𝜇!"#$% and the average interaction energy

given by the changes in the (excess) chemical〈𝑢〉! against the index 𝑖 of the incremented monomer in the tagged

potentials between the pure and mixed states ofpolymer at 𝑖 = 30, 40, 50, 60, 70, and 80. The horizontal, dashed line isthe component species, and the chemical

the averaged value of ∆𝜇!"#$% or 〈𝑢〉! .

potentials reflect sensitively the effect of intra-

calculation has been conducted at 1 bar on theand intermolecular interactions in turn. To

supercomputer system at ISSP. We compute theapproach the chemical potential of a polymer

incremental

molecule, we formulated the method of chain

averaged interaction energy of the incremented

increment and provided a scheme to computemonomer with the surroundings 〈𝑢〉! . Figure 1

the free energy of incrementing a monomer

shows that 𝜇!"#$% stays constant within a few

with all-atom models.[1] In this work, we

tenths of kcal/mol for inner monomers,

extended the method and treated the single-

demonstrating the validity of the chain-component(PE),

increment method. 〈𝑢〉! is also constant against

polyvinylidene difluoride (PVDF), poly(vinyl

the index i of the incremented monomer,

alcohol) (PVA), polyvinylpyrrolidone (PVP) inshowing that the local environment around thetheir linear forms.

monomer is independent of the monomer

Results

location along the polymer chain.

melts

of

polyethylene

freeenergy ∆𝜇!"#$% andtheReferences

The number of monomer units is fixed at 100
for all the systems. All-atom molecular[1] K. Yamada and N. Matubayasi: Macromol.

dynamics

53 (2020) 775-788.

simulation

andfree-energy

337

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of high-throughput calculation tools
and evaluation of magnetic properties in hardmagnetic materials
Tetsuya FUKUSHIMA
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

In this year, we developed (i) an automatic exhaustive calculation tool and (ii) an
atomistic spin Monte Carlo simulation tool
for permanent magnetic materials. Our automatic exhaustive calculation tool is basedon the all-electron Korringa-Kohn-Rostoker(KKR) Green’s function method (AkaiKKRcode). The KKR Green’s function method
can be combined with the coherent potential
approximation (CPA) which can treat configurational disordered systems, is quite useful for investigating the electronic structures,
magnetic properties, and transport propertiesof rare-earth transition-metal alloys. In the
CPA approach, the multiple scattering effectby disordered potentials is replaced with effective medium. Therefore, we can perform theelectronic structure calculations for disorderedmaterials without supercells and decrease thecomputation costs dramatically. Additionally,
since a Green’s function is directory obtainedin the KKR method, we can efficiently investigate finite temperature magnetism and transport properties by the linear response theory.
We applied this tool for and high entropy alloys
and rare-earth magnet Sm-Fe-N systems and,succeeded in constructing large-scale magnetic
material databases.
Atomistic spin Monte Carlo simulation wasused for investigating the temperature dependent magnetization reversal in permanent
magnets. The microscopic mechanism of thecoercivity at finite temperature is a crucial

Figure 1: Free energy landscape for a isolated
Nd2 Fe14 B particle by atomistic spin model
simulation. The size of the particle is 14 nm,
corresponding to 212,536 spins.
issue. Since the magnetization reversal is astochastic transition from a metastable state
to a stable state, we tried to capture the physical insight of the coercive force from the viewpoint of the free energy landscape. For the
calculation of the free energy landscape, wedeveloped a numerical simulation method fordescribing the magnetization reversal by nucleation, where highly efficient parallelization
scheme (around 1,000–3,000 MPI parallelization) for the replica exchange Wang-Landau
MC method and the reduction of systematic
errors by the 1/t method are implemented.
Applying the above method to the atomistic
spin model with a isolated Nd2 Fe14 B particle,
we performed the magnetization reversal anal-

338

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

long-ranged interaction in computational costO(N logN ) without any approximations. Thismethod can be combined with Monte Carlosimulation, leading to the quantitative analysis of the temperature dependent coercive
forces of permanent magnets from the free energy landscape calculations with the magnetic
dipole interactions (see Fig. 2). It is foundthat the influence of the magnetic dipole interaction (demagnetizing field) is strongly suppressed due to the surface thermal fluctuation.

References
Figure 2: Coercive energy of Nd2 Fe14 B atroom temperature as a function of the size ofthe domain. The blue (red) circles indicate thecalculation results without (with) the magnetic
dipole interactions, respectively. White circles
are the experimental results.

[1] Y. Toga, S. Miyashita, A. Sakuma, and T.
Miyake, Npj Comput Mater 6 (2020) 1.
[2] T. Hinokihara, M. Nishino, Y. Toga, and
S. Miyashita, Phys. Rev. B 97 (2018)
104427.

ysis for the effect of the thermal fluctuationand investigated the formation of the reverse
nucleus which is a origin of the coercive force(see Fig. 1). It was considered that the barrierof the magnetization reversal is determined by
the competition between the formation energyof the reverse nucleus and the Zeeman energy
by external magnetic field: however, we newly
proposed that the energy gain due to the expansion of the magnetization reversal region by
the domain wall motion is a key role. This fact
is quantitatively consistent with experimental
results, where the size of the reverse nucleus
dose not depend on external magnetic field.
In order to investigate the coercive forceof permanent magnets quantitatively, we needto consider the effect of the magnetic dipole
interactions (demagnetizing field). Althougha convolution integral method (fast Fouriertransform) is commonly used to incorporate
long-ranged interaction, it is not effective forpermanent magnet materials with low crystal
symmetry such as Nd2 Fe14 B. We have developed a modified stochastic cutoff method thatis applicable complex crystal structures with339

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Novel chloride solid electrolytes for all solid-state sodium
metal battery
Masanobu NAKAYAMA
Department of Advanced Ceramics
Nagoya Institute of Technology, Gokiso-chi, Showa-ku, Nagoya, Aichi 466-8555
Using high-throughput computing and structure

which is a derivative of original BVFF, todatabase (Materials Project [1]), we evaluatedreproduce DFT-MD derived structural features,

exhaustively migration energies of Li, Na, andsuch as RDF and ADF.

Mg ion in inorganic solids. Figure 1 presents

approach is adopted to calculate the ion

the distribution of migration energies of Li, Na,conductive performance.

and Mg ions in oxides by using BVFF-

calculated Na ionic conductivities at room

percolation approach.[2,3] The results indicate

temperature for 86 compositions.

that various factors affect the ion conducting

verify reproducibility of present computation

performance. Thus, materials informatics (MI)and apply MI approach for thus obtained dataapproaches are adopted to clarify the crucial

near future.

factor for ionic conductivity in oxides. Among

7

various6

regression

approaches,

gradient

performance.
performance

However,
is

not

the

sufficient

Migration energy /eVboosting regression shows the best prediction
regression
from

the

diagnostic plots shown in Fig.2. Our tentative

Figure 3 shows
We plan to

Li
Na
Mg

5
4
3
2

analysis suggests that Li-O bond length and Li-

1

O-Li bond angles are important, i.e. structural

0
10

15

20

25

Cell volume per oxygen atom /Å

factors are more important than compositional
factors.

After that FF-MD

30
3

One of the reasons for rather poor

Fig. 1: Migration energies for Li, Na, and Mg

regression performance may stem from low

ions (indicated by orange, blue, and green plots,

reproducibility

respectively)ofuniversal

BVFF

parameters.[2] To improve, high-throughput

exhaustive BVFF approach.

FF approaches[4] are used for 86 Na containing
materials.

In

this

technique,calculated

DFT-MD

simulations are performed just for 2 ps, andthen metaheuristically optimize FF parameters,

340

using

automated

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

References[1] A Jain, S. P. Ong, G. Hautier, W. Chen, W.D.
Richards, S. Dacek, S. Cholia, D. Gunter, D.
Skinner,G.

Ceder,

K.A.

Persson,APL

Materials, 2013, 1, 011002.
[2] S. Adams, R. P. Rao, Phys. Status Solidi
Fig. 2 diagnostic plot of the gradient boosting

Appl. Mater. Sci., 2011, 208, 1746–1753

regression derived prediction function for Li[3] M. Nakayama, M. Kimura, R. Jalem, T.

migration energies in 711 Li-ion containing

kasuga, J. Appl. Phys. 2016, 55, 01AH05

oxides.

[4] R. Kobayashi, Y. Miyaji, K. Nakano and M.
Nakayama, APL Mater., 2020, 8, 081111

Figure 3 Histogram of room temperature Na
ion conductivities for 86 samples using highthroughput FF-MD approach.

341

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.6

Software Advancement Projects
and Workshop Support342

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

PHYSBO – optimization tools for PHYSics based on
Bayesian Optimization–
Ryo TAMURAInternational Center for Materials Nanoarchitectonics,
National Institute for Materials Science,
1-1 Namiki, Tsukuba, Ibaraki, 305-0044

Bayesian optimization (BO) is machinelearning based black-box optimization technique and has recently garnered signiﬁcant attention in physics, chemistry, and materials
science[1]. For example, for materials developments, the trial-and-error process to ﬁnd better material is regarded as optimizing a blackbox function where input is the composition,
structure, and process and output will be materials property. In this algorithm, ﬁrst, aGaussian process regression that predicts the
expected property and variance is constructedfrom the already observed input-output pairs.
Next, through the trained Gaussian process,the probable input data that will yield the desired output value are also selected based on
the acquisition function using expected property and variance. Then, the true output value
for the selected candidate is obtained by experiments or simulations as black-box functions.
BO repeats these processes to ﬁnd better inputs. Although BO is powerful tool for blackbox optimization, BO is generally computationally expensive in two parts: training Gaussian process regression and optimizing acquisition function.
COMBO (COMmon Bayesian Optimization) has been developed mainly for researchers in the materials science ﬁeld[2]. In
the Gaussian process, two hyperparameters,i.e., parameters whose values were given prior
to learning, existed: the Gaussian kernel widthand noise variance. Using the COMBO pack-age, these hyperparameters were automaticallydetermined by maximizing the Type-II likelihood. In addition, to avoid computationallyexpensive for training Gaussian process regression, COMBO achieves high scalability using
Thompson sampling, random feature map, andone-rank Cholesky update,To accelerate COMBO package further,
PHYSBO (optimization tools for PHYSics
based on Bayesian Optimization) package isdeveloped as Python 3 code[3]. In PHYSBO,
the massive parallelization using ISSP supercomputer can be performed for optimizing acquisition function, and then both computationally expensive parts in BO can be resolved.
In addition, new function to perform multiobjective optimization is implemented.
In physics ﬁeld, so far, BO has been applied to some problems such as autonomous
X-ray scattering experiments [4], inverse scattering [5], crystal structure prediction [6], andeﬀective model estimation[7]. Thus, PHYSBO
package can accelerate these problems, andwill solve more complex physical problems using supercomputer.
This package is developed with Tsuyoshi
Ueno, Kei Terayama, Koji Tsuda, Yuichi
Motoyama, Kazuyoshi Yoshimi, and Naoki
Kawashima. We would like to thank the support from Project for advancement of software usability in materials science by The
Institute for Solid State Physics, The University of Tokyo, for development of PHYSBO.

343

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

References[1] K. Terayama, M. Sumita, R. Tamura, and
K. Tsuda, Black-box optimization for automated discovery, Accounts of Chemical
Research 54, 1334 (2021).
[2] T. Ueno, T. D. Rhone, Z. Hou, T. Mizoguchi, and K. Tsuda, COMBO: An efﬁcient Bayesian optimization library formaterials science, Materials Discovery, 4,
18 (2016).
[3] https://www.pasums.issp.u-tokyo.
ac.jp/physbo/[4] M. M. Noack, K. G. Yager, M. Fukuto,
G. S. Doerk, R. Li, and J. A. Sethian,
A kriging-based approach to autonomous
experimentation with applications to xray scattering, Scientiﬁc Reports 9, 1
(2019).
[5] R. Vargas-Hernández, Y. Guan, D.
Zhang, and R. Krems, Bayesian optimization for the inverse scattering problem inquantum reaction dynamics, New Journalof Physics 21, 022001 (2019).
[6] T. Yamashita, N. Sato, H. Kino, T.
Miyake, K. Tsuda, and T. Oguchi, Crystal structure prediction accelerated bybayesian optimization, Physical Review
Materials 2, 013803 (2018).
[7] R. Tamura and K. Hukushima, Bayesian
optimization for computationally extensive probability distributions, PLoS ONE
13, e0193785 (2018).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Development of MateriApps Installer
Synge TODO1,2 , Yuichi MOTOYAMA2 , Kazuyoshi YOSHIMI2 , and Takeo KATO2
1
Department of Physics, University of Tokyo, Tokyo, 113-0033
2
Institute for Solid State Physics, University of Tokyo, Kashiwa, 277-8581

Nowadays, computer numerical computation is indispensable for theoretical researches
in materials science. For the advancement ofcomputational materials science, eﬃcient algorithms for solving equations of materials science are essential. Many excellent applications
based on state-of-the-art algorithms have beencreated so far. In 2013, we launched a portal site for materials science simulations, MateriApps [1], to disseminate information about
the developed software to experimentalists andcorporate researchers. We have been disseminating information about the application.
One of the obstacles for users to start using
published applications in materials science isinstalling software. MateriApps LIVE! [2] isan environment that allows users to quickly
try out computational materials science applications on their laptops and other devices.
MateriApps LIVE! is a Virtual Hard Disk Image (OVA) of VirtualBox that includes applications, OS (Debian GNU/Linux), editors, visualization tools, and other environments needed
to get started with the tutorial. Using MateriApps LIVE!, it is possible to quickly set up
a computing environment for participants inclasses and software training sessions.
However, the environment provided by MateriApps LIVE! is not enough to proceedwith full-scale simulations. Since MateriApps
LIVE! runs as a virtual machine, its computational power is somewhat limited. To support
users interested in larger-scale simulations, we
had started the development of MateriApps Installer in 2013.
As FY2020 Project for Advancement ofSoftware Usability in Materials Science (PASUMS), we have made several signiﬁcant updates on MateriApps Installer: i) organizeddirectory structure and scripts, ii) added fulldocumentation and tutorials, iii) upgradedsupported software, iv) supported new hardware [ISSP system B (ohtaka)], v) supported
new compilers [GCC 10 and Intel oneAPI].
Version 1.0 of MateriApps Installer was released in March 2021, which includes install
scripts for ALPS, ALPSCore, DSQSS, Quantum ESPRESSO, HΦ, Kω, LAMMPS, mVMC,
OpenMX, RESPACK, and TeNeS. Also, it includes scripts for the following tools and libraries: Boost, CMake, Eigen3, FFTW, GCC,
Git, GSL, HDF5, LAPACK, libﬃ, OpenBLAS,
OpenMPI, OpenSSL, Python3, ScaLAPACK,
Tcl/Tk, and zlib.
Using MateriApps Installer, the above material science applications have been preinstalled on the ISSP supercomputers (ohtaka
and enaga). The source code of MateriApps
Installer is freely available from GitHub [4].
MateriApps Installer is distributed under
the GNU General Public License version 3(GPLv3). However, the patch ﬁles for eachsoftware are distributed under the license of
the software.
[1] https://ma.issp.u-tokyo.ac.jp/[2] https://cmsi.github.io/
MateriAppsLive/[3] https://www.pasums.issp.u-tokyo.ac.
jp/mainstaller/[4] https://github.com/wistaria/
MateriAppsInstaller/

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Advancement of the experimental data analysis for 2D
material structure
Takeo Hoshi
Department of Applied Mathematics and Physics, Tottori University,
4-101 Koyama-Minami, Tottori 680-8550, Japan.
20. April 2021 and was filled to capacity with

The open source software 2DMAT, a dataanalysis software of total-reflection high-30

energytokyo.ac.jp/event/4570).

positrondiffraction(TRHEPD)

experiment, was developed in Project for
Advancementof

Software

Usability

participants(https://ccms.issp.uSeveral

application

studies with 2DMAT are currently underway.

in

Our successor PASUMS project started inmaterials science (PASUMS) at FY2020 [1].

April 2021, so as to add several parallelized

TRHEPD is a novel experimental technique ofalgorithms and support other experimental

structure determination of two-dimensional

techniques of the structure determination ofmaterials and is being conducted intensively at

two-dimensional materials, such as surface X-

the Slow Positron Facility of High Energy

ray diffraction experiment and low energy

Accelerator Research Organization (KEK) [2].

electron diffraction experiment.

We developed a python-based data analysis
software of TRHEPD at 2018 and 2019 [3].

References

The software uses an iterative optimization[1](Nelder-Mead) algorithm and the grid-basehttps://www.pasums.issp.utokyo.ac.jp/2DMAT

search algorithm. The software was used in[2] (Review) Y. Fukaya, et al, J. Phys. D: Appl.

several application studies [4, 5] in the

Phys. 52, 013002 (2019).

collaboration[3] K. Tanaka, et al, Acta. Phys. Pol. A 137, 188

withexperimentalists,

I.

Mochizuki (KEK), A. Takayama (Waseda U)(2020);and their co-workers.

https://arxiv.org/abs/2002.12165

In the PASUMS project at FY2020, we

JJAP

Conf.

Series,inpress;[4] T. Hoshi, et al, Submitted; Preprint:

reorganized the software and added thehttps://arxiv.org/abs/2103.04875

Bayesian optimization algorithm, realized by[5] M. Hamada , et al, Poster presentation, JPS

the PHYSBO library [6],meeting, online, Mar. 2021.

and the replica-

exchange Monte-Carlo algorithm. The software[6] T. Ueno, et al, Materials Discovery 4, 18

was called 2DMAT v.1 and was published at(2016);

Feb. 2021 [1]. A hands-on seminar was held attokyo.ac.jp/physbo346

https://www.pasums.issp.u-

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Report of CCMS hands-on sessions
in the 2020 ﬁscal year
Kota IDO
Institute for Solid State Physics, University of Tokyo
Kashiwa-no-ha, Kashiwa, Chiba 277-8581

In the 2020 ﬁscal year, Center for Computational Materials Science (CCMS)[1] in theInstitute for Solid State Physics (ISSP) held
one hands-on session using the ISSP supercomputer, which is shown in Table 1. In this report, we brieﬂy summarize the hands-on session in Table 1.
TeNeS is open-source software based on thetensor network method[3, 4]. Users can solve
two-dimensional quantum lattice models using the corner transfer matrix renormalizationgroup method for a projected entangled pairstate. Since TeNeS supports MPI/OpenMP
hybrid parallelization, this software eﬃciently
works on massively parallel machines such asenaga. Development of TeNeS was supported
by “Project for advancement of software usability in materials science” (PASUMS) [5] inthe 2019 ﬁscal year. In the hands-on session,
Tsuyoshi Okubo and co-developers explained
the basics of the tensor network method andgave a tutorial of TeNeS. Materials for thishands-on session are available on the oﬃcialsite (in Japanese) [6].

Date

Software

Main lecturer

Nov. 10

TeNeS

T. Okubo

References[1] https://ccms.issp.u-tokyo.ac.jp[2] https://ccms.issp.utokyo.ac.jp/event/3844[3] https://www.pasums.issp.utokyo.ac.jp/tenes/en[4] https://ma.issp.utokyo.ac.jp/en/app/2291[5] https://www.pasums.issp.u-tokyo.ac.jp/[6] https://www.pasums.issp.utokyo.ac.jp/tenes/doc/paper

Website[2]

Table 1: List of CCMS hands-on sessions using
ISSP supercomputer in the 2020 ﬁscal year.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Supercomputer course of Computational Materials Design(CMD®) workshop
Masaaki GESHI1, Yoshitada MORIKAWA2, Tomoya ONO3
1Institute for NanoScience Design, Osaka University,

1-2 Machikaneyama, Toyonaka, Osaka 560-0043, Japan
2Department of Precision Engineering, Graduate School of Engineering,Osaka University,

2-1 Yamada-oka, Suita, Osaka 565-0871, Japan
3Department of Electrical and Electronic Engineering,

Graduate School of Engineering, Kobe University,1-1 Rokkodaicho, Nada, Kobe 657-8501, JapanThe 37th Computational Materials Design

batteries and so on. The participants performed(CMD®) workshop (CMD37) has been held

the calculations and examined the results.

from August 31st to September 4th and the 38th

In CMD38 four participants took the

CMD® workshop (CMD38) has been done fromsupercomputer

February 22nd to February 26th. Both were held

supercomputer of ISSP. They got a tutorial on

online. In this workshop we have the

RSPACE developed by T. Ono and M. Uemoto.

supercomputer course to train up human

After giving the introductory lecture of large-

resources to advance research by using system B

scale computing by M. Geshi and describing thesupercomputer of ISSP, the University of Tokyo.

calculation method of electronic states andIn CMD37 eight participants took theelectron conduction property using RSPACE,

supercomputer course and got a tutorial on

exercises published in the manual were carried

STATE-Senri developed by Y. Morikawa. Afterout. Then, electronic state calculations were

giving the introductory lecture of large-scale

carried out on a plurality of molecular systems,

computing by M. Geshi and explaining how toand the electronic density distribution was

use the supercomputer of ISSP and also how tovisualized.

use STATE-Senri, calculation models on each

optimization of graphene blisters, SiC/SiO2

research subject of the participants were built

interfaces, fullerenes, and ZnO was carried out.

and their calculations were carried out. Concrete

We would like to thank the organizers of thesubjects were molecular adsorption on solid

MateriApps workshop at the Institute for Solidsurfaces,

electrodeState Physics, the University of Tokyo, forinterfaces, adsorption and diffusion of atoms on

providing us with useful information for holding

graphene, electronic structures of oxides for ion

the workshop online.

chemical

reactionsat348

courseFinally,theandatomicusedthestructure

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

4

PUBLICATION LIST

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Example:LASTNAME, Firstname [ project class; # points (B), # points (C) ] (Page #)— Project title
1. First paper
Names of Authors, etc.
2. Second paper...

2 ISSP Joint Research Projects◦ B–E classes
AKAI, Hisazumi [ B class; 1200 (B), 150 (C) ] (141, 142)
— Magnetic properties of rare earth magnetic materials with structural disorder
1. Data assimilation method for experimental and ﬁrst-principles data: Finite-temperature magnetization of (Nd, Pr, La, Ce)2 (Fe, Co, Ni)14 B
Y. Harashima, K. Tamai, S. Doi, M. Matsumoto, H. Akai, N. Kawashima, M. Itho, N. Sakuma,
K. Kato, T. Shoji, and T. Miyake Phys. Rev. Materials 5, 013806 (2021).
DOI:10.1103/PhysRevMaterials.5.013806
2.

Spin-wave dispersion and exchange stiﬀness in Nd2 Fe14 B and RFe11 Ti (R=Y, Nd, Sm) from ﬁrstprinciples calculations
T. Fukazawa, H. Akai, Y. Harashima, and T. Miyake Phys. Rev. B 103, 024418 (2021).
DOI:0.1103/PhysRevB.103.024418

3.

Magnetic Friedel Oscillation at Fe(001) Surface: Direct Observation by Atomic-Layer-Resolved
Synchrotron Radiation 57 Fe Mössbauer Spectroscopy
T. Mitsui, S. Sakai, S. Li, T. Ueno, T. Watanuki, Y. Kobayashi, R. Masuda, M. Seto, and H. Akai
Phys. Rev. Lett. 125,236806 (2020).
DOI:10.1103/PhysRevLett.125.236806

4.

First-principles calculations of ﬁnite temperature electronic structures and transport properties
of Heusler alloy Co2 MnSi
H. Shinya, S. Kou, T. Fukushima, A. Masago, K. Sato, H. Katayama-Yoshida, and H. Akai Appl.
Phys. Lett. 117,042402 (2020).
DOI:10.1063/5.0017862

5.

Element- and orbital-selective magnetic coherent rotation at the ﬁrst-order phase transition of a
hard uniaxial ferrimagnet
Sh. Yamamoto, D. I. Gorbunov, H. Akai, H. Yasumura, Y. Kotani, T. Nakamura, T. Kato, N. V.
Mushnikov, A. V. Andreev, H. Nojiri, and J. Wosnitza Phys. Rev. B 101,174430 (2020).
DOI:10.1103/PhysRevB.101.174430

6.

Calculating Curie temperatures for rare-earth permanent magnets: Ab initio inspection of localized magnetic moments in d-electron ferromagnetism
M. Matsumoto and H. Akai Phys. Rev. B 101, 1444402 (2020).

350

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

DOI:10.1103/PhysRevB.101.144402

AKASHI, Ryosuke [ C class; 4000 (B), 750 (C) ] (93)— First principles exploration of the metastable phases of hydrides and their superconductivity— First principles exploration of the metastable phases of hydrides and their superconductivity II
1. AtomREM: Non-empirical seeker of the minimum energy escape paths on many-dimensional potential landscapes without coarse graining
Y. S. Nagornov and R. Akashi Comput. Phys. Commun. 254 (2020) 107260.
2.

Eﬀect of spin ﬂuctuations on superconductivity in V and Nb: A ﬁrst-principles study
K. Tsutsumi, Y. Hizume, M. Kawamura, R. Akashi, and S. Tsuneyuki, Phys. Rev. B 102 (2020)
214515.

AKERA, Hiroshi [ C class; 4000 (B), 650 (C) ] (95)
— Generation of spin and pseudospin polarizations in atomic-layer inplane heterostructures and stacked
structures
AOYAMA, Kazushi [ B class; 1000 (B), 200 (C) ] (280)— Spin transport near a phase transition in magnets— Transport properties of multiple-q states in frustrated magnets
1. Hedgehog-lattice spin texture in classical Heisenberg antiferromagnets on the breathing pyrochlore
lattice
K. Aoyama and H. Kawamura Phys. Rev. B 103 (2021) 014406.

ARAI, Munehito [ C class; 4400 (B), 350 (C) ] (252)— Computational rational design of novel proteins for industrial and pharmaceutical applications— Protein design toward the development of therapeutic drugs for COVID-19
ARAI, Toyoko [ C class; 1800 (B), 400 (C) ] (130)— DFT calculation of atomic displacement captured by energy dissipation channel of noncontact atomic
force microscope
ARIMA, Kenta [ B class; 600 (B), 150 (C) ] (171)— Analysis of electronic structures around the Fermi level of graphene nanoribbons with diﬀerent widths— Origin of speciﬁc dot patters on small graphene sheets observed by STM
ARUGA, Tetsuya [ B class; 200 (B), 0 (C) ] ()— Interaction among phthalocyanine molecules adsorbed on metal surfaces
ASANO, Yuta [ E class; 22500 (B), 4000 (C) ] (36)
— Molecular dynamics simulation of cavitation in complex ﬂuids
1. Molecular Dynamics Simulation of Soundwave Propagation in a Simple Fluid
Y. Asano, H. Watanabe, and H. Noguchi, J. Chem. Phys. 153, 124504 (2020).
DOI:10.1063/5.0024150
2.

Rotational Dynamics of Water at the Phospholipid Bilayer Depending on the Head Groups Studied
by Molecular Dynamics Simulations
Y. Higuchi, Y. Asano, T. Kuwahara, and M. Hishida, Langmuir 37, 5329 (2021).
DOI:10.1021/acs.langmuir.1c00417

3.

Eﬀects of polymers on the cavitating ﬂow around a cylinder: A Large-scale molecular dynamics
analysis351

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Y. Asano, H. Watanabe, and H. Noguchi, J. Chem. Phys. 155, 14905 (2021).
DOI:10.1063/5.0056988

BUI, VANPHO [ C class; 1000 (B), 100 (C) ] (152)— Study on removal mechanism in catalyst referred etching of single crystalline Si with pure water— Study on removal mechanism of single crystalline Si planarized by catalyst referred etching in pure
water
EGAMI, Yoshiyuki [ C class; 7200 (B), 1100 (C) ] (63)
— Development and application of algorithms for large-scale ﬁrst-principles electron-transport simulation— Development and application of ﬁrst-principles algorithms for for long-range electron transport simulation
1. Calculation of the Green’s function in the scattering region for ﬁrst-principles electron-transport
simulations
Y. Egami, S. Tsukamoto, and T. Ono, Phys. Rev. Res. 3, 013038 (2021).
DOI:10.1103/PhysRevResearch.3.013038

FUCHIZAKI, Kazuhiro [ C class; 1800 (B), 250 (C) ] (271)— Kinetics of phase transition and polyamorphism
1. A unique multianvil 6–6 assembly for a cubic-type multianvil apparatus
K. Fuchizaki, T. Wada, H. Naruta, A. Suzuki, and K. Irino Rev. Sci. Instrum. 92, 025117 (2021).
DOI:10.1063/5.0039306
2.

Application of nonequilibrium relaxation scheme to machine learning for detecting a phase transition
K. Fuchizaki, K. Nakamura, and D. Hiroi, J. Phys. Soc. Jpn. in press.

3.

The microscopic transition process from high-density to low-density amorphous state of SnI4
K. Fuchizaki, A. Ohmura, H. Naruta, and T. Nishioka, submitted to J. Phys.: Condens. Matter.

FUJII, Susumu [ B class; 600 (B), 0 (C) ] (303)— Systematic Investigation on Phonon Transport at Nanoscale Interfaces
FUJIMOTO, Satoshi [ D class; 6000 (B), 1000 (C) ] (236)— O(N) solution to the disordered Kitaev model using the large-scale parallel computing
1. Anderson-Kitaev spin liquid
Masahiko G. Yamada, npj Quantum Mater 5, 82 (2020).
DOI:10.1038/s41535-020-00285-3

FUJIMOTO, Yoshitaka [ C class; 1000 (B), 0 (C) ] (154)— Doping and molecular adsorption of graphene
1. Stacking and curvature-dependent behaviors of electronic transport and molecular adsorptions ofgraphene: A comparative study of bilayer graphene and carbon nanotube
Y. Fujimoto and S. Saito, Applied Surface Science Advances 1, 100028 (2020).
2.

Carbon annealed HPHT-Hexagonal boron nitride: Exploring defect levels using 2D materials
combined through van der Waals interface
M. Onodera, M. Isayama, T. Taniguchi, K. Watanabe, S. Masubuchi, R. Moriya, T. Haga, Y.
Fujimoto, S. Saito and T. Machida, Carbon 167, 785 (2020).

3.

First-Principles Materials Design for Graphene-based Sensor Devices

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Y. Fujimoto, Sustainable Materials for Next Generation Energy Devices, p.343 (Elsevier 2021).
4.

Quantum transport, electronic properties and molecular adsorption in graphene
Y. Fujimoto, Modern Physics Letters B 35, 2130001 (2021).

5.

Electronic states and modulation doping of hexagonal boron-nitride trilayer
T. Haga, Y. Matsuura, Y. Fujimoto and S. Saito, Physical Review Materials, submitted.

6.

Stability of Hydrogen Boride Sheets in Water
K. I. Rojas, N. T. Cuong, H. Nishino et al., Communications Materials, submitted.

FUJISHIRO, Hiroki [ C class; 2200 (B), 0 (C) ] (128)— Strained Band-Structure Engineering for Antimonide-Based Terahertz Transistors
FUKUDA, Jun-ichi [ B class; 800 (B), 0 (C) ] (289)— Calculation of ordered structures dynamics and optical properties of soft materials
1. Lattice orientation of cholesteric blue phases in contact with surfaces enforcing unidirectional
planar anchoring
J. Fukuda and S. Žumer, Physical Review Research 2 (2020) 033407/1-11.

FUKUDA, Masahiro [ B class; 300 (B), 100 (C) ] (182)— Analysis of local quantities of electron ﬁeld in material surface
FUKUMOTO, Yoshiyuki [ B class; 500 (B), 0 (C) ] (309)— Eﬀects of exchange randomness on magnetic properties of a spherical-kagome spin-system W72V30— Exact diagonalization calculations of density of states and dynamical structure factor for the sphericalkagome spin-system W72 V30
FUKUSHIMA, Tetsuya [ B,C class; 1700 (B), 300 (C) ] (132)— Construction of magnetic materials database by KKR Green’s function method— Highthroughput screening calculations by KKR Green’s function method
1. Hole-mediated ferromagnetism in a high-magnetic moment material, Gd-doped GaN
A. Masago, H. Shinya, T. Fukushima, K. Sato, and H. Katayama-Yoshida, J. Phys.: Condens.
Matter 32, 485803 (2020).
DOI:10.1088%2F1361-648x%2Fabac8e2.

First-principles calculations of ﬁnite temperature electronic structures and transport properties
of Heusler alloy Co2 MnSi
H. Shinya, S. Kou, T. Fukushima, A. Masago, K. Sato, H. Katayama-Yoshida, and H. Akai, Appl.
Phys. Lett. 117, 042402 (2020).
DOI:10.1063/5.0017862

GOHDA, Yoshihiro [ C class; 2800 (B), 550 (C) ] (112)— Theoretical analysis of inﬂuences of phonons on magnetism
1. First-principles determination of intergranular atomic arrangements and magnetic properties inrare-earth permanent magnets
Y. Gohda, Sci. Technol. Adv. Mater. 22, 113 (2021).
DOI:10.1080/14686996.2021.1877092
2.

Prediction of the Curie temperature considering the dependence of the phonon free energy onmagnetic states
T. Tanaka and Y. Gohda, npj Comput. Mater. 6, 184 (2020).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

DOI:10.1038/s41524-020-00458-5
3.

Eﬀective quantum-well width of conﬁned electrons in ultrathin Ag(111) ﬁlms on Si(111)7x7 substrates
K. Sugawara, I. Seo, S. Yamazaki, K. Nakatsuji, Y. Gohda, and H. Hirayama, Surf. Sci. 704,
121745 (2020).
DOI:10.1016/j.susc.2020.121745

4.

First-principles study of magnetism-dependent phonons governed by exchange ligand ﬁeld
T. Tanaka and Y. Gohda, J. Phys. Soc. Jpn. 89, 093705 (2020).
DOI:10.7566/JPSJ.89.093705

5.

First-principles Calculations on High-temperature Desorption Loss from Iridium
I. Seo, S. Yokota, Y. Imai, and Y. Gohda, Comput. Mater. Sci. 184, 109897 (2020).
DOI:10.1016/j.commatsci.2020.109897

6.

First-principles study on magnetism of a crystalline grain-boundary phase in Nd–Fe–B permanent
magnets
Y. Ainai, S. Kou, Y. Tatetsu, and Y. Gohda Jpn. J. Appl. Phys. 59, 060904 (2020).
DOI:10.35848/1347-4065/ab9402

7.

First-principles study of the adsorption of 3d transition metals on BaO- and TiO2-terminatedcubic-phase BaTiO3(001) surfaces
R. Costa-Amaral and Y. Gohda, J. Chem. Phys. 152, 204701 (2020).
DOI:10.1063/5.0008130

GOHLKE, Matthias [ C class; 1800 (B), 400 (C) ] (268)— Numerical study of spin-nematic order in the S = 1/2 J1 J2 K-Heisenberg model on the square lattice
HAGITA, Katsumi [ D class; 6500 (B), 0 (C) ] (239)— Conﬁrmation of stress-overshoot phenomena under biaxial elongational ﬂow of ring-linear mixtures
1. Eﬀect of Chain-Penetration on Ring Shape for Mixtures of Rings and Linear Polymers.
K. Hagita, T. Murashima, Polymer, 2021, 218, 123493.
2.

Multi-Ring Conﬁgurations and Penetration of Linear Chains through Rings on Bonded Rings andPoly-Catenanes in Linear Chain Matrices.
K. Hagita, T. Murashima, Polymer, 2021, 223, 123705.

3.

Multi-Interval Trajectory Recording for Eﬃcient Analyses of Time Correlations.
K. Hagita, T. Murashima J. Phys. Soc. Jpn. 89, 024002 (2020).

HAMADA, Ikutaro [ C class; 2800 (B), 0 (C) ] (122)— First-principles study of molecule/metal interfaces
1. Manipulable Metal Catalyst for Nanographene Synthesis
A. Shiotari, I. Hamada, T. Nakae, S. Mori, T. Okujima, H. Uno, H. Sakaguchi, Y. Hamamoto, Y.
Morikawa, and Y. Sugimoto Nano Lett. 11 (2020) 8339.

HAMAGUCHI, Satoshi [ C class; 6000 (B), 1150 (C) ] (68)
— Analyses of Surface Reactions in Atomic Layer Etching Processes
1. Self-limiting processes in thermal atomic layer etching of nickel by hexaﬂuoroacetylacetone
A. H. Basher, I. Hamada, and S. Hamaguchi, Jpn. J. Appl. Phys. 59, 090905 (2020).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

HAMAMOTO, Yuji [ C class; 2800 (B), 0 (C) ] (120)— van der Waals density functional study of Cu phthalocyanine adsorbed on the Au(110) surface— van der Waals density functional study of Cu phtyalocyanine adsorbed on the Au(110) surface
1. Identifying Atomic-Level Correlation Between Geometric and Electronic Structure at a MetalOrganic Interface
H. Koshida, H. Okuyama, S. Hatta, T. Aruga, Y. Hamamoto, I. Hamada, and Y. Morikawa, J.
Phys. Chem. C 124, 17696 (2020).
DOI:10.1021/acs.jpcc.0c04678

HARADA, KENJI [ C class; 1600 (B), 500 (C) ] (270)— Development of entanglement optimization method
HARASHIMA, Yosuke [ C class; 800 (B), 0 (C) ] (170)— First-principles study on complexes of impurity and dislocation in GaN p-n diodes— leakage current on power semiconductor devices and an electronic structure on a threading dislocation
1. Screw dislocation that converts p-type GaN to n-type: Microscopic study on Mg condensationand leakage current in p-n diodes
T. Nakano, Y. Harashima, K. Chokawa, K. Shiraishi, A. Oshiyama, Y. Kangawa, S. Usami, N.
Mayama, K. Toda, A. Tanaka, Y. Honda, and H. Amano, Appl. Phys. Lett. 117, 012105 (2020).
DOI:10.1063/5.0010664

HARUYAMA, Jun [ C class; 6000 (B), 1100 (C) ] (71)
— Electrochemical reaction analysis using density functional calculation + implicit solvation model 2— Electrochemical reaction analysis using density functional calculation + implicit solvation model 2-2
HASHIMOTO, Tamotsu [ C class; 800 (B), 150 (C) ] (284)— Molecular dynamics simulation of liquid BaTiO3
1. Structure of Amorphous BaTiO3 by Molecular Dynamics Simulations Using a Shell Model
T. Hashimoto and H. Moriwake, J. Phys. Soc. Jpn 90, 044604 (2021).
DOI:10.7566/JPSJ.90.044604

HATSUGAI, Yasuhiro [ C class; 3600 (B), 700 (C) ] (262)— Numerical study of bulk-edge correspondence and topological phases: From quantum to classical mechanics
1. Adiabatic heuristic principle on a torus and generalized Streda formula
Koji Kudo and Yasuhiro Hatsugai, Phys. Rev. B 102, 125108 (2020).
DOI:10.1103/PhysRevB.102.125108
2.

Chiral edge modes in game theory: a kagome network of rock-paper-scissors
Tsuneya Yoshida, Tomonari Mizoguchi, Yasuhiro Hostage, arXiv:2012.05562.

3.

Fate of fractional quantum Hall states in open quantum systems: Characterization of correlated
topological states for the full Liouvillian
Tsuneya Yoshida, Koji Kudo, Hosho Katsura, and Yasuhiro Hatsugai, Phys. Rev. Research 2,033428 (2020).
DOI:10.1103/PhysRevResearch.2.033428

4.

Mirror skin eﬀect and its electric circuit simulation
Tsuneya Yoshida, Tomonari Mizoguchi, and Yasuhiro Hatsugai, Phys. Rev. Research 2, 022062(R)(2020).
DOI:10.1103/PhysRevResearch.2.022062

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

5.

Higher-order topological phases in a spring-mass model on a breathing kagome lattice
Hiromasa Wakao, Tsuneya Yoshida, Hiromu Araki, Tomonari Mizoguchi, and Yasuhiro Hatsugai,
Phys. Rev. B 101, 094107 (2020).

6.

Detecting Bulk Topology of Quadrupolar Phase from Quench Dynamics
Tomonari Mizoguchi, Yoshihito Kuno, and Yasuhiro Hatsugai Phys. Rev. Lett. 126, 016802(2021).
DOI:10.1103/PhysRevLett.126.016802

7.

Machine Learning of Mirror Skin Eﬀects in the Presence of Disorder
Hiromu Araki, Tsuneya Yoshida, and Yasuhiro Hatsugai J. Phys. Soc. Jpn. 90, 053703 (2021).
DOI:10.7566/JPSJ.90.053703

8.

Square-root topological phase with time-reversal and particle-hole symmetry
Tsuneya Yoshida, Tomonari Mizoguchi, Yoshihito Kuno, Yasuhiro Hatsugai arXiv: 2103.11305.

9.

Bulk-edge correspondence of classical diﬀusion phenomena
Tsuneya Yoshida Yasuhiro Hatsugai Scientiﬁc Reports 11, 888 (2021)
DOI:10.1038/s41598-020-80180-w

HATTORI, Ken [ B class; 500 (B), 100 (C) ] (174)— Atomic structure and electronic states for silicide ﬁlms
HAYAMI, Satoru [ C class; 5000 (B), 900 (C) ] (202)— Search for multiple-Q magnetic orders in systems with bond-dependent anisotropic interactions— Search for square-lattice skyrmion crystal in itinerant electron systems
1. Magnetic hedgehog lattices in noncentrosymmetric metals
S. Okumura, S. Hayami, Y. Kato, and Y. Motome Phys. Rev. B 101, 144416 (2020).
DOI:10.1103/PhysRevB.101.144416
2.

Spontaneous antisymmetric spin splitting in noncollinear antiferromagnets without spin-orbit coupling
S. Hayami, Y. Yanagi, and H. Kusunose Phys. Rev. B 101, 220403(R) (2020).
DOI:10.1103/PhysRevB.101.220403

3.

Nonreciprocal magnons due to symmetric anisotropic exchange interaction in honeycomb antiferromagnets
T. Matsumoto and S. Hayami, Phys. Rev. B 101, 224419 (2020).
DOI:10.1103/PhysRevB.101.224419

4.

Multiple-Q magnetism by anisotropic bilinear-biquadratic interactions in momentum space
S. Hayami, J. Magn. Magn. Mater. 513, 167181 (2020).
DOI:10.1016/j.jmmm.2020.167181

5.

Anomalous Hall eﬀect in κ-type organic antiferromagnets
M. Naka, S. Hayami, H. Kusunose, Y. Yanagi, Y. Motome, and H. Seo Phys. Rev. B 102, 075112(2020).
DOI:10.1103/PhysRevB.102.075112

6.

Degeneracy Lifting of Neel, Bloch, and Anti-Skyrmion Crystals in Centrosymmetric Tetragonal
Systems
S. Hayami and R. Yambe, J. Phys. Soc. Jpn. 89, 103702 (2020).
DOI:10.7566/JPSJ.89.103702

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7.

Complete Multipole Basis Set for Single-Centered Electron Systems
H. Kusunose, R. Oiwa, and S. Hayami J. Phys. Soc. Jpn. 89, 104704 (2020).
DOI:10.7566/JPSJ.89.104704

8.

Bottom-up design of spin-split and reshaped electronic band structures in spin-orbit-coupling free
antiferromagnets: Procedure on the basis of augmented multipoles
S. Hayami, Y. Yanagi, and H. Kusunose Phys. Rev. B 102, 144441 (2020).
DOI:10.1103/PhysRevB.102.144441

9.

Imaging the coupling between itinerant electrons and localised moments in the centrosymmetricskyrmion magnet GdRu2Si2
Y. Yasui, C. J. Butler, N. D. Khanh, S. Hayami, T. Nomoto, T. Hanaguri, Y. Motome, R. Arita,
T.-h. Arima, Y. Tokura, and S. Seki Nat. Commun. 11, 5925 (2020).
DOI:10.1038/s41467-020-19751-4

10. NQR and NMR spectra in odd-parity multipole material CeCoSi
M. Yatsushiro and S. Hayami Phys. Rev. B 102, 195147 (2020).
DOI:10.1103/PhysRevB.102.195147
11. Square skyrmion crystal in centrosymmetric itinerant magnets
S. Hayami and Y. Motome, Phys. Rev. B 103, 0244439 (2021).
DOI:10.1103/PhysRevB.103.024439
12. Noncoplanar multiple-Q spin textures by itinerant frustration: Eﬀects of single-ion anisotropy andbond-dependent anisotropy
S. Hayami and Y. Motome, Phys. Rev. B 103, 054422 (2021).
DOI:10.1103/PhysRevB.103.054422
13. Modeling a nanometric skyrmion lattice using anisotropic exchange interactions in a centrosymmetric host
M. Hirschberger, S. Hayami, and Y. Tokura New J. Phys. 23, 023039 (2021).
DOI:10.1088/1367-2630/abdef9
14. Spin-texture-driven electrical transport in multi-Q antiferromagnets
S. Seo, S. Hayami, Y. Su, S. M. Thomas, F. Ronning, E. D. Bauer, J. D. Thompson, S.-Z. Lin
and P. F. S. Rosa Commun. Phys. 4, 58 (2021).
DOI:10.1038/s42005-021-00558-8

HIDA, Kazuo [ B class; 500 (B), 150 (C) ] (300)— Numerical Study of One Dimensional Frustrated Quantum Spin Systems
1. Inﬁnite Series of Ferrimagnetic Phases Emergent from the Gapless Spin Liquid Phase of Mixed
Diamond Chains
K. Hida, arXiv:2102.02116, J. Phys. Soc. Jpn. in press.

HIGUCHI, Yuji [ C class; 5400 (B), 850 (C) ] (242)— Large deformation process of amphiphilic molecular aggregate— Self-assemble process of amphiphilic molecules by coarse-grained molecular dynamics simulation
1. Coarse-grained molecular dynamics simulations of void generation and growth processes in thefracture of the lamellar structure of polyethylene
Y. Higuchi, Phys. Rev. E 103, 042502 (2021).
DOI:10.1103/PhysRevE.103.042502

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

2.

Rotational Dynamics of Water at the Phospholipid Bilayer Depending on the Head Groups Studied
by Molecular Dynamics Simulations
Y. Higuchi, Y. Asano, T. Kuwahara, and M. Hishida, Langmuir 37, 5329 (2021).
DOI:10.1021/acs.langmuir.1c00417

3.

高分子材料の破壊に関する粗視化シミュレーション
樋口祐次, 分子シミュレーション学会誌「アンサンブル」 22, 216-221 (2020).

HINUMA, Yoyo [ B class; 800 (B), 0 (C) ] (168, 169)
— Calculation of multication oxide surface properties for catalyst informatics— Search of accessible surfaces for catalyst informatics
1. Changes in Surface Oxygen Vacancy Formation Energy at Metal/Oxide Perimeter Sites: A Systematic Study on Metal Nanoparticles Deposited on an In2O3(111) Support
Yoyo Hinuma, Takashi Toyao, Nobutsugu Hamamoto, Motoshi Takao, Ken-ichi Shimizu, andTakashi Kamachi, J. Phys. Chem. C 2020, 124, 27621
a
2. Surface Oxygen Vacancy Formation Energy Calculations in 34 Orientations of beta-Ga2O3 andtheta-Al2O3
Yoyo Hinuma, Takashi Kamachi, Nobutsugu Hamamoto, Motoshi Takao, Takashi Toyao, and
Ken-ichi Shimizu, J. Phys. Chem. C 2020, 124, 10509
a
HIRATSUKA, Masaki [ B class; 400 (B), 100 (C) ] ()— Estimation of Infrared and Raman spectra using ab initio calculation and machine learning
HIYAMA, Miyabi [ B class; 500 (B), 50 (C) ] (308)— Theoretical analysis for photo absorption- and emission spectra for ﬁreﬂy bioluminescence related
molecules— Theoretical study for caged compound and its conjugate acid/bases
1. Theoretical Study of the Wavelength Selection for the photocleavage of Coumarin-caged Dluciferin
J. Usukura, M. Hiyama, M. Kurata, Y. Hazama, X-P. Qiu, F. M. Winnik, H. Akiyama, and N.
Koga, Photochem. Photobiol. (2020) 96, 805-814
2.

Quantum-Mechanical Hydration Plays Critical Role in the Stability of Fireﬂy Oxyluciferin Isomers: State-of-the-art Calculations of the Excited States
Y. Noguchi, M. Hiyama, M. Shiga, H. Akiyama, O. Sugino, J. Chem. Phys. (2020) 153, 201103

HORI, Yuta [ B,C class; 3700 (B), 0 (C) ] (98)— The analysis of the hydrogen-bonding structures in proton-conduction organic crystals— The analysis of the local structures and molecular dynamics in proton-conduction acid-base composites
HOSHI, Takeo [ C class; 4600 (B), 850 (C) ] (82, 346)
— Fusion of computational material science and data-driven science with massively parallel computation— Fusion of computational material science and data-driven science with parallel computation
1. Development of data-analysis software for total-reﬂection high-energy positron diﬀraction (TRHEPD)
K. Tanaka, T. Hoshi, I. Mochizuki, T. Hanada, A. Ichimiya, T. Hyodo, Acta. Phys. Pol. A
137, 188-192 (2020).
2.

Two-stage data-analysis method for total-reﬂection high-energy positron diﬀraction (TRHEPD)
K. Tanaka, I. Mochizuki, T. Hanada, A. Ichimiya, T. Hyodo, T. Hoshi, JJAP Conf. Series, inpress; Preprint: https://arxiv.org/abs/2002.12165

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3.

Revisiting the Charge-Transfer States at Pentacene/C60 Interfaces with the GW/Bethe–Salpeter
Equation Approach
Takatoshi Fujita, Yoshifumi Noguchi, Takeo Hoshi, Materials 13, 2728/1-15 (2020).

4.

An a posteriori veriﬁcation method for generalized Hermitian eigenvalue problems in large-scale
electronic state calculations
Takeo Hoshi, Takeshi Ogita, Katsuhisa Ozaki, Takeshi Terao J. Comp. Appl. Math. 376,
112830/1-13 (2020).

5.

Recent progress in large-scale electronic state calculations and data-driven sciences
Takeo Hoshi and Satoshi Ito Chap. 14 of Handbook of Silicon Based MEMS Materials andTechnologies 3rd Ed., Elsevier (2020).

6.

Data-driven sensitivity analysis in a total-reﬂection√√high-energy positron diﬀraction (TRHEPD)
experiment of the Si4O5N3 / 6H-SiC (0001)-( 3 × 3) R30◦
Takeo Hoshi, Daishiro Sakata, Shotaro Oie, Izumi Mochizuki, Satoru Tanaka, Toshio Hyodo, Koji
Hukushima: Submitted; Preprint:https://arxiv.org/abs/2103.04875

HOTTA, Chisa [ C class; 800 (B), 800 (C) ] (210)— Exploring chage glass phase in two-dimensional lattice models
HOTTA, Takashi [ C class; 2400 (B), 0 (C) ] (207)— Research of Quantum Critical Points Emerging between Two-Channel Kondo and Fermi-Liquid States
1. Two-Channel Kondo Eﬀect Emerging from Np and Pu Ions
Dai Matsui and Takashi Hotta, JPS Conf. Proc. 30, 011125 (2020).
DOI:10.7566/JPSCP.30.011125
2.

Quantum Critical Point between Two-Channel Kondo and Fermi-Liquid Phases
Takashi Hotta, J. Phys. Soc. Jpn. 89, 114706 (2020).
DOI:10.7566/JPSJ.89.114706

HU, Shiqian [ C class; 3000 (B), 400 (C) ] (109)— Study of Phonon Thermal Conduction in Two-dimensional (2D) Composite Materials— Two-Path Phonon-Interference Resonance Induces a Stop-Band in Silicon Crystal Matrix by Embedded Nanoparticles Array
HUKUSHIMA, Koji [ C class; 4600 (B), 0 (C) ] (258, 259)
— Parallel Bayesian computation in material science— Tensor renormalization-group study of spin glasses
1. Replica Exchange Particle-Gibbs Method with Ancestor Sampling
Hiroaki Inoue, Koji Hukushima and Toshiaki Omori J. Phys. Soc. Jpn. 89, (2020) 104801
2.

Lattice Glass Model in Three Spatial Dimensions
Yoshihiko Nishikawa and Koji Hukushima Phys. Rev. Lett. 125, (2020) 065501

3.

Data-driven determination of the spin Hamiltonian parameters and their uncertainties: The caseof the zigzag-chain compound KCu4P3O12
Ryo Tamura, Koji Hukushima, Akira Matsuo, Koichi Kindo, and Masashi Hase Phys. Rev. B
101, (2020) 224435

4.

Maximum Separated Distribution with High Interpretability Found Using an Exhaustive Search
Method –Application to Magnetocrystalline Anisotropy of Fe/Co Films–

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Hiori Kino, Kohji Nakamura, Koji Hukushima, Takashi Miyake, and Dam Hieu Chi J. Phys. Soc.
Jpn. 89, 064802 (2020).

IDO, Kota [ C class; 6000 (B), 900 (C) ] (201)— Numerical analyses on quantum spin liquids in strongly correlated electron systems— Spin dynamical structure factor in extended Kitaev model
IIDA, Tsutomu [ B class; 500 (B), 100 (C) ] (173)— A theoretical study on the eﬀect of impurity doping on the thermoelectric performance of environmental friendly silicide SrSi2
1. Re-evaluation of the electronic structure and thermoelectric properties of narrow-gap semiconducting α-SrSi2: A complementary experimental and ﬁrst-principles hybrid-functional approach
Daishi Shiojiri, Tsutomu Iida, Tomoyuki Kadono, Masato Yamaguchi, Takuya Kodama, Seiya
Yamaguchi, Shinta Takahashi, Yuki Kayama, Kota Hiratsuka, Motoharu Imai, Naomi Hirayama,
and Yoji Imai, J. Appl. Phys. 129(11), 115101 (2021).
DOI:10.1063/5.0041670

IKEDA, Hiroaki [ B class; 700 (B), 150 (C) ] ()— Multipole orders and superconductivity in strongly correlated electron systems
IKUHARA, Yuichi [ C class; 2800 (B), 0 (C) ] (118, 119)— Analysis of hetero-interface by ab-initio molecular dynamics simulations— Study of atomic structure and segregation behavior in oxide interface
1. Atomistic origin of high-concentration Ce3+ in {100}-faceted Cr-substituted CeO2 nanocrystals
X. Hao, A. Yoko, K. Inoue, Y. Xu, M. Saito, C. Chen, G. Seong, T. Tomai, S. Takami, A.L.
Shluger, B. Xu, T. Adschiri, and Y. Ikuhara, Acta Mater. 203, 116473 (2021).
DOI:10.1016/j.actamat.2020.11.015

IMADA, Masatoshi [ E class; 29000 (B), 4600 (C) ] (184)— Exhaustive Studies on High Temperature Superconductors by Highly Accurate ab initio Scheme forStrongly Correlated Electron Systems— Machine learning analyses on quasi-particle interference data of cuprate high-temperature superconductors
1. Single-Particle Spectral Function Formulated and Calculated by Variational Monte Carlo Methodwith Application to d-Wave Superconducting State
Maxime Charlebois and Masatoshi Imada, Phys. Rev. X 10 (2020) 041023.
2.

Charge dynamics of correlated electrons: Variational description with inclusion of composite
fermions
Kota Ido, Masatoshi Imada, Takahiro Misawa, Phys. Rev. B 101 (2020) 075124.

3.

Ab initio study of superconductivity and inhomogeneity in a Hg-based cuprate superconductor
Takahiro Ohgoe, Motoaki Hirayama, Takahiro Misawa, Kota Ido, Youhei Yamaji, Masatoshi
Imada, Phys. Rev. B 101 (2020) 045124.

INAOKA, Takeshi [ B class; 700 (B), 150 (C) ] (163)— Search and realization of novel electronic properties of solid surfaces and interfaces and of small
particles
1. Identiﬁcation of surface states formed above the substrate bands of the Ni(110)-(2x1)O surface
T. Inaoka and Y. Uehara, to be submitted.

360

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoISHIBASHI, Shoji [ C class; 800 (B), 0 (C) ] (167)— Prediction of properties of organic ferroelectrics and piezoelectrics by ﬁrst-principles calculation
1. Metaelectric multiphase transitions in a highly polarizable molecular crystal
S. Horiuchi, S. Ishibashi, R. Haruki, R. Kumai, S. Inada, and S. Aoyagi Chem. Sci. 11, 6183
(2020).
DOI:10.1039/d0sc01687j

ISHIDA, Kunio [ B class; 1100 (B), 200 (C) ] (275)— Dynamics of phonon entanglement creation between remote electron-phonon systems
1. Coherent control of nonadiabatic dynamics of electron-phonon systems by quantized light ﬁeld
Kunio Ishida Progress in Ultrafast Intense Laser Science XV, 121-132, (2020).
DOI:10.1007/978-3-030-47098-2 62.

Two-step dynamics of photoinduced phonon entanglement generation between remote electronphonon systems
Kunio Ishida and Hiroaki Matsueda arXiv: 2005.14615.

ISHIHARA, Sumio [ B class; 800 (B), 0 (C) ] ()— Inhomogeneous eﬀect in light induced nonequilibrium state— Numerical study of nonequilibrium dynamics in correlated electron systems
ISHII, Fumiyuki [ C class; 6000 (B), 1100 (C) ] ()— First-Principles Calculations of Two-Dimensional Materials and Surface Alloys— First-principles calculation of anomalous Hall coeﬃcient in metallic ferromagnet by using Berry phaseapproach
ISOBE, Masaharu [ B class; 400 (B), 0 (C) ] (315)— Nonequilibrium phase transition and slow dynamics in the dense hard sphere systems
1. Direct Evidence of Void-Induced Structural Relaxations in Colloidal Glass Formers
C.-T. Yip, M. Isobe, C.-H. Chan, S. Ren, K.-P. Wong, Q. Huo, C.-S. Lee, Y.-H. Tsang, Y. Han,
and C.-H. Lam, Phys. Rev. Lett. 125, 258001 (2020).
DOI:10.1103/PhysRevLett.125.258001
2.

Non-equilibrium response and equilibration in hard disk systems
D. Mugita and M. Isobe, EPJ Web Conferences, in press.

IWASA, Takeshi [ C class; 2800 (B), 550 (C) ] (111)— Development and applications of ﬁrst principles methods for light-matter interactions beyond thedipole approximation
1. Theoretical method for near-ﬁeld Raman spectroscopy with multipolar Hamiltonian and real-timeTDDFT: Application to on- and oﬀ-resonance tip-enhanced Raman spectroscopy
M. Takenaka, T. Taketsugu, T. Iwasa, J. Chem. Phys. 154, (2021) 024104.
DOI:10.1063/5.0034933

JESCHKE, Harald [ C class; 4400 (B), 0 (C) ] ()— Sr and Ag doped Bi2 Se3 under pressure— Theory for Superconductivity in quasi-one-dimensional Cr-based pnictides
JOUTSUKA, Tatsuya [ B class; 1300 (B), 0 (C) ] (143, 144)
— Theoretical Analysis of Photocatalytic Reaction Mechanism at Titanium Dioxide Interfaces361

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo— Ab Initio Calculation of High-Rate Deposition of Metal Film by Low-Pressure Chemical Vapor Deposition— Ab Initio Calculation of High-Rate Deposition of Metal Films by Low-Pressure Chemical Vapor Deposition
1. Low-pressure chemical vapor deposition of Cu on Ru using CuI as precursor
T. Nishikawa, K. Horiuchi, T. Joutsuka, S. Yamauchi J. Cryst. Growth 549 (2020) 125849.
2.

Constrained Density Functional Theory Molecular Dynamics Simulation of Deprotonation in
Aqueous Silicic Acid
T. Joutsuka, K. Ando, J. Phys. Chem. B 124 (2020) 8323.

3.

Facet Dependence of Photocatalytic Activity in Anatase TiO2 : Combined Experimental and DFT
Study
T. Joutsuka, H. Yoshinari, S. Yamauchi, Bull. Chem. Soc. Jpn. 94 (2021) 106.

KADOWAKI, Hiroaki [ B class; 800 (B), 50 (C) ] ()— Exact diagonalization and TPQ of quantum pyrochlore model— Exact diagonalization of quantum pyrochlore model
KAGESHIMA, Hiroyuki [ B class; 800 (B), 0 (C) ] (166)— Study on structural elementary excitations at semiconductor surfaces and interfaces
1. First-principles study of strain eﬀect on oxygen vacancy in silicon oxide
K. Yata and H. Kageshima, Jpn. J. Appl. Phys. 60 (2020) 035504/1-6.

KANEKO, Ryui [ B class; 500 (B), 50 (C) ] (306)— tensor-network study of phase transitions in large spin systems
1. Continuous phase transition between Néel and valence bond solid phases in a J-Q-like spin laddersystemT. Ogino, R. Kaneko, S. Morita, S. Furukawa, and N. Kawashima, Phys. Rev. B 103, 085117(2021)
DOI:10.1103/PhysRevB.103.085117
2.

Multiple magnetization plateaus induced by further neighbor interaction in an S = 1 two-leg
Heisenberg spin ladder
H. Kohshiro, R. Kaneko, S. Morita, and N. Kawashima, submitted to Phys. Rev. B
DOI:arXiv:2102.07473

3.

Reentrance of the disordered phase in the antiferromagnetic Ising model on a square lattice withlongitudinal and transverse magnetic ﬁelds
R. Kaneko, Y. Douda, S. Goto, and I. Danshita, submitted to J. Phys. Soc. Jpn.
DOI:arXiv:2103.12364

KARIYADO, Toshikaze [ B class; 600 (B), 50 (C) ] (299)— Study of superstructure induced novel phenomena: stacking of atomically thin materials— Superstructure based band engineering and its application
1. Giant orbital diamagnetism of three-dimensional Dirac electrons in Sr3 PbO antiperovskite
S. Suetsugu, K. Kitagawa, T. Kariyado, A. W. Rost, J. Nuss, C. Mühle, M. Ogata, and H. Takagi,
Phys. Rev. B 103, 115117 (2021).
DOI:10.1103/PhysRevB.103.115117
2.

Selective branching and converting of topological modes
T. Kariyado and R.-J. Slager, submitted to Phys. Rev. Research362

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoKASAMATSU, Shusuke [ C class; 5400 (B), 900 (C) ] (16)— Analysis of disordered materials using a combination of ﬁrst-principles calculations statistical physics
and machine learning— Thermodynamic analysis of charge-storing interfaces based on direct coupling of statistical physics
and ﬁrst-principles calculation
1. Dopant arrangements in Y-doped BaZrO3 under processing conditions and their impact on proton
conduction: a large-scale ﬁrst-principles thermodynamics study
Shusuke Kasamatsu, Osamu Sugino, Takafumi Ogawa, and Akihide Kuwabara, J. Mater. Chem.
A 8, 12674-12686 (2020).
DOI:10.1039/D0TA01741H
2.

Theoretical study on proton diﬀusivity in Y-doped BaZrO3 with realistic dopant conﬁgurations
Takeo Fujii, Kazuaki Toyoura, Tetsuya Uda, and Shusuke Kasamatsu, Phys. Chem. Chem.
Phys. 23, 5908-5918 (2021).
DOI:10.1039/D0CP06035F

3.

Monte Carlo Sampling of Conﬁguration Disorder in Crystalline Materials
Shusuke Kasamatsu, The Brain & Neural Networks 28, 12-19 (2021).
DOI:10.3902/jnns.28.12

KATO, Takeo [ B class; 900 (B), 100 (C) ] (283)— Numerical Study of Adiabatic Charge Pumping through Kondo Quantum Dots
— Theory of Adiabatic Pumping in Mesoscopic Devices
1. Transmission of waves through a pinned elastic medium
T. Yamamoto, L. I. Glazman, and M. Houzet, Phys. Rev. B 103, 224211 (2021).
DOI:10.1103/PhysRevB.103.224211

KATO, Yusuke [ C class; 5800 (B), 400 (C) ] (243)— Dynamics of Kitaev spin liquid via functional renormalization group method— Functional renormalization group approach for dynamics of Kitaev-Heisenberg model
KAWAKAMI, Norio [ C class; 9200 (B), 1350 (C) ] (191)— Magnetism topological phase formation and transport phenomena in strongly correlated systems— Study of phase formation and transport phenomena in strongly correlated quantum systems
1. Spin-caloritronic transport in hexagonal graphene nanoﬂakes
Thi. Thu Phung, Robert Peters, Andreas Honecker, Guy Trambly de Laissardiere, and Javad
Vahedi, Phys. Rev. B 102 (2020) 035160.
2.

Equivalence of the eﬀective non-hermitian Hamiltonians in the context of open quantum systems
and strongly-correlated electron systems
Yoshihiro Michishita and Robert Peters, Phys. Rev. Lett. 124 (2020) 196401.

3.

Exceptional band touching for strongly correlated systems in equilibrium
Tsuneya Yoshida, Robert Peters, Norio Kawakami, and Yasuhiro Hatsugai, Prog. Theor. Exp.
Phys. (2020) 12A109

4.

Exceptional points in the one-dimensional Hubbard model
Roman Rausch, Robert Peters and Tsuneya Yoshida, New J. Phys. 23 (2021) 013011.

5.

Edge magnetic properties of black phosphorene nanoribbons
Javad Vahedi and Robert Peters, Phys. Rev. B 103 (2021) 075108.

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

6.

Minimal model of many-body localization
F. Monteiro, T. Micklitz, Masaki Tezuka, and Alexander Altland, Phys. Rev. Research 3 (2021)
013023.

KAWAKATSU, Toshihiro [ C class; 6800 (B), 0 (C) ] (237)— Analyses on complex ﬂuids using multiscale simulation platform— Fluid-elastomer hybrid simulations using multiscale simulation platform
KAWAMURA, Hikaru [ C class; 6400 (B), 0 (C) ] (241)— Novel order in frustrated magnets
1. Monte Carlo studies of the spin-chirality decoupling in the three-dimensional Heisenberg spin glass
T. Ogawa, K. Uematsu and H. Kawamura, Phys. Rev. B 101, 014434/1-16 (2020).
DOI:10.1103/PhysRevB.101.014434
2.

Spin Current as a Probe of the Z2-Vortex Topological Transition in the Classical Heisenberg
Antiferromagnet on the Triangular Lattice
K. Aoyama and H. Kawamura, Phys. Rev. Letters 124, 047202/1-6 (2020).
DOI:10.1103/PhysRevLett.124.047202

3.

Hedgehog-lattice spin texture in classical Heisenberg antiferromagnets on the breathing pyrochlore
lattice
K. Aoyama and H. Kawamura, Phys. Rev. B 131, 014406/1-15 (2021).
DOI:10.1103/PhysRevB.103.014406

KAWAMURA, Takahiro [ C class; 600 (B), 350 (C) ] (158)— First-principles analysis of melt structure and property in Na ﬂux GaN growth
1. Activation free energies for formation and dissociation of N–N, C–C, and C–H bonds in a Na–Ga
melt
T. Kawamura, M. Imanishi, M. Yoshimura, Y. Mori, and Y. Morikawa Comp. Mater. Sci. 194,110366 (2021).
DOI:10.1016/j.commatsci.2021.110366

KAWASHIMA, Naoki [ E class; 24500 (B), 3950 (C) ] (221)— Tensor-network study of Kitaev models
1. DSQSS: Discrete Space Quantum Systems Solver,
Yuichi Motoyama, Kazuyoshi Yoshimi, Akiko Masaki-Kato, Takeo Kato, Naoki Kawashima, Computational Physics Communications 264, 107944 (2021)
DOI:10.1016/j.cpc.2021.107944
2.

Multiple magnetization plateaus induced by further neighbor interaction in an S=1 two-leg Heisenberg spin ladder
Hidehiko Kohshiro, Ryui Kaneko, Satoshi Morita, Naoki Kawashima, arXiv:2102.07473

3.

Generating Function for Tensor Network Diagrammatic Summation
Wei-Lin Tu, Huan-Kuang Wu, Norbert Schuch, Naoki Kawashima, Ji-Yao Chen, arXiv:2101.03935

4.

Continuous phase transition between Néel and valence bond solid phases in a J-Q-like spin laddersystem
Takuhiro Ogino, Ryui Kaneko, Satoshi Morita, Shunsuke Furukawa, Naoki Kawashima, Phys.
Rev. B 103, 085117 (2021)
DOI:10.1103/PhysRevB.103.085117

364

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

5.

Data Assimilation Method for Experimental and First-Principles Data: Finite-Temperature Magnetization of (Nd,Pr,La,Ce)2 (Fe,Co,Ni)14 B
Yosuke Harashima, Keiichi Tamai, Shotaro Doi, Munehisa Matsumoto, Hisazumi Akai, Naoki
Kawashima, Masaaki Ito, Noritsugu Sakuma, Akira Kato, Tetsuya Shoji, and Takashi Miyake,Physical Review Materials 5, 013806 (2021)
DOI:10.1103/PhysRevMaterials.5.013806

6.

Thermal Hall Eﬀects of Spins and Phonons in Kagome Antiferromagnet Cd-Kapellasite
Masatoshi Akazawa, Masaaki Shimozawa, Shunichiro Kittaka, Toshiro Sakakibara, Ryutaro Okuma,
Zenji Hiroi, Hyun-Yong Lee, Naoki Kawashima, Jung Hoon Han and Minoru Yamashita, PhysicalReview X 10, 041059 (2020)
DOI:10.1103/PhysRevX.10.041059

7.

Global optimization of tensor renormalization group using the corner transfer matrix
Satoshi Morita and Naoki Kawashima, Physical Review B 103, 045131 (2020)
DOI:10.1103/PhysRevB.103.045131

8.

Construction of variational matrix product states for the Heisenberg spin-1 chain
Jintae Kim, Minsoo Kim, Naoki Kawashima, Jung Hoon Han and Hyun-Yong Lee, Phys. Rev.
B 102, 085117 (2020)
DOI:10.1103/PhysRevB.102.085117

9.

Kω–Open-sourcelibraryfortheshiftedKrylovsubspacemethodoftheform(zI–H)x=b
Takeo Hoshi, Mitsuaki Kawamura, Kazuyoshi Yoshimi, Yuichi Motoyama, Takahiro Misawa,
Youhei Yamaji, Synge Todo, Naoki Kawashima, Tomohiro Sogabea Computer Physics Communications 258, 107536 (2020)
DOI:10.1016/j.cpc.2020.107536

10. Tensor network wave function of S=1 Kitaev spin liquids
Hyun-Yong Lee, Naoki Kawashima and Yong Baek Kim, Phys. Rev. Res. 2 033318 (2020)
DOI:10.1103/PhysRevResearch.2.033318
11. Boundary conformal spectrum and surface critical behavior of classical spin systems:A tensor
network renormalization study
Shumpei Iino, Satoshi Morita, and Naoki Kawashima, Phys. Rev. B 101, 155418 (2020)
DOI:10.1103/PhysRevB.101.155418
12. Magnetic ﬁeld induced quantum phases in a tensor network study of Kitaev magnets
Hyun-Yong Lee, Ryui Kaneko, Li Ern Chern, Tsuyoshi Okubo, Youhei Yamaji, Naoki Kawashima,
and Yong Baek Kim, Nature Communications 11, 1639 (2020)
DOI:10.1038/s41467-020-15320-x
13. Tensor-Ring Decomposition with Index-Splitting
Hyun-Yong Lee, and Naoki Kawashima, J. Phys. Soc. Jpn. 89, 054003 (2020)
DOI:10.7566/JPSJ.89.054003

KITA, Takafumi [ C class; 600 (B), 200 (C) ] (287)— Magnetic ﬁeld dependence of the thermal Hall eﬀect based on the augmented quasiclassical equations
1. Drastic enhancement of the thermal Hall angle in a d-wave superconductor
H. Ueki, H. Morita, M. Ohuchi, and T. Kita, Phys. Rev. B 101, 184518 (2020).
DOI:10.1103/PhysRevB.101.184518
2.

Zero-Field Surface Charge Due to the Gap Suppression in d-Wave Superconductors

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E. S. Joshua, H. Ueki, W. Kohno, and T. Kita
J. Phys. Soc. Jpn. 89, 104702 (2020).
DOI:10.7566/JPSJ.89.104702
3.

Charging in the Abrikosov lattice of type-II superconductors
M. Ohuchi, H. Ueki, and T. Kita, submitted to Phys. Rev. B

KITAO, Akio [ C class; 8000 (B), 0 (C) ] (234)— Eﬃcient sampling simulation of the soft modes signiﬁcantly contribute to protein properties
1. Regulation of caveolae through cholesterol-depletion-dependent tubulation mediated by PACSIN2.
A. Gusmira, K. Takemura, S.Y. Lee, T. Inaba, K. Hanawa-Suetsugu, K. Oono-Yakura, K. Yasuhara, A. Kitao and S. Suetsugu, J Cell Sci 133 (2020) jcs246785.
2.

Edge expansion parallel cascade selection molecular dynamics simulation for investigating largeamplitude collective motions of proteins.
D.P. Tran and A Kitao, J. Chem. Phys. 152 (2020) 225101.

3.

Kinetic selection and relaxation of the Intrinsically Disordered Region of a Protein upon Binding.
K. Takaba, D.P. Tran and A. Kitao, J. Chem. Theory Comput. 16 (2020) 2835.

4.

An Eﬃcient Timer and Sizer of Biomacromolecular Motions.
J. Chan, K. Takemura, H.R. Lin, K.C. Chang, Y.Y. Chang, Y. Joti, A. Kitao and L.W. Yang,
Structure 28 (2020) 259.

5.

High pressure inhibits signaling protein binding to the ﬂagellar motor and bacterial chemotaxis
through enhanced hydration.
H. Hata, Y. Nishihara, M. Nishiyama, Y. Sowa, I. Kawagishi, A. Kitao, Sci. Rep. 10 (2020)
2351.

6.

Molecular dynamics simulation of proteins under high pressure: Structure, function and thermodynamics.
H. Hata, M. Nishiyama, A. Kitao, Biochimica et Biophysica Acta 1864 (2020) 129395.

KOBAYASHI, Akito [ B class; 1000 (B), 150 (C) ] (211)— Hidden Order in Low Temperature Phase of Organic Dirac Electron System α-(BETS)2 I3— Hidden Ordered State in Organic Dirac Electron System α − (BET S)2 I3
1. Possible spin-density wave on Fermi arc of edge state in single-component molecular conductors[Pt(dmdt)2] and [Ni(dmdt)2]
T. Kawamura, B. Zhou, Akiko Kobayashi, Akito Kobayashi accepted to J. Phys. Soc. Jpn.
(2021/03/30)
2.

Interacting chiral electrons at the 2D Dirac points: a review
M. Hirata, A. Kobayashi, C. Berthier and K. Kanoda Rep. Prog. Phys. 84 036502 (2021)
DOI:10.1088/1361-6633/abc17c

3.

Transport properties of the organic Dirac electron system α-(BEDT-TSeF)2 I3
D. Ohki, K. Yoshimi, and A. Kobayashi Phys. Rev. B 102, 235116 (2020)
DOI:10.1103/PhysRevB.102.235116

4.

Chiral excitonic instability of two-dimensional tilted Dirac cones
D. Ohki, M. Hirata, T. Tani, Kazushi K., and A. Kobayashi Phys. Rev. Research 2, 033479(2020)
DOI:10.1103/PhysRevResearch.2.033479

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

5.

Tight-binding model and electronic property of Dirac nodal line in single-component molecular
conductor [Pt(dmdt)2 ]T. Kawamura, D. Ohki, B. Zhou, Akiko Kobayashi, Akito Kobayashi J. Phys. Soc. Jpn. 89,
074704 (2020)
DOI:10.7566/JPSJ.89.074704

6.

Eﬀect of Coulomb interactions on the Seebeck coeﬃcient of the organic Dirac electron system
α-(BEDT-TTF)2 I3
D. Ohki, Y. Omori, A. Kobayashi Phys. Rev. B 101, 245201 (2020)
DOI:10.1103/PhysRevB.101.245201

KOBAYASHI, Katsuyoshi [ B class; 700 (B), 100 (C) ] (165)— Theoretical study on electronic properties of new nanoscale surfaces and interfaces
1. Method of forming time-reversed LEED states from repeated-slab calculations
K. Kobayashi, J. Phys.: Condens. Matter 32 (2020) 495002.
DOI:10.1088/1361-648X/abb444

KOBAYASHI, Nobuhiko [ C class; 3800 (B), 600 (C) ] (96)— First-principles study of quantum transport in nanostructures
1. SAKE: ﬁrst-principles electron transport calculation code
H. Takaki, N. Kobayashi, and K. Hirose, J. Phys.: Condens. Matter 32 (2020) 325901.
2.

Charge mobility calculation of organic semiconductors without use of experimental single-crystal
data
H. Ishii, S. Obata, N. Niitsu, S. Watanabe, H. Goto, K. Hirose, N. Kobayashi, T. Okamoto, and
J. Takeya, Sci Rep 10, 2524 (2020)

KOBAYASHI, Riki [ B class; 500 (B), 0 (C) ] ()— Screening of substitutable element in van der Waals coupling rare-earth compounds— Screening of substitutable non-magnetic element in rare-earth inter-metallic compounds II
KOGA, Akihisa [ C class; 4200 (B), 600 (C) ] (251)— Numerical analysis for nonequilibrium dynamics in electronic systems on quasicrystals— Study of new ordered phase and nonequilibrium phenomena in quasicrystals
1. Majorana-mediated spin transport in Kitaev quantum spin liquids
T. Minakawa, Y. Murakami, A. Koga and J. Nasu, Phys. Rev. Lett. 125, 047204 (2020).
2.

Superlattice structure in the antiferromagnetically ordered state in the Hubbard model on the
Ammann-Beenker tiling
A. Koga, Phys. Rev. B 102, 115125 (2020).

3.

Antiferromagnetically ordered state in the half-ﬁlled Hubbard model on the Socolar dodecagonaltilingA. Koga, Mater. Trans. 62, 360-366 (2021).

4.

Majorana correlations in the Kitaev model with ordered-ﬂux structure
A. Koga, Y. Murakami, and J. Nasu, submitted to PRB.

KOMATSU, Hisato [ B class; 400 (B), 100 (C) ] (312)— Magnetic structures under the non-equilibrium state of the magnetic thin ﬁlms with the dipolar in-367

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

teraction
KOMATSU, Yu [ C class; 6200 (B), 900 (C) ] (70)— Thermodynamic properties of icy materials in the interior of planets and satelites
KOU, Sonju [ B class; 500 (B), 0 (C) ] ()— Development of Seebeck coeﬃcient calculation method in the framework of density functional theory
and linear response theory
KOURA, Akihide [ C class; 2600 (B), 400 (C) ] (115)— Ab initio molecular dynamics study on static structure of glass materials
1. Application of First-Principles-Based Artiﬁcial Neural Network Potentials to Multiscale-ShockDynamics Simulations on Solid Materials
M. Misawa, S. Fukushima, A. Koura, K. Shimamura, F. Shimojo, S. Tiwari, K. Nomura, R. K.
Kalia, A. Nakano, and P. Vashishta, J. Phys. Chem. Lett. 11, 4536 (2020).
DOI:10.1021/acs.jpclett.0c00637
2.

Molecular-Dynamics Study of Thermal Conductivity of Silver Chalcogenides
S. Fukushima, K. Shimamura, A. Koura, and F. Shimojo, Phys. Status Solidi B 257, 2000183(2020)
DOI:10.1002/pssb.202000183

3.

Computational and training requirements for interatomic potential based on artiﬁcial neural network for estimating low thermal conductivity of silver chalcogenides
K. Shimamura, Y. Takeshita, S. Fukushima, A. Koura, and F. Shimojo, J. Chem. Phys. 153,
234301 (2020)
DOI:10.1063/5.0027058

KUMAZOE, Hiroyuki [ C class; 400 (B), 50 (C) ] (314)— Establishment of new analysis method for extend X-ray absorption ﬁne structure with sparse modeling
KUNISADA, Yuji [ C class; 5600 (B), 0 (C) ] (80)
— Reduction of Rare Metals in Formic Acid Decomposition Catalysts and Oxygen Storage Materials
1. グラフェン担持 Pt サブナノクラスタの酸素還元反応活性長谷川瞬，國貞雄治，坂口紀史表面と真空 63 (2020) 413.
a DOI:10.1380/vss.63.413
2.

Single Pt Atoms on N-Doped Graphene: Atomic Structure and Local Electronic States
R. Sugimoto, Y. Segawa, A. Suzuta, Y. Kunisada, T. Uchida, K. Yamazaki, K. Gohara The
Journal of Physical Chemistry C 125 (2021) 2900.
DOI:10.1021/acs.jpcc.0c08811

KUROKI, Kazuhiko [ C class; 7200 (B), 1100 (C) ] (197)— Study on spin-ﬂuctuation-mediated superconductivity enhanced by interorbital interactions— Study on the enhanced superconductivity in cuprates with peculiar electronic structures
1. Many-variable variational Monte-Carlo study of superconductivity in two-band Hubbard models
with an incipient band
D. Kato and K. Kuroki, Phys. Rev. Research 2, 023156 (2020)
DOI:10.1103/PhysRevResearch.2.023156
2.

Superconducting mechanism for the cuprate Ba2 CuO3+δ based on a multiorbital Lieb latticemodel
K. Yamazaki, M. Ochi, D. Ogura, K. Kuroki, H. Eisaki, S. Uchida, and H. Aoki Phys. Rev.

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Research 2, 033356 (2020)
DOI:10.1103/PhysRevResearch.2.033356
3.

Designing nickelate superconductors with d8 conﬁguration exploiting mixed-anion strategy
N. Kitamine, M. Ochi, and K. Kuroki, Phys.Rev.Research 2, 042032 (2020)
DOI:10.1103/PhysRevResearch.2.042032

4.

Quantifying the stability of the anion ordering in SrVO2 H
M. Ochi and K. Kuroki, Phys.Rev.B 102, 134108 (2020)
DOI:10.1103/PhysRevB.102.134108

LIAO, YUXUAN [ C class; 4000 (B), 700 (C) ] (254, 256)
— Machine-learning-assisted Development of Giant Thermal-Property Database for Polymer Materials
1. Automated calculation system of physical properties with molecular dynamics simulation for polymer informatics
Yoshihiro Hayashi, Ruimin Ma, Yuxuan Liao, Tengfei Luo, Junichiro Shiomi, Ryo Yoshida,
Preparing for submitting.
2.

Akhiezer Mechanism Dominates Relaxation of Propagons in Amorphous at Room Temperature
Yuxuan Liao, Junichiro Shiomi, submitted to JAP

3.

Ultimate suppression of thermal transport in amorphous silicon nitride by phononic nanostructure
Naoki Tambo, Yuxuan Liao, Chun Zhou, Elizabeth Michiko Ashley, Kouhei Takahashi, Paul F
Nealey, Yasuyuki Naito, Junichiro Shiomi, Science Advances 6, eabc0075 (2020).

4.

Heat conduction below diﬀusive limit in amorphous superlattice structures
Yuxuan Liao, Sotaro Iwamoto, Michiko Sasaki, Masahiro Goto, Junichiro Shiomi, Nano Energy
84, 105903 (2021).

MAKINO, Takayuki [ B class; 1300 (B), 250 (C) ] (136)— Calculation of electronic states in strongly-electron-correlated antiferromagnetic oxides
1. Contactless measurement of electric ﬁeld with constant-DC-reﬂectivity photoreﬂectance method
E. Kobayashi et al. Solids
DOI:10.3390/solids2020008
2.

Temperature-induced localized exciton dynamics in mixed Lead-Tin based CH3NH3Pb1-xSnxI3
Perovskite materials
Md. Sherajul Islam et al. AIP Advances
DOI:10.1063/5.0007087

MASAGO, Akira [ B class; 400 (B), 0 (C) ] ()— First principles calculations of thermal dependence of conductivity and Seebeck coeﬃcient
MATSUKAWA, Hiroshi [ C class; 0 (B), 350 (C) ] ()— Physics of Friction
MATSUMOTO, Munehisa [ D,C class; 8100 (B), 1950 (C) ] (225, 226, 227)
— Optimal design of Ce-based magnetic compounds for rare-earth permanet magnets— Optimal design of magnetic materials via data integration between experiments and theory— Self-consistent analysis between ab initio data and experimental measurement results via extended
dynamical mean ﬁeld theory369

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

MATSUNAKA, Daisuke [ B class; 600 (B), 0 (C) ] (176)— First-principles Study of Defects of Magnesium Alloys
1. Defect nucleation from a pre-existing intrinsic I1 stacking fault in magnesium by molecular dynamics simulations
So Yoshikawa and Daisuke Matsunaka, Computational Materials Science, 179 (2020) 109644/1-5.

MATSUSHITA, Katsuyoshi [ C class; 0 (B), 350 (C) ] (318)— Construction of Response Theory for Motion of Crowding Cells— Many body eﬀects in the collective motion of crowding cells
1. Leader-guiding collective cell rotation
Katsuyoshi Matsushita, Sunsuke Yabunaka, Hidenori Hashimura, Hidekazu Kuwayama, Kouichi
Fujimoto, Proceedings of the Symposium on Traﬃc Flow and Self-Driven Particles 26, 38 (2020)2.

Adhesion-stabilizing long-distance transport of cells on tissue surface
K. Matsushita, Physical Review E 101, 052410 (2020)
DOI:10.1103/PhysRevE.101.052410

MATSUSHITA, Yu-ichiro [ C class; 8400 (B), 1300 (C) ] (58)
— Identiﬁcation of interface-state defects in power semiconductors: Approach from ab-initio calculations
1. Design and formation of SiC(0001)/SiO2 interfaces via Si deposition followed by low-temperatureoxidation and high-temperature nitridation
T. Kobayashi, T. Okuda, K. Tachiki, K. Ito, Y. Matsushita, and T. Kimoto, Applied Physics
Express 13, 091003 (2020).
DOI:10.35848/1882-0786/ababed
2.

Unraveling crystal symmetry and strain eﬀects on electronic band structures of SiC polytypes
Y. Kuroiwa, Y. Matsushita, and F. Oba, AIP Advances 10, 105014 (2020).
DOI:10.1063/5.0010512

3.

Implementation of quantum imaginary-time evolution method on NISQ devices: Nonlocal approximation
H. Nishi, T. Kosugi, and Y. Matsushita, npj quantum information in press.

4.

Linear-response functions of mol;ecules on a quantum computer: Charge and spin responses andoptical absorption
T. Kosugi, and Y. Matsushita, Physical Review Research 2, 033043 (2020).
DOI:10.1103/PhysRevResearch.2.033043

MINAMITANI, Emi [ C class; 3200 (B), 800 (C) ] ()— Ab-initio analysis of phonon and electron-phonon interaction
MISAWA, Masaaki [ B class; 900 (B), 0 (C) ] (161)— Molecular Dynamics Simulation on Plastic-Wave Propagation in Solid Materials Based on FirstPrinciples Calculation and Machine Learning— Molecular dynamics study on non-equilibrium processes using ﬁrst-principles calculation and machine
leaning
1. Application of First-Principles-Based Artiﬁcial Neural Network Potentials to Multiscale-ShockDynamics Simulations on Solid Materials
Masaaki Misawa, Shogo Fukushima, Akihide Koura, Kohei Shimamura, Fuyuki Shimojo, Subodh
Tiwari, Ken-ichi Nomura, Rajiv K. Kalia, Aiichiro Nakano, and Priya Vashishta, The Journal of
Physical Chemistry Letters 11, 4536 (2020).

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2.

First-Principles Study of Pressure-Induced Amorphization of Fe2SiO4 Fayalite
Masaaki Misawa and Fuyuki Shimojo, Physica Status Solidi B-Basic Solid State Physics 257
2000173 (2020).

MISAWA, Takahiro [ E class; 9000 (B), 2100 (C) ] (189)— Systematic analysis of ab initio low-energy eﬀective Hamiltonians for Pd(dmit)2 molecular conductors
1. Electronic correlation and geometrical frustration in molecular solids: A systematic ab initio studyof β ′ -X[Pd(dmit)2 ]2
T. Misawa, K. Yoshimi, and T. Tsumuraya, Phys. Rev. Research 2, 032072(R) (2020).
DOI:10.1103/PhysRevResearch.2.032072
2.

Asymmetric melting of a one-third plateau in kagome quantum antiferromagnets
T. Misawa, Y. Motoyama, and Y. Yamaji, Phys. Rev. B 102, 094419 (2020)
DOI:10.1103/PhysRevB.102.094419

3.

Kω – Open-source library for the shifted Krylov subspace method of the form (zI − H)x = b
Hoshi, Takeo and Kawamura, Mitsuaki and Yoshimi, Kazuyoshi and Motoyama, Yuichi and Misawa, Takahiro and Yamaji, Youhei and Todo, Synge and Kawashima, Naoki and Sogabe, Tomohiro, Computer Physics Communications 258, 107536 (2021)
DOI:10.1016/j.cpc.2020.107536

4.

RESPACK: An ab initio tool for derivation of eﬀective low-energy model of material
Nakamura, Kazuma and Yoshimoto, Yoshihide and Nomura, Yusuke and Tadano, Terumasa andKawamura, Mitsuaki and Kosugi, Taichi and Yoshimi, Kazuyoshi and Misawa, Takahiro andMotoyama, Yuichi, Computer Physics Communications 261, 107781 (2021)
DOI:10.1016/j.cpc.2020.107781

MIZUGUCHI, Tomoko [ C class; 0 (B), 150 (C) ] ()— DNA unwinding mechanism studied by steered molecular dynamics simulations
1. Icosahedral order in liquid and glassy phases of cyclohexane
T. Mizuguchi, S. Tatsumi and S. Fujiwara, Mol. Sim. /bf 46 721 (2020).
DOI:10.1080/08927022.2020.1757092

MIZUKAMI, Wataru [ C class; 1200 (B), 0 (C) ] (147, 149)
— First principles calculations of crystals with quantum classical hybrid algorithms— Noisy simulations of ﬁrst-principles calculations using quantum classical hybrid algorithms
1. Orbital optimized unitary coupled cluster theory for quantum computer
W. Mizukami, K. Mitarai, Y.O. Nakagawa, T. Yamamoto, T. Yan, and Y.-y. Ohnishi, Phys.
Rev. Research 2, 033421 (2020)
DOI:10.1103/PhysRevResearch.2.033421
2.

Variational Quantum Simulation for Periodic Materials
N. Yoshioka, Y.O. Nakagawa, Y.-y. Ohnishi, W. Mizukami, arXiv:2008.09492

3.

Neural-Network Quantum States for the Electronic Structure of Real Solids
N. Yoshioka, W. Mizukami, F. Nori, arXiv:2010.01358

MORIKAWA, Yoshitada [ C class; 7400 (B), 1200 (C) ] (61)— Quantum simulations on dynamical heterogeneous catalysts
1. Blue moon ensemble simulation of aquation free energy proﬁles applied to mono and bifunctional
platinum anticancer drugs

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T. Hirakawa, D. R. Bowler, T. Miyazaki, Y. Morikawa, and L. A. Truﬂandier, J. Comput. Chem.
41, 1973 (2020).
DOI:10.1002/jcc.26367
2.

Identifying Atomic-Level Correlation Between Geometric and Electronic Structure at a MetalOrganic Interface
H. Koshida, H. Okuyama, S. Hatta, T. Aruga, Y. Hamamoto, I. Hamada, and Y. Morikawa, J.
Phys. Chem. C 124, 17696 (2020).
DOI:10.1021/acs.jpcc.0c04678

3.

Enhanced CO tolerance of Pt clusters supported on graphene with lattice vacancies
Y. Hamamoto, S. A. Wella, K. Inagaki, F. Abild-Pedersen, T. Bligaard, I. Hamada, and Y.
Morikawa, Phys. Rev. B 102, 075408 (2020).
DOI:10.1103/PhysRevB.102.075408

4.

Oxygen vacancy-induced insulator-metal transition in LaNiO3 thin ﬁlms
H. D. Nguyen, C. T. Bach, and Y. Morikawa, Phys. Rev. B 102, 165411 (2020).
DOI:10.1103/PhysRevB.102.165411

5.

Metal-Tip-Catalyzed Dehydrogenation of a Single Hydrocarbon Molecule
A. Shiotari, I. Hamada, T. Nakae, S. Mori, T. Okujima, H. Uno, H. Sakaguchi, Y. Hamamoto, Y.
Morikawa, and Y. Sugimoto, Nano Letters 20, 8339 (2020).
DOI:10.1021/acs.nanolett.0c03510

6.

Oxidative etching mechanism of diamond (100) surface
J. I. Enriquez, F. Muttaqien, M. Michiuchi, K. Inagaki, M. Geshi, I. Hamada, and Y. Morikawa
Carbon 174, 36-51 (2021).
DOI:10.1016/j.carbon.2020.11.057

7.

Density functional theory study on a nitrogen-rich carbon nitride material C3 N5 as photocatalyst
for CO2 reduction to C1 and C2 products
Y. Wang, T. N. Pham, Y. Tian, Y. Morikawa and L. Yan J. Colloid and Interface Science 585,
740 (2021).
DOI:10.1016/j.jcis.2020.10.054

8.

Alkaline earth atom doping-induced changes in the electronic and magnetic properties of graphene:
a density functional theory study
A. C. F. Serraon, J. A. D. Del Rosario, P.-Y. A. Chuang, M. N. Chong, Y. Morikawa, A. A. B.
Padama, and J. D. Ocon RSC Advances 11, 6268, (2021).
DOI:10.1039/D0RA08115A

9.

Multi-scale Simulation of Equilibrium Step Fluctuations on Cu(111) Surface
H. H. Halim, S. E. M. Putra, F. Muttaqien, I. Hamada, K. Inagaki, Y. Hamamoto, and Y.
Morikawa, ACS Omega 6, 5183 (2021).
DOI:10.1021/acsomega.0c05064

10. Role of intermolecular interactions in the catalytic reaction of formic acid on Cu(111)
A. Shiotari, S. E. M. Putra, Y. Shiozawa, Y. Hamamoto, K. Inagaki, Y. Morikawa, Y. Sugimoto,J. Yoshinobu, and I. Hamada, Small, in press.
DOI:10.1002/smll.202008010
11. Activation free energies for formation and dissociation of N-N, C-C, and C-H bonds in a Na-Ga
melt
T. Kawamura, M. Imanishi, M. Yoshimura, Y. Mori, and Y. Morikawa Comput. Mater. Sci. 194,110366 (2021).

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DOI:10.1016/j.commatsci.2021.110366

MORITA, Satoshi [ B class; 1200 (B), 200 (C) ] (274)— Study of phase transitions and critical phenomena by tensor network methods— Study of phase transitions and critical phenomena by tensor renormalization group
1. Global optimization of tensor renormalization group using the corner transfer matrix
S. Morita, and N. Kawashima, Phys. Rev. B 103, 045131 (2021).
DOI:10.1103/PhysRevB.103.045131
2.

Continuous phase transition between Neel and valence bond solid phases in a J-Q-like spin laddersystemT. Ogino, R. Kaneko, S. Morita, S. Furukawa, and N. Kawashima, Phys. Rev. B 103, 085117(2021).
DOI:10.1103/PhysRevB.103.085117

MOTOME, Yukitoshi [ C class; 8800 (B), 1350 (C) ] (193)— Theoretical study of correlated electron systems with strong spin-orbit coupling
1. Magnetic hedgehog lattices in noncentrosymmetric metals
S. Okumura, S. Hayami, Y. Kato, and Y. Motome Phys. Rev. B 101, 144416 (2020).
DOI:10.1103/PhysRevB.101.144416
2.

Switching of band inversion and topological surface states by charge density wave
N. Mitsuishi, Y. Sugita, M. S. Bahramy, M. Kamitani, T. Sonobe, M. Sakano, T. Shimojima,
H. Takahashi, H. Sakai, K. Horiba, H. Kumigashira, K. Taguchi, K. Miyamoto, T. Okuda, S.
Ishiwata, Y. Motome, and K. Ishizaka Nat. Commun. 11, 2466 (2020).
DOI:10.1038/s41467-020-16290-w

3.

Antiferromagnet-Semiconductor Van Der Waals Heterostructures: Interlayer Interplay of Excitonwith Magnetic Ordering
M. Onga, Y. Sugita, T. Ideue, Y. Nakagawa, R. Suzuki, Y. Motome, and Y. Iwasa, Nano Lett.
20, 4625 (2020).
DOI:10.1021/acs.nanolett.0c01493

4.

Materials design of Kitaev spin liquids beyond the Jackeli-Khaliullin mechanism
Y. Motome, R. Sano, S.-H. Jang, Y. Sugita, and Y. Kato J. Phys: Condens. Matter 32, 404001(2020).
DOI:10.1088/1361-648X/ab8525

5.

Anomalous Hall eﬀect in κ-type organic antiferromagnets
M. Naka, S. Hayami, H. Kusunose, Y. Yanagi, Y. Motome, and H. Seo Phys. Rev. B 102, 075112(2020).
DOI:10.1103/PhysRevB.102.075112

6.

Thermodynamic classiﬁcation of three-dimensional Kitaev spin liquids
T. Eschmann, P. A. Mishchenko, K. O’Brien, T. A. Bojesen, Y. Kato, M. Hermanns, Y. Motome,
and S. Trebst Phys. Rev. B 102, 075125 (2020).
DOI:10.1103/PhysRevB.102.075125

7.

Thermodynamic and transport properties in disordered Kitaev models
J. Nasu and Y. Motome, Phys. Rev. B 102, 054437 (2020).
DOI:10.1103/PhysRevB.102.054437

8.

Channel-selective non-Fermi liquid behavior in the two-channel Kondo lattice model under a373

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

magnetic ﬁeld
K. Inui and Y. Motome, Phys. Rev. B 102, 155126 (2020).
DOI:10.1103/PhysRevB.102.155126
9.

Computational design of f-electron Kitaev magnets: Honeycomb and hyperhoneycomb compounds
A2 PrO3 (A= alkali metals)
S.-H. Jang, R. Sano, Y. Kato, and Y. Motome, Phys. Rev. Materials 4, 104420 (2020).
DOI:10.1103/PhysRevMaterials.4.104420

10. Imaging the coupling between itinerant electrons and localised moments in the centrosymmetricskyrmion magnet GdRu2 Si2
Y. Yasui, C. J. Butler, N. D. Khanh, S. Hayami, T. Nomoto, T. Hanaguri, Y. Motome, R. Arita,
T. Arima, Y. Tokura, and S. Seki Nat. Commun. 11, 5925 (2020).
DOI:10.1038/s41467-020-19751-4
11. Optical Hall response in spin-orbit coupled metals: Comparative study of magnetic cluster monopole,quadrupole, and toroidal orders
T. Sato, Y. Umimoto, Y. Sugita, Y. Kato, and Y. Motome Phys. Rev. B 103, 054416 (2021).
DOI:10.1103/PhysRevB.103.054416
12. Noncoplanar multiple-Q spin textures by itinerant frustration: Eﬀects of single-ion anisotropy andbond-dependent anisotropy
S. Hayami and Y. Motome, Phys. Rev. B 103, 054422 (2021).
DOI:10.1103/PhysRevB.103.054422
13. Phase transitions between helices, vortices, and hedgehogs driven by spatial anisotropy in chiralmagnets
K. Shimizu, S. Okumura, Y. Kato, and Y. Motome, Phys. Rev. B 103, 054427 (2021).
DOI:10.1103/PhysRevB.103.054427
14. Perovskite as a spin current generator
M. Naka, Y. Motome, and H. Seo Phys. Rev. B 103, 125114 (2021).
DOI:10.1103/PhysRevB.103.125114
15. Phase Shift in Skyrmion Crystals
S. Hayami, T. Okubo, and Y. Motome, preprint (arXiv:2005.03168).
16. Spin Moire Engineering of Emergent Electromagnetism
K. Shimizu, S. Okumura, Y. Kato, and Y. Motome, preprint (arXiv:2009.14569).
17. Topological spin crystals by itinerant frustration
S. Hayami and Y. Motome, preprint (arXiv:2103.10647).
18. Spin dynamics in the Kitaev model with disorder: Quantum Monte Carlo study of dynamical spin
structure factor, magnetic susceptibility, and NMR relaxation rate
J. Nasu and Y. Motome, preprint (arXiv:2103.10549).

MURAGUCHI, Masakazu [ B class; 400 (B), 100 (C) ] (178)— Study on machine learning model of carrier dynamics in semiconductor devices
MURASHIMA, Takahiro [ C class; 2400 (B), 450 (C) ] (267)— Multiscale simulation of polymeric ﬂuids and solids
1. Viscosity Overshoot in Biaxial Elongational Flow: Coarse-Grained Molecular Dynamics Simulation of Ring-Linear Polymer Mixtures374

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

T. Murashima, K. Hagita, and T. Kawakatsu, submitted to Macromolecules

NADA, Hiroki [ B,C class; 600 (B), 650 (C) ] (278, 279)
— Large-scale metadynamics simulations for water and aqueous solutions— Metadynamics Simulation Analysis of Various Cluster Structures Appearing in Calcium Carbonate
Supersaturated Solution
1. High Virus Removal by Self-Organized Nanostructured 2D Liquid-Crystalline Smectic Membranes
for Water Treatment
D. Kuo, M. Liu, K. R. S. Kumar, K. Hamaguchi, K. P. Gan, T. Sakamoto, T. Ogawa, N. Miyamoto,
H. Nada, M. Kimura, M.Henmi, H. Katayama and T. Kato Small 16 (2020) 2001721.
2.

High-Density Liquid Water at a Water-Ice Interface
H. Niinomi, T. Yamazaki, H. Nada, T. Hama, A. Koichi, J. T. Okada, J. Nozawa, S. Uda and Y.
Kimura J. Phys. Chem. Lett. 11 (2020) 6779.

3.

Melt Crystallization Mechanism Analyzed with Dimensional Reduction of Distribution Function
Geometries
H. Nada, Sci. Rep. 10 (2020) 15465.

4.

Capturing the Moment of Emergence of Crystal Nucleus from Disorder
T. Nakamuro, M. Sakakibara, H. Nada, K. Harano and E. Nakamura J. Am. Chem. Soc. 143(2021) 1763.

NAKAGAWA, Naoko [ B,C class; 2600 (B), 450 (C) ] (266)— Global thermodynamic functions extended to nonequilibrium steady states
1. Eﬀective Langevin equations leading to large deviation function of time-averaged velocity for a
nonequilibrium Rayleigh piston
Masato Itami, Yohei Nakayama, Naoko Nakagawa and Shin-ichi Sasa Phys. Rev. E 103 (2021)
022125.

NAKAHARA, Akio [ B class; 400 (B), 100 (C) ] (311)— Diversity in memory eﬀects of ﬂow in paste
NAKAMURA, Kazuma [ C class; 2800 (B), 0 (C) ] (116)— Ab initio calculation for thermodynamic phase diagram: Investigation on exchange-correlation functional dependence
projectAb initio phonon calculation for Ca5Or3O12
NAKANO, Hiroki [ C class; 3000 (B), 550 (C) ] (263)— Numerical study on low-energy states of quantum spin systems
NAKAYAMA, Takashi [ C class; 4200 (B), 900 (C) ] (85)
— First-principles study on physics of gap-state control at metal/semiconductor interfaces II— First-principles study on physics of gap-state control at metal/semiconductor interfaces III: eﬀects ofelectric ﬁeld and alloy interface
NASU, Joji [ C class; 1800 (B), 550 (C) ] (209)— Disorder eﬀect on Kitaev quantum spin liquids
1. Majorana-Magnon Crossover by a Magnetic Field in the Kitaev Model: Continuous-Time Quantum Monte Carlo Study
J. Yoshitake, J. Nasu, Y. Kato, and Y. Motome, Phys. Rev. B 101, 100408(R) (2020).

375

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo2.

The range of non-Kitaev terms and fractional particles in α-RuCl3
Y. Wang, G. B. Osterhoudt, Y. Tian, P. Lampen-Kelley, A. Banerjee, T. Goldstein, J. Yan, J.
Knolle, H. Ji, R. J. Cava, J. Nasu, Y. Motome, S. Nagler, D. Mandrus, and K. S. Burch, npj
Quantum Materials 5, 14 (2020).

3.

Majorana-Magnon Crossover by a Magnetic Field in the Kitaev Model: Continuous-Time Quantum Monte Carlo Study
J. Yoshitake, J. Nasu, Y. Kato, and Y. Motome, Phys. Rev. B 101, 100408(R) (2020).

4.

Majorana-Mediated Spin Transport in Kitaev Quantum Spin Liquids
T. Minakawa, Y. Murakami, A. Koga, and J. Nasu, Phys. Rev. Lett. 125, 047204 (2020).

5.

Strong enhancement of magnetic susceptibility induced by spin-nematic ﬂuctuations in an excitonic insulating system with spin-orbit coupling
J. Nasu, M. Naka, S. Ishihara, Phys. Rev. B 102, 045143 (2020).

6.

Thermodynamic and transport properties in disordered Kitaev models
J. Nasu and Y. Motome, Phys. Rev. B 102, 054437/1-6 (2020).

7.

Spin Seebeck eﬀect in nonmagnetic excitonic insulators
J. Nasu and M. Naka, Phys. Rev. B 103, L121104/1-6 (2021).

NIKI, Kaori [ C class; 0 (B), 400 (C) ] (180)— Establishment of molecular crystal surface analysis technique using wave number space resolved photoelectron spectroscopy
NISHIDATE, Kazume [ C class; 1600 (B), 0 (C) ] (135)— Investigation on the electronic structure of photo-catalytic double-perovskite
1. Electronic Properties and Crystal Structures of Double-Perovskites, Ba2 BiIII BiV O6 , Ba2 PrBiO6 ,and Ba2 PrSbO6 : First-principles study
K. Nishidate, A. Adiko, M. Matsukawa, H. Taniguchi, A. Sato, A. Matsushita, S. Tanibayashi and
M. Hasegawa, Mater. Res. Express 7 (2020) 065505.
2.

Hybridization versus sublattice symmetry breaking in the band gap opening in graphene onNi(111): A ﬁrst-principles study
K. Nishidate, S. Tanibayashi, M. Matsukawa, M. Hasegawa, Surface Science, 700, October (2020)
121651.

NISHIGUCHI, Kazutaka [ B class; 700 (B), 150 (C) ] (212, 214)
— Development of electronic structure calculation for solids with post-Hartree-Fock— Development of electronic structure calculation for solids with quantum chemistry calculations
NOGUCHI, Hiroshi [ C class; 7400 (B), 1200 (C) ] (230)— structure formation of biomembrane
1. Rational Design Principles of Attenuated Cationic Lytic Peptides for Intracellular Delivery of
Biomacromolecules
N.Tamemoto, M. Akishiba, K. Sakamoto, K. Kawano, H. Noguchi, S. Futaki, Mol. Pharmaceutics
17, 2175-2185 (2020).
DOI:10.1021/acs.molpharmaceut.0c00312
2.

Pattern Formation in Reaction-Diﬀusion System on Membrane with Mechanochemical Feedback
N. Tamemoto and H. Noguchi Sci. Rep. 10, 19582/1-10 (2020).
DOI:10.1038/s41598-020-76695-x

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3.

Molecular Dynamics Simulation of Soundwave Propagation in a Simple Fluid
Y. Asano, H. Watanabe, and H. Noguchi, J. Chem. Phys. 153, 124504 (2020).
DOI:10.1063/5.0024150

4.

Conformation of ultra-long-chain fatty acid in lipid bilayer: Molecular dynamics study
K. Kawaguchi, K. M. Nakagawa, S. Nakagawa, H. Shindou, H. Nagao, and H. Noguchi, J. Chem.
Phys. 153, 165101 (2020).
DOI:10.1063/5.0026030

5.

Virtual bending method to calculate bending rigidity, saddle-splay modulus, and spontaneous
curvature of thin ﬂuid membranes
H. Noguchi, Phys. Rev. E 102, 053315 (2020).
DOI:10.1103/PhysRevE.102.053315

6.

Undulation of a moving ﬂuid membrane pushed by ﬁlament growth
H. Noguchi and O. Pierre-Louis Sci. Rep. 11, 7985 (2021).
DOI:10.1038/s41598-021-87073-6

7.

Binding of thermalized and active membrane curvature-inducing proteins
Q. Goutaland, F. van Wijland, J.-B. Fournier, and H. Noguchi Soft Matter 17, 5560 (2021).
DOI:10.1039/d1sm00027f

8.

Reaction-Diﬀusion Waves Coupled with Membrane Curvature
N. Tamemoto and H. Noguchi Soft Matter (2021) in press
DOI:10.1039/d1sm00540e

9.

Eﬀects of polymers on the cavitating ﬂow around a cylinder: A Large-scale molecular dynamics
analysis
Y. Asano, H. Watanabe, and H. Noguchi, J. Chem. Phys. 155, 14905 (2021).
DOI:10.1063/5.0056988

NOGUCHI, Yoshifumi [ C class; 5200 (B), 850 (C) ] (75)
— Development of Exact First-Principles GW+Bethe-Salpeter Method— Development of GW+Bethe-Salpeter method
1. Quantum-mechanical hydration plays critical role in the stability of ﬁreﬂy oxyluciferin isomers:
State-of-the-art calculations of the excited states
Yoshifumi Noguchi, Miyabi Hiyama, Hidefumi Akiyama, and Osamu Sugino, J. Chem. Phys.
153, 201103 (2020).
DOI:10.1063/5.0031356

NOMURA, Yusuke [ C class; 7600 (B), 1150 (C) ] (195)— Ab initio calculation for strongly-correlated nickelate superconductor— Comparison between nickelate and cuprate superconductors
1. Machine Learning Quantum States-Extensions to Fermion–Boson Coupled Systems and ExcitedState Calculations
Yusuke Nomura J. Phys. Soc. Jpn. 89, 054706 (2020).
2.

Eﬃcient implementation of the continuous-time interaction-expansion quantum Monte Carlo method
Hiroshi Shinaoka, Yusuke Nomura and Emanuel Gull, Computer Physics Communications 252,
106826 (2020).

3.

Higgs-mode resonance in third harmonic generation in NbN superconductors: Multiband electron-

377

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyophonon coupling, impurity scattering, and polarization-angle dependence
Naoto Tsuji and Yusuke Nomura Phys. Rev. Research 2, 043029 (2020).
4.

Eﬃcient ab initio Migdal-Eliashberg calculation considering the retardation eﬀect in phononmediated superconductors
Tianchun Wang, Takuya Nomoto, Yusuke Nomura, Hiroshi Shinaoka, Junya Otsuki, Takashi
Koretsune, and Ryotaro Arita Phys. Rev. B 102, 134503 (2020).

5.

Magnetic exchange coupling in cuprate-analog d9 nickelates
Yusuke Nomura, Takuya Nomoto, Motoaki Hirayama, and Ryotaro Arita, Phys. Rev. Research
2, 043144 (2020).

6.

Geometrical Hall eﬀect and momentum-space Berry curvature from spin-reversed band pairs
Max Hirschberger, Yusuke Nomura, Hiroyuki Mitamura, Atsushi Miyake, Takashi Koretsune,
Yoshio Kaneko, Leonie Spitz, Yasujiro Taguchi, Akira Matsuo, Koichi Kindo, Ryotaro Arita,
Masashi Tokunaga, and Yoshinori Tokura Phys. Rev. B 103, L041111 (2021).

NOZAWA, Kazuki [ B,C class; 800 (B), 300 (C) ] (151)— First-principles study of atomic and electronic structures of intermetallic compound catalysts
1. Atomic structure of the (111) surface of the antiferromagnetic 1/1 Au-Al-Tb approximant
Sam Coates, Kazuki Nozawa, Masahiro Fukami, Kazuki Inagaki, Masahiko Shimoda, Ronan McGrath, Hem Raj Sharma, and Ryuji Tamura, Physical Review B 102 235419(2020)
DOI:10.1103/PhysRevB.102.235419
2.

Accuracy of Cluster Model Calculations for Quasicrystal Surface
Masanori Sato, Takanobu Hiroto, Yoshitaka Matsushita, and Kazuki Nozawa, Materials Transactions, 62, 350(2021)
DOI:10.2320/matertrans.MT-MB2020015

OBATA, Masao [ B class; 700 (B), 200 (C) ] (160)— Analysis on atomic and magnetic structure in magnetic molecular complex crystal and interface andinvestigation of external electric and magnetic ﬁeld eﬀect— Analysis on atomic and magnetic structure in magnetic molecular complex crystal and interface andinvestigation of external electromagnetic ﬁeld eﬀect
1. Anatomy of magnetic anisotropy and voltage-controlled magnetic anisotropy in metal oxide heterostructure from ﬁrst principles
Indra Pardede, Daiki Yoshikawa, Tomosato Kanagawa, Nurul Ikhsan, Masao Obata, and Tatsuki
Oda, Crystals: 10, (2020) 1118.
DOI:10.3390/cryst10121118
2.

Finite electric-ﬁeld approach to evaluate the vertex correction for the screened Coulomb interactionin the quasiparticle self-consistent GW method
Hirofumi Sakakibara, Takao Kotani, Masao Obata, and Tatsuki Oda, Phys. Rev. B 101, (2020)
205120.
DOI:10.1103/PhysRevB.101.205120

ODA, Tatsuki [ C,E class; 16400 (B), 3200 (C) ] (52)— Analyses on electronic structure and magnetoelectric eﬀect in high-performance spintronics and magnetic materials
1. Anatomy of large perpendicular magnetic anisotropy in free-standing Co/Ni (111) multilayer,
Journal of Magnetism and Magnetic Materials
Indra Pardede, Daiki Yoshikawa, Tomosato Kanagawa, Nurul Ikhsan, Itsuki Murata, Masao

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Obata, Tatsuki Oda, Journal of Magnetism and Magnetic Materials 500(2020)166357.
2.

Finite electric-ﬁeld approach to evaluate the vertex correction for the screened Coulomb interactionin the quasiparticle self-consistent GW method
Hirofumi Sakakibara, Takao Kotani, Masao Obata, and Tatsuki Oda, Physical Review B, 101(2020) 205120.

3.

Electronic structure investigation of spinel NiCo2O4 from quasi-particle self-consistent GW method
Hasan Al Rasyid, Masao Obata, Indra Pardede, Marleni Wirmas, Takao Kotani, and Tatsuki Oda,
The Science Reports of Kanazawa University 64 (2020).

4.

Anatomy of magnetic anisotropy and voltage-controlled magnetic anisotropy in metal oxide heterostructure from ﬁrst principles
Indra Pardede, Daiki Yoshikawa, Tomosato Kanagawa, Nurul Ikhsan, Masao Obata, and Tatsuki
Oda, Crystals 10 (2020) 1118.

OGUCHI, Tamio [ B,C class; 4000 (B), 250 (C) ] (97)— Magnetocaloric Eﬀect of Transition-Metal Alloys
1. First-principles study of magnetism and phase stabilities of V2 based antiferromagnetic Heusler
alloysF. Kuroda, T. Fukushima, and T. Oguchi, J. Appl. Phys. 127, 193904 (2020).
DOI:10.1063/1.5143826
2.

Ferroelectric atomic displacement in multiferroic tetragonal perovskite Sr1/2 Ba1/2 MnO3
D. Okuyama, K. Yamauchi, H. Sakai, Y. Taguchi, Y. Tokura, K. Sugimoto, T. J. Sato, and T.
Oguchi, Phys. Rev. Research 2, 033038 (2020).
DOI:10.1103/PhysRevResearch.2.033038

3.

Spin injection through energy-band symmetry matching with high spin polarization in atomicallycontrolled ferromagnet/ferromagnet/semiconductor structures
Michihiro Yamada, Fumiaki Kuroda, Makoto Tsukahara, Shinya Yamada, Tetsuya Fukushima,
Kentarou Sawano, Tamio Oguchi, and Kohei Hamaya, npg Asia Materials 12, 47 (2020).
DOI:10.1038/s41427-020-0228-5

4.

DFT-based Engineering of Dirac Surface States in Topological-insulator Multilayers
Takao Kosaka, Kunihiko Yamauchi, and Tamio Oguchi, J. Phys. Soc. Jpn. 89, 094701 (2020).
DOI:10.7566/JPSJ.89.094701

5.

Suppression of O-redox reactions by multivalent Cr in Li-excess Li2.4 M0.8 M ’0.8 O4 (M , M ’=Cr,
Mn, and Ti) cathodes with layered and cation-disordered rock-salt structures
Motoyuki Hamaguchi, Hiroyoshi Momida, Ayuko Kitajou, Shigeto Okada, and Tamio Oguchi,Electrochimica Acta 354, 136630 (2020).
DOI:10.1016/j.electacta.2020.136630

6.

Insight into the diﬀusion mechanism of sodium ion-polaron complexes in orthorhombic P2 layered
cathode oxide Nax MnO2
Huu Duc Luong, Van An Dinh, Hiroyoshi Momida, and Tamio Oguchi, Phys. Chem. Chem.
Phys. 22, 18219-18228 (2020).
DOI:10.1039/d0cp03208e

7.

Impact of Inter-site Spin-Orbit Coupling on Perpendicular Magnetocrystalline Anisotropy in
Cobalt-Based Thin Films
Thi Phuong Thao Nguyen, Kunihiko Yamauchi, Kohji Nakamura, and Tamio Oguchi, J. Phys.
Soc. Jpn. 89, 114710 (2020).

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DOI:10.7566/JPSJ.89.114710
8.

Magnetocaloric eﬀect in MnCoGe alloys studied by ﬁrst-principles calculations and Monte-Carlosimulation
Hung Ba Tran, Tetsuya Fukushima, Yukihiro Makino, and Tamio Oguchi, Solid State Commun.
323, 114077 (2021).
DOI:10.1016/j.ssc.2020.114077

9.

Tuning structural-transformation temperature toward giant magnetocaloric eﬀect in MnCoGe
alloy: A theoretical study
Hung Ba Tran, Tetsuya Fukushima, Kazunori Sato, Yukihiro Makino, and Tamio Oguchi, J.
Alloys Compd. 854, 157063/1-9 (2021).
DOI:10.1016/j.jallcom.2020.157063

OHMURA, Satoshi [ C class; 5000 (B), 0 (C) ] (89, 90)— Eﬀects of solvents on properties of artiﬁcial-retina molecule: ab initio molecular dynamics simulations— Structural and transport properties of multi-component liquid Fe mixtures under high pressure
1. Structures of Liquid Iron–Light-Element Mixtures under High Pressure
S. Ohmura, T. Tsuchiya and F. Shimojo, physica status solidi (b). 257, 2000098 (2020).
DOI:10.1002/pssb.202000098
2.

Dissociation mechanism from highly charged bromophenol: ab initio molecular dynamics simulations
S. Ohmura, K. Nagaya, F. Shimojo and M. Yao, Z. Phys. Chem. 235, 169 (2021).
DOI:10.1515/zpch-2020-1634

OHNISHI, Masato [ C class; 5000 (B), 950 (C) ] (76)— Analysis of Thermoelectric Properties of Clathrate Compounds with Ab Initio Calculations
1. Ultimate impedance of coherent heat conduction in van der Waals graphene-MoS2 heterostructures
S. Hu, S. Ju, J. Guo, B. Xu, M. Ohnishi, and J. Shiomi, Mater. Today Phys. 16, 100324 (2021).
DOI:10.1016/j.mtphys.2020.100324
2.

Run Hu, Sotaro Iwamoto, Lei Feng, Shenghong Ju, Shiqian Hu, Masato Ohnishi, Naomi Nagai,
Kazuhiko Hirakawa, Junichiro Shiomi
Machine-learning-optimized aperiodic superlattice minimizes coherent phonon heat conduction
Physical Review X 10, 2 (2020).
DOI:10.1103/PhysRevX.10.021050

OHNO, Akira [ B class; 400 (B), 0 (C) ] ()— Modeling and elucidation of electron transport mechanism in liquid crystals
OHNO, Kaoru [ C class; 3000 (B), 600 (C) ] (105)— Improvement and application of all-electron mixed basis program
1. Clear evidence of element partitioning eﬀects in a Ti-6Al-4V alloy by the ﬁrst-principles phaseﬁeld method
T N Pham, K Ohno, R Sahara, R Kuwahara, and S Bhattacharyya, J. Phys.: Cond. Mat. 32,
264001 (2020).
DOI:10.1088/1361-648X/ab7ad5
2.

Study on Ni-Ti alloys around equiatomic composition by the ﬁrst-principles phase ﬁeld method
Kaoru Ohno, Monami Tsuchiya, Riichi Kuwahara, Ryoji Sahara, Swastibrata Bhattacharyya, andThi Nu Pham, Comp. Mat. Sci. 191, 110284 (2021).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

DOI:10.1016/j.commatsci.2021.110284

OHSAWA, Kazuhito [ C class; 1200 (B), 300 (C) ] (137)— Study of interaction between radiation damage and interstitial atom
OHTO, Tatsuhiko [ C class; 2600 (B), 0 (C) ] (127)— First-principles molecular dynamics study of water/TiO2 interfaces using hybrid functionals
1. Acceleration of Electrochemical CO2 Reduction to Formate at the Sn/Reduced Graphene Oxide
Interface
Takuya Tsujiguchi, Yusuke Kawabe, Samuel Jeong, Tatsuhiko Ohto, Suresh Kukunuri, Hirotaka
Kuramochi, Yasufumi Takahashi, Tomohiko Nishiuchi, Hideki Masuda, Mitsuru Wakisaka, Kailong Hu, Ganesan Elumalai, Jun-ichi Fujita, and Yoshikazu Ito ACS Catal. 11, 3310 (2021).
2.

Single-Molecule Conductance of a π-Hybridized Tripodal Anchor while Maintaining Electronic
Communication
Tatsuhiko Ohto, Aya Tashiro, Takuji Seo, Nana Kawaguchi, Yuichi Numai, Junpei Tokumoto,
Soichiro Yamaguchi, Ryo Yamada, Hirokazu Tada, Yoshio Aso, and Yutaka Ie Small 17, 2006709(2021).

3.

Improving Intramolecular Hopping Charge Transport via Periodical Segmentation of π-Conjugation
in a Molecule
Yutaka Ie, Yuji Okamoto, Takuya Inoue, Takuji Seo, Tatsuhiko Ohto, Ryo Yamada, Hirokazu
Tada, and Yoshio Aso J. Am. Chem. Soc. 143, 599 (2021).

4.

Catalytic Activity of Graphene-Covered Non-Noble Metals Governed by Proton Penetration inElectrochemical Hydrogen Evolution Reaction
Kailong Hu, Tatsuhiko Ohto, Yuki Nagata, Mitsuru Wakisaka, Yoshitaka Aoki, Jun-ichi Fujita,
and Yoshikazu Ito Nat. Commun. 12, 203 (2021).

5.

Correlation between the Dipole Moment of Nonfullerene Acceptors and the Active Layer Morphology of Green-Solvent Processed P3HT-based Organic Solar Cells
Shreyam Chatterjee, Tatsuhiko Ohto, Hirokazu Tada, Seihou Jinnai, and Yutaka Ie ACS Sustain.
Chem. Eng. 8, 19013 (2020)6.

Vibrational Couplings and Energy Transfer Pathways of Water’s Bending Mode
Chun-Chieh Yu, Kuo-Yang Chiang, Masanari Okuno, Takakazu Seki, Tatsuhiko Ohto, Xiaoqing
Yu, Vitaly Korepanov, Hiro-o Hamaguchi, Mischa Bonn, Johannes Hunger, and Yuki Nagata Nat.
Commun. 11, 5977 (2020)7.

Vibrational Mode Frequency Correction of Liquid Water in Density Functional Theory Molecular
Dynamics Simulations with van der Waals Correction
Kai Zhong, Chun-Chieh Yu, Mayank Dodia, Mischa Bonn, Yuki Nagata, and Tatsuhiko Ohto
Phys. Chem. Chem. Phys. 22, 12785 (2020).

8.

Decoding the molecular water structure at complex interfaces through surface-speciﬁc spectroscopyof the water bending mode
Takakazu Seki, Chun-Chieh Yu, Xiaoqing Yu, Tatsuhiko Ohto, Shumei Sun, Konrad Meister, Ellen
H. G. Backus, Mischa Bonn, and Yuki Nagata, Phys. Chem. Chem. Phys. 22, 10934 (2020).

9.

Hydrogen-Bonds and Molecular Orientations of Supramolecular Structure between Barbituric
Acid and Melamine Derivative at the Air/Water Interface Revealed by Heterodyne-Detected Vibrational Sum Frequency Generation Spectroscopy
Masanari Okuno, Shuhei Yamada, Tatsuhiko Ohto, Hirokazu Tada, Waka Nakanishi, Katsuhiko
Ariga, and Taka-aki Ishibashi J. Phys. Chem. Lett. 11, 2422 (2020).

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10. Mechanical switching of current-voltage characteristics in spiropyran single-molecule junctions
Takashi Tamaki, Keigo Minode, Yuichi Numai, Tatsuhiko Ohto, Ryo Yamada, Hiroshi Masai,
Hirokazu Tada, and Jun Terao Nanoscale, 12, 7527 (2020).
11. Molecular Structure and Modeling of Water-Air and Ice-Air Interfaces Monitored by Sum-Frequency
Generation
Fujie Tang, Tatsuhiko Ohto, Shumei Sun, Jeremy Rouxel, Sho Imoto, Ellen H. G. Backus, Shaul
Mukamel, Mischa Bonn, and Yuki Nagata Chem. Rev. 120, 3633 (2020).
12. Eﬀect of Graphene Encapsulation of NiMo Alloys on Oxygen Evolution Reaction
Samuel Jeong, Kailong Hu, Tatsuhiko Ohto, Yuki Nagata, Hideki Masuda, Jun-ichi Fujita, andYoshikazu Ito ACS Catal. 10, 792 (2020).
13. Impact of intermolecular vibrational coupling eﬀects on the sum-frequency generation spectra of
the water/air interface
Naveen Kumar Kaliannan, Andres Henao Aristizabal, Hendrik Wiebeler, Frederik Zysk, TatsuhikoOhto, Yuki Nagata, and Thomas D. Kuhne Mol. Phys. 118, 1620358 (2020).

OHTSUKI, Tomi [ C class; 7800 (B), 700 (C) ] (27)
— Quantum phase transitions in novel disordered systems— Quantum phase transitions in novel disordered topological systems
1. Transfer matrix study of the Anderson transition in non-Hermitian systems
Xunlong Luo, Tomi Ohtsuki, Ryuichi Shindou arXiv:2103.05239
2.

Universality Classes of the Anderson Transitions Driven by Non-Hermitian Disorder
Xunlong Luo, Tomi Ohtsuki, Ryuichi Shindou Phys. Rev. Lett. 126, 090402 (2021)
DOI:10.1103/PhysRevLett.126.090402

3.

Machine learning the dynamics of quantum kicked rotor
Tomohiro Mano, Tomi Ohtsuki arXiv:2101.09432

4.

Ballistic transport in disordered Dirac and Weyl semimetals
Koji Kobayashi, Miku Wada, Tomi Ohtsuki Phys. Rev. Research 2, 022061(R)(2020)
DOI:10.1103/PhysRevResearch.2.022061

OKAMOTO, Yuko [ C class; 5800 (B), 0 (C) ] (246)— Study on complex systems by generalized-ensemble algorithms
1. Calculation of the residual entropy of Ice Ih by Monte Carlo simulation with the combination of
the replica-exchange Wang–Landau algorithm and multicanonical replica-exchange method
T. Hayashi, C. Muguruma, and Y. Okamoto, J. Chem. Phys. 154 (2021) 044503.

OKAZAKI, Susumu [ C class; 1200 (B), 350 (C) ] (273)— Investigation of the molecular origins of the mechanical and thermal properties of realistic biopolymers using all-atomistic molecular dynamics
1. A comparison of the brittle PMMA with the ductile PC on the elasticity and yielding from amolecular dynamics perspective
Zhiye Tang, Kazushi Fujimoto, Susumu Okazaki, Polymer 226, 123809 (2021).

OKITSU, Kouhei [ C class; 200 (B), 0 (C) ] (323)— Study on bankruptcy of the two-beam approximation in X-ray crystal structure analysis

382

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

OKUBO, Tsuyoshi [ C class; 7400 (B), 1250 (C) ] (228)— Finite temperature properties of frustrated spin systems
1. Anisotropic Tensor Renormalization GroupD. Adachi, T. Okubo and S. Todo Phys. Rev. B, 102 (2020) 054432.
DOI:10.1103/PhysRevB.102.054432
2.

Phase Shift in Skyrmion Crystals
S. Hayami, T. Okubo, and Y. Motome, arXiv:2005.03168

OKUMURA, Hisashi [ C class; 4800 (B), 1150 (C) ] (245)— Disruption of amyloid ﬁbril by nonequilibrium molecular dynamics simulations— Molecular dynamics simulations for assembly and disassembly of protein aggregates
1. Energetics and kinetics of substrate analog-coupled staphylococcal nuclease folding revealed by astatistical mechanical approach
T. Mizukami, S. Furuzawa, S. G. Itoh, S. Segawa, T. Ikura, K. Ihara, H. Okumura, H. Roder, andK. Maki Proc. Natl. Acad. Sci. USA 117 (2020) 19953-19962.
2.

Replica-permutation molecular dynamics simulations of an amyloid-β(16-22) peptide and polyphenols
L. Le Nguyen Ngoc, S. G. Itoh, P. Sompornpisut, and H. Okumura : Chem. Phys. Lett. 758(2020) 137913/1-7.

3.

Involvement of pore helix in voltage-dependent inactivation of TRPM5 channel
K. Uchida, T. Kita, M. Hatta, S. G. Itoh, H. Okumura, M. Tominaga, J. Yamazaki : Heliyon 7(2021) e06102/1-10.

4.

Structural basis for promiscuous action of monoterpenes on TRP channels
T. H. D. Nguyen, S. G. Itoh, H. Okumura, M. Tominaga Commun. Biol. 4 (2021) 293/1-12.

5.

Dimerization of α-synuclein fragments studied by isothermal-isobaric replica-permutation molecular dynamics simulation
M. Yamauchi and H. Okumura J. Chem. Inf. Model. 61 (2021) 1307-1321.

6.

Structural dynamics and susceptibility of anti-HIV drugs against HBV reverse transcriptase
J. Kammarabutr, P. Mahalapbutr, H. Okumura, P. Wolschann, and T. Rungrotmongkol J. Biomol.
Struct. Dyn. 39 (2021) 2502-2511.

7.

Role of water molecules in the laser-induced disruption of amyloid ﬁbrils observed by nonequilibrium molecular dynamics simulations
H. Okumura, S. G. Itoh, K. Nakamura and T. Kawasaki, J. Phys. Chem. B, submitted.

ONO, Shota [ B,C class; 1000 (B), 250 (C) ] (145, 146)
— A new method for exploring dynamically stable alloys from the periodic table of 2D materials— Uniﬁed understanding of the femtosecond infrared luminescence for metals— Uniﬁed understanding of the femtosecond infrared luminescence for metals: II
1. Ultrafast photoluminescence in metals: Theory and its application to silver
S. Ono and T. Suemoto, Phys. Rev. B 102, 024308 (2020).
DOI:10.1103/PhysRevB.102.024308
2.

Two-dimensional square lattice polonium stabilized by the spin-orbit coupling
S. Ono, Sci. Rep. 10, 11810 (2020).
DOI:10.1038/s41598-020-68877-4

383

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.

Dynamical stability of two-dimensional metals in the periodic table
S. Ono, Phys. Rev. B 102, 165424 (2020).
DOI:10.1103/PhysRevB.102.165424

4.

High-throughput computational search for two-dimensional binary compounds: Energetic stability
versus synthesizability of three-dimensional counterparts
S. Ono and H. Satomi, Phys. Rev. B 103, L121403 (2021).
DOI:10.1103/PhysRevB.103.L121403

5.

Lattice stability of ordered Au-Cu alloys in the warm dense matter regime
S. Ono and D. Kobayashi, Phys. Rev. B 103, 094114 (2021).
DOI:10.1103/PhysRevB.103.094114

ONO, Tomoya [ C class; 9400 (B), 1450 (C) ] (54)
— Development of ﬁrst-principles electronic-structure and transport calculation code RSPACE and simulations for device
1. Calculation of the Green’s function in scattering region for ﬁrst-principles electron-transport simulations
Y. Egami, S. Tsukamoto, and T. Ono, Phys. Rev. Research 3 (2021) 013038.
2.

Ising ferromagnetism and robust half-metallicity in two-dimensional honeycomb-kagome Cr2 O3
layer
A. Hashmi, K. Nakanishi, M. U. Farooq, and T. Ono, npj 2D Materials and Applications 4 (2020)
39.

ORIMOTO, Yuuichi [ C class; 400 (B), 100 (C) ] (177)— Elucidation of the mechanism of self-ordering phenomena at the interface between organic and inorganic materials
1. Microscopic Hopping Mechanism of an Isolated PTCDA Molecule on a Reactive Ge(001) Surface
T. Shiota, W. Mizukami, H. Tochihara, K. Yagyu, T. Suzuki, and Y. Aoki, J. Phys. Chem. C.
124, 24704 (2020).
DOI:10.1021/acs.jpcc.0c05858

OSHIKAWA, Masaki [ B class; 800 (B), 100 (C) ] (285)— An exploration of the topological phase transition driven by Z2 vortex with Tensor Network Renormalization— An exploration of the topological phase transition driven by Z2 vortices with Tensor Network Renormalization
OSHIYAMA, Atsushi [ E class; 17500 (B), 2950 (C) ] (49)
— Mechanisms of Semiconductor Interface Formation and its Electronic Properties based on Quantum
Theory1. Density-Functional Calculations for Structures and Energetics of Atomic Steps and their Implication for Surface Morphology on Si-face SiC Polar Surfaces
K. Seino and A. Oshiyama, Phys. Rev. B 101 (2020) 195307
DOI:10.1103/PhysRevB.101.195307
2.

Absence of oxygen-vacancy-related deep levels in amorphous (Al2 O3 )1−x (SiO2 )x : First-principles
exploration of gate oxides in GaN-based devices
K. Chokawa, T. Narita, D. Kikuta, T. Kachi, K. Shiozaki, A. Oshiyama and K. Shiraishi, Phys.
Rev. Applied 14 (2020) 014034

384

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DOI:10.1103/PhysRevApplied.14.014034
3.

Screw dislocation that converts p-type GaN to n-type: Microscopic study on Mg condensationand leakagae current in p-n diodes
T. Nakano, Y. Harashima, K. Chokawa, K. Shiraishi, A. Oshiyama, Y. Kangawa, S. Usami, N.
Mayama, K. Toda, A. Tanaka, Y. Honda, and H. Amano, Appl. Phys. Lett. 117 (2020) 012105
DOI:10.1063/5.0010664

4.

Gallium-gallium weak bond that incorporates nitrogen at atomic steps during GaN epitaxial
growthK. M. Bui, K. Shiraishi and A. Oshiyama, Appl. Surf. Sci. 557 (2021) 149542
DOI:10.1016/j.apsusc.2021.149542

OZEKI, Yukiyasu [ C class; 4400 (B), 0 (C) ] (260)— Dynamical scaling analysis for phase transitions and critical phenomena in frustrated systems— Dynamical scaling analysis for phase transitions and critical phenomena in frustrated systems II
1. Dynamical scaling analysis of symmetry breaking for the antiferromagnetic triangular Heisenberg
model in a uniform ﬁeld
K. Murayama and Y. Ozeki Phys. Rev B 101 (2020) 184427.

RAEBIGER, Hannes [ C class; 3600 (B), 0 (C) ] (103)— First principles calculation of ﬂuorocarbon layer in dry etching process— First principles theory of exciton self-trapping in low-dimensional perovskites
1. MXene phase with C3 structure unit: a family of 2D electrides
S. Bae, W. Espinosa-Garcı́a, Y.-G. Kang, N. Egawa, J. Lee, K. Kuwahata, M. Khazaei, K. Ohno,
Y.-H. Kim, M. J. Han, H. Hosono, G. M. Dalpian, and H. Raebiger, Adv. Funct. Mater. in press(2021).
DOI:10.1002/adfm.202100009
2.

Electronic and magnetic properties of carbide MXenes—the role of electron correlations
S. Bae, Y.-G. Kang, M. Khazaei, K. Ohno, Y.-H. Kim, M. J. Han, K.J. Chan, and H. Raebiger,
Mater. Today Adv. 9 100118 (2021).
DOI:10.1016/j.mtadv.2020.100118

3.

Electronic mechanism for resistive Switching in metal/insulator/metal nanodevices
H. Raebiger, A. C. M. Padilha, A. R. Rocha, and G. M. Dalpian Journal of Physics D: Applied
Physics 53 295302 (2020).
DOI:10.1088/1361-6463/ab7a58

SAITO, Mineo [ C class; 4200 (B), 800 (C) ] (88)
— Band structure calculation based on the group theory
1. Electronic structure of puckered group IV?VI two-dimensional monolayer materials
A. Zaharo, A. Purqon, T. Winata, and M. Saito, Jpn. J. Appl. Phys. 59, 071006 (2020) .
DOI:10.35848/1347-4065/ab984c
2.

Spin-polarized cation monovacancies in wurtzite structure semiconductors: ﬁrst-principles study
M. Y. H. Widianto, H. P. Kadarisman, A. M. Yatmeidhy, and M. Saito, Jpn. J. Appl. Phys. 59,
071001 (2020) .
DOI:10.35848/1347-4065/ab9654

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

SAKAGUCHI, Norihito [ C class; 5200 (B), 0 (C) ] (84)
— Reduction of Rare Metals in Fuel Cell Catalysts and Hydrogen Permeable Membrane
1. グラフェン担持 Pt サブナノクラスタの酸素還元反応活性長谷川瞬，國貞雄治，坂口紀史表面と真空 63 (2020) 413.
a DOI:10.1380/vss.63.413
2.

Single Pt Atoms on N-Doped Graphene: Atomic Structure and Local Electronic States
R. Sugimoto, Y. Segawa, A. Suzuta, Y. Kunisada, T. Uchida, K. Yamazaki, K. Gohara J. Phys.
Chem. C 125 (2021) 2900.
DOI:10.1021/acs.jpcc.0c08811

SAKAI, Masatoshi [ B class; 300 (B), 50 (C) ] (217)— Field-induced metal-insulator transition in organic charge order phase
SAKAI, Toru [ C class; 4200 (B), 750 (C) ] (248, 249)
— Numerical Diagonalization Study on the Field-Induced Spin Nematic Liquid— Symmetry Protected Topological Phase of the S=2 antiferromagnetic chain
1. Spin Nematic Liquids of the S = 1 Spin Ladder in Magnetic Field
T. Sakai and K. Okamoto, JPS Conf. Proc. 30 (2020) 011083/1-62.

Ground-State Phase Diagram of an Anisotropic S = 1 Ferromagnetic-Antiferromagnetic BondAlternating Chain
K. Okamoto, T. Tonegawa, M. Kaburagi and T. Sakai, JPS Conf. Proc. 30 (2020) 011024/1-6

3.

Quantum Phase Transition of the Twisted Spin Tube
Y. Tachibana, Y. Ueno, T. Zenda, K. Okamoto and T. Sakai,
011082/1-5

JPS Conf. Proc. 30 (2020)

4.

Quantum Phase Transitions of the Distorted Diamond Spin Chain
T. Zenda, Y. Tachibana, Y. Ueno, K. Okamoto and T. Sakai, JPS Conf. Proc. 30 (2020)
011084/1-5

5.

Magnetization Plateau of the Distorted Diamond Spin Chain
Y. Ueno, T. Zenda, Y. Tachibana, K. Okamoto and T. Sakai,
011085/1-5

JPS Conf. Proc. 30 (2020)

6.

Features of Chirality Generated by Paramagnetic Coupling to Magnetic Fields in the 3K-Phaseof Sr2 RuO4
H. Kaneyasu, Y. Enokida, T. Nomura, Y. Hasegawa, T. Sakai and M. Sigrist, JPS Conf. Proc.
30 (2020) 011039/1-6

7.

EPR Theories for Selection Rules to Observe the Spin Gap
T. Sakai, Applied Magnetic Resonance 52, 507 (2021).
DOI:10.1007/s00723-020-01298-8

8.

Quantum spin nematic liquid in the S=1 antiferromagnetic chain with the biquadratic interaction
T. Sakai, AIP Advances 11 (2021) 015306/1-4.

SAKAKIBARA, Hirofumi [ B class; 800 (B), 150 (C) ] (156)— First-principles derivation of a many-body eﬀective model based on PMT basis— First-principles derivation of a many-body eﬀective model based on a new basis PMT
1. Finite electric-ﬁeld approach to evaluate the vertex correction for the screened Coulomb interactionin the quasiparticle self-consistent GW method386

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

H. Sakakibara, T. Kotani, M. Obata, and T. Oda, Phys. Phys. B 101 205120 (2020).
2.

Model Construction and a Possibility of Cupratelike Pairing in a New d9 Nickelate Superconductor(Nd,Sr)NiO2
H. Sakakibara, H. Usui, K. Suzuki, T. Kotani, H. Aoki, and K. Kuroki, Phys. Phys. Lett. 125
077003 (2020).

SAKASHITA, Tatsuya [ B class; 100 (B), 150 (C) ] (322)— Development of integrated interface of eigensolvers Rokko and application to quantum spin systems
SAKURAI, Masahiro [ B class; 400 (B), 50 (C) ] ()— First-principles KKR calculations for evaluating magnetic properties
SASAKI, Takehiko [ C class; 2800 (B), 600 (C) ] (107)— Reaction processes of polyalcohols in high temperature water by First Principles Calculations— Study on cyclodehydration of sorbitol in hot water by First Principles calculations
1. Reﬁned metadynamics through canonical sampling using time-invariant bias potential: A studyof polyalcohol dehydration in hot acidic solutions
T. Kondo, T. Sasaki, S. Ruiz-Barragan, J. Ribas-Arino, M. Shiga, J. Comput. Chem. 42, 156(2020).
DOI:10.1002/jcc.26443

SATO, Taku [ B class; 400 (B), 50 (C) ] ()— Magnetic excitations in the quantum pyrochlore magnet
SATO, Tetsuya [ C class; 5600 (B), 850 (C) ] (73)
— Study of ferromagnetism in Pt(100) thin ﬁlms by ﬁrst-principles calculation
1. Appearance of ferromagnetism in Pt(100) ultrathin ﬁlms originated from quantum-well stateswith small orbital magnetic moment
T.Yamada, K. Ochiai, H. Kinoshita, S. Sakuragi, M. suzuki, H. Ozawa, H. Kageshima, T. Sato,
submitted to Phys. Rev. B

SHAO, Cheng [ C class; 5200 (B), 900 (C) ] ()— Coupled electron-phonon transport at metal-insulator interface— Phonon engineering in PbS quantum dot ligand system
SHIMADA, Toshihiro [ B class; 800 (B), 150 (C) ] (155)— Analysis of reaction and prediction of properties of atomic layer materials— Carbonization reaction and electronic structures of molecular crystals under high temperature highpressure conditions
1. DFT Calculation of Square MoS2 Nanotubes
Meiqi Zhang, Mengting Weng, Takahiro Tamura, Manami Goto, Ichiro Yamane, Takashi Yanase,Taro Nagahama, Toshihiro Shimada , Physica E 130, 114693 (2021)
DOI:10.1016/j.physe.2021.114693
2.

Porous Graphitic Carbon Nitride Nanoplates Obtained by A Combined Exfoliation Strategy for
Enhanced Visible Light Photocatalytic Activity
Wei Liu, Nobuhiro Iwasa, Shinichiro Fujita, Hitoshi Koizumi, Makoto Yamaguchi and Toshihiro
Shimada , Applied Surface Science 499,143901 (2020).
DOI:10.1016/j.apsusc.2019.143901

387

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoSHIMAMURA, Kohei [ C class; 2600 (B), 800 (C) ] (106)— Study of Eﬃcient Training Data Generation Method for Constructing Artiﬁcial Neural Network Force
Field— Study of Eﬃcient Training Data Generation Method for Constructing Artiﬁcial Neural Network Force
Field II
1. Computational and Training Requirements for Interatomic Potential Based on Artiﬁcial Neural
Network for Estimating Low Thermal Conductivity of Silver Chalcogenides
K. Shimamura, Y. Takeshita, S. Fukushima, A. Koura, and F. Shimojo, J. Chem. Phys. 153(2020) 234301.

SHIMOJO, Fuyuki [ C class; 7600 (B), 1150 (C) ] (60)— First-Principles Molecular-Dynamics Study of Structural and Electronic Properties of Covalent Liquids and Glasses under Pressure
1. Intermediate range structure of amorphous Cu2 GeTe3 : ab initio molecular dynamics study
A. Koura and F. Shimojo, J. Phys.: Condens. Matter 32, 244001 (2020)
DOI:10.1088/1361-648X/ab7b1b2.

Structures of liquid iron-light-element mixtures under high pressure
S. Ohmura, T. Tsuchiya, and F. Shimojo, Phys. Stat. Solidi B 257, 2000098 (2020)
DOI:10.1002/pssb.202000098

3.

Application of First-Principles-Based Artiﬁcial Neural Network Potentials to Multiscale-ShockDynamics Simulations on Solid Materials
M. Misawa, S. Fukushima, A. Koura, F. Shimojo, K. Shimamura, S. Tiwari, K. Nomura, R. K.
Kalia, A. Nakano, and P. Vashishta, J. Phys. Chem. Lett. 11, 4536 (2020)
DOI:10.1021/acs.jpclett.0c00637

4.

Molecular-Dynamics Study of Thermal Conductivity of Silver Chalcogenides
S. Fukushima, K. Shimamura, A. Koura, and F. Shimojo, Phys. Stat. Solidi B 257, 2000183(2020)
DOI:10.1002/pssb.202000183

5.

First-Principles Study of Pressure-Induced Amorphization of Fe2 SiO4 Fayalite
M. Misawa and F. Shimojo, Phys. Stat. Solidi B 257, 2000173 (2020)
DOI:10.1002/pssb.202000173

6.

Computational and training requirements for interatomic potential based on artiﬁcial neural network for estimating low thermal conductivity of silver chalcogenides
K. Shimamura, Y. Takeshita, S. Fukushima, A. Koura, and F. Shimojo, J. Chem. Phys. 153,
234301 (2020)
DOI:10.1063/5.0027058

SHIMOKAWA, Tokuro [ C class; 2800 (B), 500 (C) ] (265)— Thermal eﬀects on quantum frustrated magnetisms
1. Signatures of ﬁnite-temperature mirror symmetry breaking in the S=1/2 Shastry-Sutherland
model
T. Shimokawa, Phys. Rev. B 103, 134419 (2020).
DOI:10.1103/PhysRevB.103.134419

SHINAOKA, Hiroshi [ B,C class; 2300 (B), 350 (C) ] (205, 206)
— Classical Monte Carlo study of J1-J2 Heisenberg antiferromagnet on the kagome lattice— Development and application of DFT+DMFT software DCore

388

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1.

Sparse modeling of large-scale quantum impurity models with low symmetries
H. Shinaoka and Y. Nagai, Phys. Rev. B 103, 045120
DOI:10.1103/PhysRevB.103.045120

2.

DCore: Integrated DMFT software for correlated electrons
H. Shinaoka, J. Otsuki, M. Kawamura, N. Takemori, K. Yoshimi, submitted to SciPost Phys.

SHINODA, Wataru [ E class; 21000 (B), 2250 (C) ] (223)— Molecular Simulation of Soft Materials using All-Atom and Coarse-Grained Force Field
1. pSPICA: A coarse-grained force ﬁeld for lipid membranes based on a polar water model
Y. Miyazaki, S. Okazaki, W. Shinoda, J. Chem. Theory Comput. 16, 782-793 (2020)
DOI:10.1021/acs.jctc.9b00946
2.

Monodisperse Polymer Melts Crystallize via Structurally Polydisperse Nanoscale Clusters: Insights from Polyethylene
K. W. Hall, T. W. Sirk, S. Percec, M. L. Klein, W. Shinoda Polymers, 12, 447 (2020)
DOI:10.3390/polym12020447

3.

Eﬀects of anion on liquid structures of ionic liquids at graphene electrode interface analyzed bymolecular dynamics simulations
S. Tsuzuki, T. Nakamura, T. Morishita, W. Shinoda, S. Seki, Y. Umebayashi, K. Ueno, K. Dokko,
M. Watanabe Batteries & Supercaps, 3, 658-667 (2020)
DOI:10.1002/batt.201900197

4.

Molecular Simulation of the Shape Deformation of a Polymersome
K. Chakraborty, W. Shinoda, S. M. Loverde Soft Matter, 16, 3234-3244 (2020)
DOI:10.1039/C9SM02165E

5.

Free energy proﬁle of permeation of Entecavir through Hepatitis B virus capsid studied by molecular dynamics calculation
K. Fujimoto, M. Fukai, R. Urano, W. Shinoda, T. Ishikawa, K. Omagari, Y. Tanaka, A. Nakagawa, S. Okazaki, Pure Appl. Chem. 92, 1585-1594 (2020)
DOI:10.1515/pac-2020-0109

6.

Property Decoupling across the Embryonic Nucleus-Melt Interface during Polymer Crystal Nucleation
K. W. Hall, S. Percec, W. Shinoda, M. L. Klein J. Phys. Chem. B, 124, 4793-4804 (2020)
DOI:10.1021/acs.jpcb.0c01972

7.

Eﬀect of Packing Density on the Surface Hydrophobicity of ω-Functionalized (–CF3, –CH3, –OCH3, and –OH) Self-assembled Monolayers: A Molecular Dynamics Study
H. Yadav, A. Kuo, S. Urata, W. Shinoda, J. Phys. Chem. C, 124, 14237-14244 (2020)
DOI:10.1021/acs.jpcc.0c03485

8.

脂質膜系の粗視化力場 SPICA の開発とその展望
W. Shinoda 生物物理, 60, 157-161 (2020)
DOI:10.2142/biophys.60.157

9.

Exact Long-Range Coulombic Energy Calculation for Net Charged Systems Neutralized by Uniformly Distributed Background Charge Using Fast Multipole Method and Its Application to Efﬁcient Free Energy Calculation
R. Urano, W. Shinoda, N. Yoshii, S. Okazaki, J. Chem. Phys. 152, 244115 (2020)
DOI:10.1063/5.0007957

389

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

10. Pivotal Role of Interdigitation in Interleaﬂet Interactions: Implications from Molecular Dynamics
Simulations
S. Seo, M. Murata, W. Shinoda, J. Phys. Chem. Lett. 11, 5171-5176 (2020)
DOI:10.1021/acs.jpclett.0c01317
11. Conformation and orientation of branched acyl chains responsible for the physical stability of
diphytanoylphosphatidylcholine
H. Tsuchikawa, T. Ono, M. Yamagami, Y. Umegawa, W. Shinoda, M. Murata, Biochemistry, 59,3929-3938 (2020)
DOI:10.1021/acs.biochem.0c00589
12. Position-Dependent Diﬀusion Constant of Molecules in Heterogeneous Systems as Evaluated by
the Local Mean Squared Displacement
T. Nagai, S. Tsurumaki, R. Urano, K. Fujimoto, W. Shinoda, S. Okazaki, J. Chem. Theory
Comput. 16, 7239-7254 (2020)
DOI:10.1021/acs.jctc.0c00448
13. Thermodynamic aspect of sulfur, polysulﬁde anion and lithium polysulﬁde: plausible reaction
path during discharge of lithium–sulfur battery
S. Tsuzuki, T. Kaneko, K. Sodeyama, Y. Umebayashi, W. Shinoda, S. Seki, K. Ueno, K. Dokko,
M. Watanabe, Phys. Chem. Chem. Phys. 23, 6832-6840 (2021)
DOI:10.1039/D0CP04898D
14. Chain-End Modiﬁcation: A Starting Point for Controlling Polymer Crystal Nucleation
K. W. Hall, S. Percec, W. Shinoda, M. L. Klein Macromolecules, 54, 1599-1610 (2021)
DOI:10.1021/acs.macromol.0c02398
15. Seipin accumulates and traps diacylglycerols and triglycerides in its ring-like structure
V. Zoni, R. Khaddaj, I. Lukmantara, W. Shinoda, H. Yang, R. Schneiter, S. Vanni Proc. Natl.
Acad. Sci. U.S.A. 118, e2017205118 (2021)
DOI:10.1073/pnas.2017205118
16. Hemimicelle formation of semi-ﬂuorocarbon chains at air–water interface: coarse-grained molecular dynamics study with an extension of the SPICA force ﬁeld
H. O. S. Yadav, S. Harada, A. Kuo, S. Urata, W. Shinoda, Mol. Phys. e1910355 (2021)
DOI:10.1080/00268976.2021.1910355

SHINOHARA, Yasushi [ C class; 3000 (B), 0 (C) ] (113)— First-principles calculations for light absorption of crystalline solids— First-principles calculations for nonlinear light absorption of insulators
1. Detecting electron-phonon coupling during photoinduced phase transition
Takeshi Suzuki, Yasushi Shinohara, Yangfan Lu, Mari Watanabe, Jiadi Xu, Kenichi L. Ishikawa,
Hide Takagi, Minoru Nohara, Naoyuki Katayama, Hiroshi Sawa, Masami Fujisawa, Teruto Kanai,
Jiro Itatani, Takashi Mizokawa, Shik Shin, and Kozo Okazaki, Phys. Rev. B 103, L121105(2021).
DOI:10.1103/PhysRevB.103.L121105

SHIOMI, Junichiro [ C class; 7200 (B), 1100 (C) ] (232)— Development of Thermal Functional Materials Using Materials Informatics
1. Phonon transport in multiphase nanostructured silicon fabricated by high-pressure torsion
C. Shao, K. Matsuda, S. Ju, Y. Ikoma, M. Kohno, and J. Shiomi, J. Appl. Phys. 129, 085101(2021).
DOI:10.1063/5.0037775

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2.

Scalable monolayer-functionalized nanointerface for thermal conductivity enhancement in copper/diamond composite
B. Xu, S-W. Hung, S. Hu, C. Shao, R. Guo, J. Choi, T. Kodama, F-R. Chen, and J. Shiomi
Carbon, 175, 299-306 (2021).
DOI:10.1016/j.carbon.2021.01.018

3.

Ultimate impedance of coherent heat conduction in van der Waals graphene-MoS2 heterostructures
S. Hu, S. Ju, J. Guo, B. Xu, M. Ohnishi, and J. Shiomi, Mater. Today Phys. 16, 100324 (2021).
DOI:10.1016/j.mtphys.2020.100324

4.

Designing thermal functional materials by coupling thermal transport calculations and machinelearning
Shenghong Ju, Shuntaro Shimizu, Junichiro Shiomi Journal of Applied Physics, 128, 161102(2020).
DOI:10.1063/5.0017042

5.

Revisiting thermal conductivity and interface conductance at the nanoscale
B. Davier, P Dollfus, S. Volz, J. Shiomi, J Saint-Martin , 175, (2020).

6.

Modulation of Interfacial Thermal Transport between Fumed Silica Nanoparticles by Surface
Chemical Functionalization for Advanced Thermal Insulation
Takashi Kodama, Nobuhiro Shinohara, Shih-Wei Hung, Masanao Obori, Donguk, Suh, Junichiro
Shiomi ACS Appl. Mater. Interfaces, 13, 15 (2021).
DOI:10.1021/acsami.0c11066

7.

Run Hu, Sotaro Iwamoto, Lei Feng, Shenghong Ju, Shiqian Hu, Masato Ohnishi, Naomi Nagai,
Kazuhiko Hirakawa, Junichiro Shiomi
Machine-learning-optimized aperiodic superlattice minimizes coherent phonon heat conduction
Physical Review X, 10, 2 (2020).
DOI:10.1103/PhysRevX.10.021050

8.

Machine learning analysis of tunnel magnetoresistance of magnetic tunnel junctions with disordered MgAl2O4
Shenghong Ju, Yoshio Miura, Kaoru Yamamoto, Keisuke Masuda, Ken-ichi Uchida, Junichiro
Shiomi Physical Review Research, 2, 023187 (2020).
DOI:10.1103/PhysRevResearch.2.023187

9.

Two-Path Phonon-Interference Resonance Induces a Stop Band in Silicon Crystal Matrix byEmbedded Nanoparticles Array
Shiqian Hu, Lei Feng, Shao Cheng, Yuriy Kosevich, Junichiro Shiomi Physical Review B, 102,024301 (2020).
DOI:10.1103/PhysRevB.102.024301

10. Design of highly-selective radiative-cooling structure accelerated by materials informatics
Jiang Guo, Shenghong Ju, Junichiro Shiomi Optics Letters, 45, 343 (2020).
DOI:10.1364/OL.45.000343

SHIRAI, Tatsuhiko [ B class; 700 (B), 0 (C) ] (297, 298)
— Quantum annealing with inhomogeneous ﬂuctuations— Universal properties of non-equilibrium steady states
1. Resolving a Discrepancy between Liouvillian Gap and Relaxation Time in Boundary-DissipatedQuantum Many-Body Systems
T. Mori and T. Shirai, Phys. Rev. Lett. 125 (2020) 230604.

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DOI:10.1103/PhysRevLett.125.230604
2.

Thermalization in open many-body systems based on eigenstate thermalization hypothesis
T. Shirai and T. Mori, Phys. Rev. E 101 (2020) 042116.
DOI:10.1103/PhysRevE.101.042116

3.

Guiding Principle for Minor-Embedding in Simulated-Annealing-Based Ising Machines
T. Shirai, S. Tanaka, and N. Togawa, IEEE Access 8 (2020), 210490
DOI:10.1109/ACCESS.2020.3040017

4.

Tensor-network approach to thermalization in open quantum many-body systems
H. Nakano, T. Shirai, and T. Mori, Phys. Rev. E, in press.

5.

Exact bounds for dynamical critical exponents of transverse-ﬁeld Ising chains with a correlateddisorderT. Shirai, and S. Tanaka, submitted to Annals of Physics

SHIRAISHI, Kenji [ C class; 6600 (B), 1050 (C) ] (66, 67)— First Principles Studies on Atomic and Electronic Structures of Impurity-screw dislocation complexes
in Gan— Theoretical Studies on Semiconductor MOVPE Growth Based on Multi-Physics Simulation
1. Screw dislocation that converts p-type GaN to n-type: Microscopic study on Mg condensationand leakage current in p-n diodes
T. Nakano, Y. Harashima, K. Chokawa, K. Shiraishi, A. Oshiyama, Y. Kangawa, S. Usami, N.
Mayama, K. Toda, A. Tanaka, Y. Honda, and H. Amano, Appl. Phys. Lett. 117, 012105 (2020).
DOI:10.1063/5.0010664
2.

Theoretical study on the eﬀect of H2 and NH3 on trimethylgallium decomposition process in GaN
MOVPE
S. Sakakibara, K. Chokawa, M. Araidai, A. Kusaba, Y. Kangawa, and K. Shiraishi, Jpn. J. Appl.
Phys. 60, 045507 (2021).

SHUDO, Ken-ichi [ C class; 1000 (B), 400 (C) ] (139, 140)
— Optical gaps of metastable Ga2O3 and GaN with impurity doping eﬀect— Optical gaps of metastable Ga2O3 structures modulated by impurity dope
1. Modulation of the optical absorption edge of ϵ- and κ-Ga2 O3 due to Co impurities caused by band
structure changes: Work function measurements and ﬁrst-principle calculations
K. Yamanaka, H. Raebiger, K. Mukai and K. Shudo, J. Appl. Phys. 127, 065701/1-9 (2020).
DOI:10.1063/1.5134521

SUGINO, Osamu [ E class; 21000 (B), 4150 (C) ] (48)
— Simulation of electrochemical interfaces— Computational hydrogenomics
1. Dopant arrangements in Y-doped BaZrO3 under processing conditions and their impact on proton
conduction: a large-scale ﬁrst-principles thermodynamics study
Shusuke Kasamatsu, Osamu Sugino, Takafumi Ogawa, and Akihide Kuwabara, J. Mater. Chem.
A 8, 12674-12686 (2020).
DOI:10.1039/D0TA01741H
2.

Quantum-Mechanical Hydration Plays Critical Role in the Stability of Fireﬂy Oxyluciferin Isomers: State-of-the-art Calculations of the Excited States
Y. Noguchi, M. Hiyama, M. Shiga, H. Akiyama, O. Sugino, J. Chem. Phys. (2020) 153, 201103

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DOI:10.1063/5.0031356
3.

Advances and challenges for experiment and theory for multi-electron multi-proton transfer at
electriﬁed solid-liquid interfaces
K. Sakaushi, T. Komeda, S. Hammes-Schiﬀer, M. M. Melander and O. Sugino Phys. Chem.
Chem. Phys. 22, 19401-19442 (2021).
DOI:10.1039/d0cp02741c

4.

Hydrogen at Electrochemical Interfaces
O. Sugino J. Phys. Soc. Jpn. 89, 051013 (2020).
DOI:10.7566/JPSJ.89.051013

5.

Surface-state Coulomb repulsion accelerates a metal-insulator transition in topological semimetal
nanoﬁlms
S. Ito, M. Arita, J. Haruyama, B. Feng, W. -C. Chen, H. Namatame, M. Taniguchi, C. -M. Cheng,
G. Bian, S. -J. Tang, T. -C. Chiang, O. Sugino, F. Komori and I. Matsuda Science Advances 6,
eaaz5015 (2020).
DOI:10.1126/sciadv.aaz5015

6.

Challenge of advanced low temperature fuel cells based on high degree of freedom of group 4 and5 metal oxides
A. Ishihara, S. Tominaka, S. Mitsushima, H. Imai, O. Sugino and K.-I. Ota Curr. Op. ElectroChem.
DOI:10.1016/j.coelec.2020.03.005

7.

Completing density functional theory by machine learning hidden messages from molecules
R. Nagai, R. Akashi and O. Sugino npj Comput. Mater. 6, 43 (2020).
DOI:10.1038/s41524-020-0310-0

8.

First-Principles Calculation of Copper Oxide Superconductors That Supports the KamimuraSuwa Model
H. Kamimura, M. Araidai, K. Ishida, S. Matsuno, H. Sakata, K. Shiraishi, O. Sugino and J.-S.
Tsai Condensed Matter 5, 69 (2020).
DOI:10.3390/condmat5040069

SUWA, Hidemaro [ C class; 7800 (B), 550 (C) ] (231)— Giant magnetic response of hidden SU(2) symmetric antiferromagnets induced by impurity disorder— Impurity eﬀect on giant magnetic response of a two-dimensional antiferromagnet
SUZUKI, Takafumi [ C class; 4200 (B), 650 (C) ] (250)— Ground state phase diagram of extended Kitaev model II— Ground-state phase diagram of extended Kitaev model on a honeycomb lattice
1. Ground-state properties of the K–Γ model on a honeycomb lattice
Takuto Yamada, Takafumi Suzuki and Seiichiro Suga, Phys. Rev. B 102, 024415 (2020).
DOI:10.1103/physrevb.102.024415
2.

Frustration-induced supersolid phases of extended Bose-Hubbard model in the hard-core limit
Wei-Lin Tu, Huan-Kuang Wu and Takafumi Suzuki J. Phys: Condens. Matter 32, 455401 (2020).
DOI:10.1088/1361-648x/aba383

SUZUKI, Yuji [ C class; 3600 (B), 0 (C) ] (101)— Development of High-performance Polymer Electret Using Quantum Chemical Analysis— Development of High-performance Polymer Electret with the Aid of Machine Learning

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1.

Solid-state Electron Aﬃnity Analysis of Amorphous Fluorinated Polymer Electret
Kim, S., Melnyk, A., Andrienko, D., and Suzuki, Y., J. Phys. Chem. B, 124, 46, 10507-10513(2020)

2.

Investigation of Amorphous Fluorinated Polymer for Bipolar Electret Based on Solid-state Quantum Chemical Analysis
Mao, Z., Zhang, Y., Suzuki, K., and Suzuki, Y. 電気学会誘電・絶縁材料研究会, DEI-20-090 (2020).

TAKAHASHI, Osamu [ C class; 200 (B), 250 (C) ] (179)— Electronic state of organic compounds in aqueous solution
1. Sub-molecular structural relaxation at physisorbed van der Waals interface with monolayer organic single crystal semiconductors
A. Yamamura, H. Fujii, H. Ogasawara, D. Nordlund, O. Takahashi, Y. Kishi, H. Ishii, N. Kobayashi,
N. Niitsu, B. Blülle, T. Okamoto, Y. Wakabayashi, S. Watanabe, J. Takeya Communications
Physics, 3(1), 20/1-8 (2020)
2.

Site-speciﬁcity reduction during Auger decay following Si:2p photoionization in Cl3SiSi(CH3)3
vapor: Interatomic-Coulombic-decay-like process
S. Nagaoka, O. Takahashi, Y. Hikosaka Chem. Phys. 534, 110756/1-7 (2020)

3.

Soft X-ray Absorption Spectroscopy Probes OH-π Interactions in Complex Polymer Systems
H. Yamane, M. Oura, O. Takahashi, P. Fons, P. R. Varadwaj, Y. Shimoi, M. Ohkubo, T. Ishikawa,N. Yamazaki, K. Hasegawa, K. Takagi, T. Hatsui J. Phys. Chem. C 124, 9622-9627 (2020)

4.

Dissociation and ionization dynamics of CF3I and CH3I molecules via pump and probe experiments with using soft X-ray free-electron laser
T. Gejo, T. Nishie, T. Nagayasu, K. Tanaka, Y. Tanaka, A. Niozu, K. Nagaya, R. Yamamura, N.
Futamata, T. Suenaga, O. Takahashi, T. Togashi, S. Owada, H. Fujise, A. Verna, M. Yabashi, M.
Oura J. Phys. B, in press

5.

Photoemission from the gas phase using soft x-ray fs pulses: An investigation of the space-charge
eﬀects
A. Verna, G. Stefani, F. Oﬃ, T. Gejo, Y. Tanaka, K. Tanaka, T. Nishie, K. Nagaya, A. Niozu, R.
Yamamura, T. Suenaga, O. Takahashi, H. Fujise, T. Togashi, M. Yabashi, M. Oura New J Phys.
22, 123029/1-13 (2020)

6.

Fragmentation pathways of methylbenzoate cations following core excitation: theoretical approach
using graph theory
N. Futamata, R. Yamamura; D. T. Ha, O. Takahashi Chem. Phys. Lett. 766, 138316/1-6 (2021)

TAMURA, Ryo [ B class; 500 (B), 100 (C) ] (301, 343)
— Eﬀective model estimation with error bars
1. Data Integration for Accelerated Materials Design via Preference Learning
X. Sun, Z. Hou, M. Sumita, S. Ishihara, R. Tamura, and K. Tsuda New Journal of Physics 22(2020) 055001.
2.

Experimental Establishment of Phase Diagrams Guided by Uncertainty Sampling: An Application
to the Deposition of Zn–Sn–P Films by Molecular Beam Epitaxy
R. Katsube, K. Terayama, R. Tamura, and Yoshitaro Nose ACS Materials Letters 2 (2020) 571.

3.

Optimization of Heterogeneous Ternary Li3PO4-Li3BO3-Li2SO4 Mixture for Li-ion Conductivity
by Machine Learning
K. Homma, Y. Liu, M. Sumita, R. Tamura, N. Fushimi, J. Iwata, K. Tsuda, and C. Kaneta The

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Journal of Physical Chemistry C 124 (2020) 12865.
4.

Pushing property limits in materials discovery via boundless objective-free exploration
K. Terayama, M. Sumita, R. Tamura, D. T. Payne, M. K. Chahal, S. Ishihara, and K. Tsuda
Chemical Science 11 (2020) 5959.

5.

Data-driven determination of a spin Hamiltonian of KCu4 P3 O12 with uncertainty
R. Tamura, K. Hukushima, A. Matsuo, K. Kindo, and M. Hase, Physical Review B 101 (2020)
224435.

6.

Materials informatics approach to understand aluminum alloys
R. Tamura, M. Watanabe, H. Mamiya, K. Washio, M. Yano, K. Danno, A. Kato, and T. Shoji
Science and Technology of Advanced Materials 21 (2020) 540.

7.

Dynamic Observation and Theoretical Analysis of Initial O2 Molecule Adsorption on Polar andm-Plane Surfaces of GaN
M. Sumiya, M. Sumita, Y. Asai, R. Tamura, A. Uedono, and A. Yoshigoe The Journal of Physical
Chemistry C 124 (2020) 25282.

8.

Machine learning-driven optimization in powder manufacturing of Ni-Co based superalloy
R. Tamura, T. Osada, K. Minagawa, T. Kohata, M. Hirosawa, K. Tsuda, and K. Kawagishi
Materials & Design 198 (2021) 109290.

9.

Mechanomics Biomarker for Cancer Cells Unidentiﬁable through Morphology and Elastic Modulus
H. Wang, H. Zhang, B. Da, D. Lu, R. Tamura, K. Goto, I. Watanabe, D. Fujita, N. Hanagata,
J. Kano, T. Nakagawa, and M. Noguchi Nano Letters 21 (2021) 1538.

10. Black-Box Optimization for Automated Discovery
K. Terayama, M. Sumita, R. Tamura, and K. Tsuda Accounts of Chemical Research 54 (2021)
1334.

TANAKA, Shu [ B class; 400 (B), 100 (C) ] (310)
Building Algorithms for Ising Machines
1. Guiding Principle for Minor-Embedding in Simulated-Annealing-Based Ising Machines
T. Shirai, S. Tanaka, and N. Togawa, IEEE Access 8 210490 (2020).
2.

How to Reduce the Bit-width of an Ising Model by Adding Auxiliary Spins
D. Oku, M. Tawada, S. Tanaka, and N. Togawa to appear in IEEE Transactions on Computers.

3.

Solving Constrained Slot Placement Problems Using an Ising Machine and Its Evaluations
S. Kanamaru, K. Kawamura, S. Tanaka, Y. Tomita, and N. Togawa IEICE Transactions on
Information and Systems 104 226 (2021).

4.

PyQUBO: Python Library for Mapping Combinatorial Optimization Problems to QUBO Form
M. Zaman, K. Tanahashi, and S. Tanaka to appear in IEEE Transactions on Computers.

5.

Exact bounds for dynamical critical exponents of transverse-ﬁeld Ising chains with a correlateddisorderT. Shirai and S. Tanaka, Annals of Physics, Accepted.

6.

Mapping Induced Subgraph Isomorphism Problems to Ising Models and Its Evaluations by an
Ising Machine
N. Yoshimura, M. Tawada, S. Tanaka, J. Arai, S. Yagi, H. Uchiyama, and N. Togawa IEICE
Transactions on Information and Systems 104 481 (2021).

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

TANAMOTO, Tetsufumi [ B class; 200 (B), 50 (C) ] (321)— All to all connections in two dimensional qubit array with two-body interactions aiming at quantum
annealing machine
1. Robustness of cluster states and surface code states against random local ﬁelds
T. Tanamoto, M. Ueda, arXiv:1910.05649
2.

Generation of all-to-all connections in a two-dimensional qubit array with two-body interactions
T. Tanamoto Journal of Applied Physics 129 (1), 014307 (2021)
DOI:10.1063/5.0033173

TATENO, Michio [ B class; 700 (B), 0 (C) ] (293, 295)
— Coarsening mechanism in mass-conserved reaction diﬀusion systems— Multicellular simulation by phase ﬁeld method
1. Power-law coarsening in network-forming phase separation governed by mechanical relaxation
M. Tateno and H. Tanaka, Nat. Commun. 12 (2021) 1.
DOI:10.1038/s41467-020-20734-8
2.

Interfacial-curvature-driven coarsening in mass-conserved reaction-diﬀusion systems
M. Tateno and S. Ishihara, Phys. Rev. Res. under review.

TATETSU, Yasutomi [ C class; 4600 (B), 850 (C) ] (81)— First-principles study on grain boundaries in Ga-doped permanent magnets— First-principles study on grain boundaries with multiple subphases in permanent magnets
1. First-principles study on magnetism of a crystalline grain-boundary phase in Nd–Fe–B permanent
magnets
Y. Ainai, K. Sonju, Y. Tatetsu, and Y. Gohda, Jpn. J. Appl. Phys. 59 (2020) 060904.

TERAO, Takamichi [ B class; 600 (B), 150 (C) ] (290)— Molecular simulation of colloidal particles
1. Wave propagation in double-negative acoustic metamaterial multilayers
T. Terao, Proceedings of 14th international congress on artiﬁcial materials for novel wave phenomena (2020), in press.
2.

Anomalous microion distribution of concentrated electrolytes in the underscreening regime: Monte
Carlo simulations
T. Terao, Mol. Phys. 119, e1831634 (2021).

TERASAWA, Asako [ C class; 1400 (B), 300 (C) ] ()— ﬁrst-principles calculation of exchange coupling constants and investigation of interface magnetism
for various phases and their interfaces of permanent magnets
TODO, Synge [ C class; 5200 (B), 1500 (C) ] (238, 345)
— Topological Order and Quantum Dynamics in Quantum Many-body Systems
1. Anisotropic tensor renormalization group
D. Adachi, T. Okubo, and S. Todo Phys. Rev. B 102, 054432 (7pp) (2020).
DOI:10.1103/PhysRevB.102.054432
2.

Sequential minimal optimization for quantum-classical hybrid algorithms
K. M. Nakanishi, K. Fujii, and S. Todo Phys. Rev. Research 2, 043158 (10pp) (2020)

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Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

DOI:10.1103/PhysRevResearch.2.043158
3.

Multithreaded event-chain Monte Carlo with local times
B. Li, S. Todo, A. C. Maggs, and W. Krauth Comp. Phys. Comm. 261, 107702 (10pp) (2021)
DOI:10.1016/j.cpc.2020.107702

4.

Bond-weighted Tensor Renormalization GroupD. Adachi, T. Okubo, and S. Todo arXiv:2103.00372

5.

Neural Network Approach to Construction of Classical Integrable Systems
F. Ishikawa, H. Suwa, and S. Todo arXiv:2011.01679

TOHYAMA, Takami [ C class; 3800 (B), 550 (C) ] (204)— Time-dependent DMRG study of spectral shape in the optical conductivity of Mott insulators— Time-dependent DMRG study of spectral shape in the optical conductivity of two-dimensional Hubbard
model
1. Characterization of photoexcited states in the half-ﬁlled one-dimensional extended Hubbard modelassisted by machine learning
K. Shinjo, S. Sota, S. Yunoki, and T. Tohyama, Phys. Rev. B 101, (2020) 195136.
2.

Cluster-Based Haldane States in Spin-1/2 Cluster Chains
T. Sugimoto, K. Morita, and T. Tohyama, Phys. Rev. Research 2, (2020) 023420.

3.

Spin dynamics in the t-t′ -J model: Dynamical density-matrix renormalization group study
T. Tohyama, S. Sota, and S. Yunoki, J. Phys. Soc. Jpn. 89, (2020) 124709.

4.

Eﬀect of phase string on single-hole dynamics in the two-leg Hubbard ladder
K. Shinjo, S. Sota, and T. Tohyama, Phys. Rev. B 103, (2021) 035141.

TONEGAWA, Takashi [ B class; 700 (B), 0 (C) ] (291)— Numerical Study of the One-Dimensional Quantum Spin Systems with Spatial Structures
TSUNEYUKI, Shinji [ C class; 6600 (B), 1100 (C) ] (64)
— Development of data assimilation method for crystal structure prediction and its application tohydrogen-containing compounds— Prediction of hydrogen function by advanced calculation of solids containing hydrogen
1. Eﬀect of spin ﬂuctuations on superconductivity in V and Nb: A ﬁrst-principles study
K.Tsutsumi, Y. Hizume, M.Kawamura, R. Akashi, S. Tsuneyuki, Phys. Rev. B 102 (2020)
214515.
DOI:10.1103/PhysRevB.102.214515
2.

実験とシミュレーションのデータ同化に基づく効率的結晶構造決定濱田幾太郎、常行真司 セラミックス 56 (2021) 100.

3.

水素の先端計算による水素機能の高精度解析
常行真司 まてりあ 60 (2021) 176.
DOI:10.2320/materia.60.176

4.

不完全な粉末回折実験データを用いたデータ同化結晶構造探索
常行真司「マテリアルズ・インフォマティクス開発事例最前線」第 3 編第１章第２節 (エヌ・ティー・エス, 2021) 101-109.

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TSURUTA, Kenji [ C class; 1200 (B), 700 (C) ] (134)— Hybrid Ab-Initio/Machine-Learning Optimization of Nano Interfaces and Molecular Structures
1. Characterization of the Σ5(210) / [001] Grain Boundary of Methyl-Ammonium Lead Triiodide
Perovskite using Density Functional Theory
M. A. A. Asad and K. Tsuruta Trans. Mater. Res. Soc. Jpn. 45, 67 (2020).
2.

A mechanistic investigation of moisture-induced degradation of methylammonium lead iodide
M. Hada, M. A. A. Asad, M. Misawa, Y. Hasegawa, R. Nagaoka, H. Suzuki, R. Mishima, H. Ota,
T. Nishikawa, Y. Yamashita, Y. Hayashi, and K. Tsuruta, App. Phys. Lett. 117, 253304 (2020).

3.

Optimization of Molecular Characteristics via Machine Learning Based on Continuous Representation of Molecules
K. Sato and K. Tsuruta Mater. Sci. Forum 1016, 1492 (2021).

UCHIDA, Takashi [ B class; 200 (B), 100 (C) ] (320)— Multiple helical spin density waves in inversion-symmetric itinerant magnets— Multiple-Q states in two-dimensional itinerant magnets
UMEMOTO, Koichiro [ B,C class; 2300 (B), 450 (C) ] (124, 126)
— First principles study of eﬀect of Al impurity on the post-post-perovskite transitions— Order-disorder transition in ultrahigh-pressure phase of the Na-Mg-F system
WATANABE, Haruki [ B class; 800 (B), 200 (C) ] ()— Comprehensive material search based on symmetry indicators
WATANABE, Hiroshi [ B class; 1000 (B), 150 (C) ] (281)— Code Optimization using Machine Learning on Parallel Computer— Molecular Dynamics Study of Crown Formation During the Splash
WATANABE, Hiroshi [ B class; 300 (B), 0 (C) ] (218)— Study for stripe order and superconductivity in high-Tc cuprates by variational Monte Carlo method
WATANABE, Satoshi [ C class; 9200 (B), 1300 (C) ] (56)
— Analyses related to atomic structures and atom dynamics at complex structures such as surfaces
interfaces and defects
1. Straintronic eﬀect for superconductivity enhancement in Li-intercalated bilayer MoS2
P. Mano, E. Minamitani, and S. Watanabe Nanoscale Adv. 2, 3150 (2020).
DOI:10.1039/D0NA00420K
2.

Prediction of viscosity behavior in oxide glass materials using cation ﬁngerprints with artiﬁcial
neural networks
J. Hwang, Y. Tanaka, S. Ishino, and S. Watanabe Sci. Tech. Adv. Mater. 21, 492 (2020).
DOI:10.1080/14686996.2020.1786856

3.

Theoretical prediction of superconductivity in monolayer h-BN doped with alkaline-earth metals(Ca, Sr, Ba)
N. H. Shimada, E. Minamitani, and S. Watanabe, J. Phys. Condensed Matter 32, 435002 (2020).
DOI:10.1088/1361-648X/aba674

4.

Eﬀects of density and composition on the properties of amorphous alumina: A high-dimensional
neural network potential study
W. Li, Y. Ando, and S. Watanabe J. Chem. Phys. 153, 164119 (2020).
DOI:10.1063/5.0026289

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5.

High-dimensional neural network atomic potentials for examining energy materials: some recent
simulations
S. Watanabe, W. Li, W. Jeong, D. Lee, K. Shimizu, E. Mimanitani, Y. Ando, and S. Han, J.
Phys. Energy 3, 012003 (2021).
DOI:10.1088/2515-7655/abc7f3

6.

Nickel-Catalyzed Acyl Group Transfer of o-Alkynylphenol Esters Accompanied by C-O Bond Fission for Synthesis of Benzo[b]furan
R. Doi, K. Shimizu, Y. Ikemoto, M. Uchiyama, M. Koshiba, A. Furukawa, K. Maenaka, S. Watanabe, and Y. Sato ChemCatChem 13, 1 (2021).
DOI:10.1002/cctc.202001949

7.

ニューラルネットワークを用いた原子間ポテンシャルの材料科学における応用事例
清水康司, 渡邉聡, 日本神経回路学会誌 28, 3 (2021).
DOI:10.3902/jnns.28.3

8.

Tuning the Schottky Barrier Height at the Interfaces of Metals and Mixed Conductors
K. Nishio, T. Shirasawa, K. Shimizu, N. Nakamura, S. Watanabe, R. Shimizu, and T. Hitosugi,
ACS Appl. Mater. Interfaces 13, 15746 (2021).
DOI:10.1021/acsami.0c18656

9.

Phase stability of Au-Li binary systems studied using neural network potential
K. Shimizu, E. F. Arguelles, W. Li, Y. Ando, E. Minamitani, and S. Watanabe, Phys. Rev. B
103, 094112 (2021).
DOI:10.1103/PhysRevB.103.094112

YAMADA, Atsuo [ C class; 2000 (B), 750 (C) ] (123)— First principles analyses on novel materials for secondary batteries
1. Theoretical analysis of electrode-dependent interfacial structures on hydrate-melt electrolytes
N. Takenaka, T. Inagaki, T. Shimada, Y. Yamada, A. Yamada J. Chem. Phys. 152, 124706(2020).
DOI:10.1063/5.0003196
2.

Impact of anion asymmetry on local structure and supercooling behavior of water-in-salt electrolytes
D. Reber, N. Takenaka, R.-S. Kuhnel, A. Yamada, C. Battaglia J. Phys. Chem. Lett. 11, 4720
(2020).
DOI:10.1021/acs.jpclett.0c00806

3.

Does spinel serve as a rigid framework for oxygen redox?
X. M. Shi, E. Watanabe, M. Okubo, A. Yamada, Chem. Mater. 32, 7181 (2020).
DOI:10.1021/acs.chemmater.0c00599

4.

First-principles study on the cation-dependent electrochemical stabilities in Li/Na/K hydratemelt electrolytes
K. Miyazaki. N. Takenaka, E. Watanabe, Y. Yamada, Y. Tateyama, A. Yamada ACS Appl.
Mater. Interfaces 12, 42734 (2020).
DOI:10.1021/acsami.0c10472

YAMADA, Atsushi [ C class; 0 (B), 200 (C) ] (219)— Studies of the superconductivity and magnetic states in the strongly correlated electron systems using
Hubbard models.

399

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

YAMADA, Masahiko [ B class; 300 (B), 50 (C) ] (317)— Numerical simulation of the spin Seebeck eﬀect in Kitaev spin liquids
YAMAGUCHI, Naoya [ B,C class; 1000 (B), 150 (C) ] (150)— First-principles Analysis of Band Dispersion in Bulk Insulators/Semiconductors Under Finite Electric
Fields by Using the LCPAO Method— First-principles Calculation of Electric Field Eﬀects in Spin-to-charge Conversion Materials
1. Simple Model for Corrugation in Surface Alloys Based on First-Principles Calculations
M. Nur, N. Yamaguchi, and F. Ishii, Materials 13, 4444 (2020).
DOI:10.3390/ma13194444

YAMAJI, Youhei [ E class; 19000 (B), 3000 (C) ] (187, 188)
— Numerical studies of quantum spin liquid candidates by highly accurate ab initio eﬀective hamiltonians— Numerical studies of quantum spin liquids by quantum mutual information
YAMASHITA, Tomoki [ C class; 3000 (B), 600 (C) ] (99)
— Development of surface and interface structure prediction methods
1. CrySPY: a crystal structure prediction tool accelerated by machine learning
T. Yamashita, S. Kanehira, N. Sato, H. Kino, K. Terayama, H. Sawahata, T. Sato, F. Utsuno, K.
Tsuda, T. Miyake, and T. Oguchi, submitted to Sci. Technol. Adv. Mater.:Methods

YAMAUCHI, Kunihiko [ C class; 4400 (B), 650 (C) ] (87)
— First-principles electronic structure calculations of non-centrosymmetric antiferromagnets
1. Impact of Inter-site Spin-Orbit Coupling on Perpendicular Magnetocrystalline Anisotropy in
Cobalt-Based Thin Films
Thi Phuong Thao Nguyen, Kunihiko Yamauchi, Kohji Nakamura, and Tamio Oguchi Journal of
the Physical Society of Japan
DOI:10.7566/JPSJ.89.114710

YANAGISAWA, Susumu [ C class; 4600 (B), 350 (C) ] (91)
— First-principles investigation on the electronic properties of polymer organic semiconductors— First-principles theoretical study on the electronic structure and interface gap states of organic semiconductor polymers
1. Quantitative analysis of the electrostatic and electronic polarization energies in molecularly mixed
ﬁlms of organic semiconductors
Y. Uemura, S. A. Abd-Rahman, S. Yanagisawa, and H. Yoshida, Phys. Rev. B 102, 125302(2020).
DOI:10.1103/PhysRevB.102.125302

YANAGISAWA, Takashi [ B class; 600 (B), 150 (C) ] (216)— Numerical study of strongly correlated electron systems— Study of new quantum phenomena in correlated electron systems
1. Phase diagram of cuprate high-temperature superconductors based on the optimization Monte
Carlo method
T. Yanagisawa, M. Miyazaki, K. Yamaji, Modern Phys. Lett. B34 (2020) 2040046.
2.

Phase diagram and mechanism of superconductivity in strongly correlated electrons
T. Yanagisawa, M. Miyazaki, K. Yamaji, J. Super. Novel Magne. 33 (2020) 2355.

3.

Electronic structure of novel superconductor doped ZrPSe
I. Hase, T. Yanagisawa, H. Kito et al. J. Phys. Conf. Ser. 1590 (2020) 012008.

400

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

4.

Three-dimensional topological insulator in pyrochlore oxides
I. Hase, T. Yanagisawa Symmetry 12 (2020) 1076.

5.

Zero-energy modes, fractional fermion numbers and the index theorem in a vortex-idirac fermion
systemT. Yanagisawa Symmetry 12 (2020) 373.

6.

Phase diagram of the three-band d-p model
T. Yanagisawa, M. Miyazaki, K. Yamaji, EPL in press

7.

On the kinetic-energy driven superconductivity in the two-dimensional Hubbard model
T. Yanagisawa, M. Miyazaki, K. Yamaji, Condensed Matter 6 (2021) 12.

8.

Enhancement of superconductivity due to kinetic energy eﬀect in the strongly correlated phase in
the two-dimensional Hubbard model
T. Yanagisawa, Physics Letters A 403 (2021) 127382.

9.

Electronic structure of novel superconductor (Ca1−x Srx )Pd3 P
I. Hase, T. Yanagisawa, A. Iyo et al. J. Phys. Conf. Ser. in press

10. Renormalization group theory of generalized multi-vertex sine-Gordon model
T. Yanagisawa Prog. Theor. Exper. Phys. 2021 (2021) 033A01

YASUDA, Chitoshi [ B class; 900 (B), 150 (C) ] (282)— Magnetism in the multiple-spin exchange model on the honeycomb lattice
YOKO, Akira [ B,C class; 5100 (B), 650 (C) ] (78)
— First-principles calculation for low-temperature oxygen transfer in metal oxide— First-principles calculation of oxygen storage capacity and structural distortion of metal doped ceriumoxide— Oxidative reaction of CH4 on CeO2 (100)
1. Atomistic Origin of High-Concentration Ce3+ in 100-Faceted Cr-Doped CeO2 Nanocrystals
X. Hao, A. Yoko, K. Inoue, Y. Xu, M. Saito, C. Chen, G. Seong, T. Tomai, S. Takami, A.L.
Shluger, B. Xu, T. Adschiri, Y. Ikuhara, Acta Materialia. 203, 116473 (2021).
DOI:10.1016/j.actamat.2020.11.015

YOSHIDA, Tsuneya [ C class; 7200 (B), 0 (C) ] (199)— Bulk-edge correspondence for non-Hermitian topological systems— Correlation eﬀects on non-Hermitian topological states
1. Mirror skin eﬀect and its electric circuit simulation
Tsuneya Yoshida, Tomonari Mizoguchi, and Yasuhiro Hatsugai, Phys. Rev. Research 2, 022062(2020).
DOI:10.1103/PhysRevResearch.2.022062
2.

Fate of fractional quantum Hall states in open quantum systems: Characterization of correlated
topological states for the full Liouvillian
Tsuneya Yoshida, Koji Kudo, Hosho Katsura, and Yasuhiro Hatsugai, Phys. Rev. Research 2,033428 (2020).
DOI:10.1103/PhysRevResearch.2.033428

3.

Chiral edge modes in game theory: a kagome network of rock-paper-scissors
Tsuneya Yoshida, Tomonari Mizoguchi, Yasuhiro Hatsugai, arXiv:2012.05562.

401

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

4.

Real-space dynamical mean ﬁeld theory study of non-Hermitian skin eﬀect for correlated systems:
Analysis based on pseudospectrum
Tsuneya Yoshida, Phys. Rev. B 103, 125145 (2021).
DOI:10.1103/PhysRevB.103.125145

5.

Bulk-edge correspondence of classical diﬀusion phenomena
Tsuneya Yoshida, Yasuhiro Hatsugai Sci. Rep. 11, 888 (2021).
DOI:10.1038/s41598-020-80180-w

6.

Exceptional points in the one-dimensional Hubbard model
Roman Rausch, Robert Peters, and Tsuneya Yoshida New J. Phys. 23, 013011 (2021).
DOI:10.1088/1367-2630/abd35e

7.

Square-root topological phase with time-reversal and particle-hole symmetry
Tsuneya Yoshida, Tomonari Mizoguchi, Yoshihito Kuno, Yasuhiro Hatsugai arXiv: 2103.11305.

8.

Machine Learning of Mirror Skin Eﬀects in the Presence of Disorder
Hiromu Araki, Tsuneya Yoshida, and Yasuhiro Hatsugai J. Phys. Soc. Jpn. 90, 053703 (2021).
DOI:10.7566/JPSJ.90.053703

YOSHIDOME, Takashi [ C class; 800 (B), 450 (C) ] (276, 277)
— A Method for Analyzing Protein Dynamics: A Hybrid of Cryo-Electron Microscopy Experiment andMolecular Simulation— A theoretical study for thermal unfolding of proteins with quite similar native structure
1. F1-ATPase Rotation and Its Inhibition from the Viewpoint of Solvent Entropy
T. Yoshidome, Chemical Physics Letters, 757, 137886/1-6 (2020).

YOSHIOKA, Nobuyuki [ B class; 500 (B), 50 (C) ] (305)— Developing numerical tool for open quantum dynamics based on neural networks
1. Neural-Network Quantum States for the Electronic Structure of Real Solids
N. Yoshioka, W. Mizukami, and F. Nori, submitted to Communications Physics
2.

Purifying Deep Boltzmann Machines for Thermal Quantum States
Y. Nomura, N. Yoshioka, and F. Nori, submitted to Phys. Rev. Lett.

402

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo◦ A classSince this class is for trial use, research reports are not required.
When other classes are also used, their publications are shown in the list of B–E classes.
Then, the pages of their reports and publications are given in ( ).
AKIYAMA, Ryota [ A class; 100 (B), 50 (C) ] ()— Band calculation in metal-intercalated graphene
ARUGA, Tetsuya [ A class; 100 (B), 50 (C) ] (351)— Electronic structure and interaction at the interface of π-electron organic molecules and metals
CHIBA, Takahiro [ A class; 100 (B), 50 (C) ] ()— Band structure and spin texture of Bi-Te/ferromagnetic-metal interface
GONOME, Hiroki [ A class; 100 (B), 50 (C) ] ()— Study of the principle of photothermal conversion by ab initio calculations
HATANO, Naomichi [ A class; 100 (B), 50 (C) ] ()— Molecular Dynamics Calculation of Non-equilibrium Steady State in Systems with Temperature Gradient
HATTORI,Ken [ A class; 100 (B), 0 (C) ] (174, 356)
— Atomic structure and electronic states for silicide ﬁlms
ISHIBASHI, Shoji [ A class; 100 (B), 50 (C) ] (167, 361)
— Prediction of properties of organic ferroelectrics and piezoelectrics by ﬁrst-principles calculation
ISHIKAWA, Ryo [ A class; 100 (B), 50 (C) ] ()— First-principles calculation on charged defects in α-Al2 O3
KOTA, Yohei [ A class; 100 (B), 50 (C) ] ()— Analysis of N-doping eﬀect on electronic structure in antiferromagnetic Cr
1. Mechanism of highly sensitive strain response in antiferromagneitc chromium
Yohei Kota, Eiji Niwa, and Masayuki Naoe, Journal of Applied Physics 129, 203901 (2021)
DOI:10.1063/5.0045728

MASAKI, Yusuke [ A class; 100 (B), 50 (C) ] ()— Microscopic calculations of non-axisymmetric vortices in topological superﬂuids
OHTO, Tatsuhiko [ A class; 100 (B), 0 (C) ] (127, 381)
— First-principles transport calculations for molecular junctions
SAKAI, Masatoshi [ A class; 100 (B), 50 (C) ] (217, 386)
— Excess carrier dependent electronic state in organic charge order phase
SATO, Taku [ A class; 100 (B), 50 (C) ] (387)— Magnetic excitations in the quantum pyrochlore magnet
TANUMA, Yasunari [ A class; 100 (B), 50 (C) ] ()— Study on numerical analysis method of superconducting junctions with broken time reversal symmetry
states403

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoTOKUMOTO, Yuki [ A class; 100 (B), 50 (C) ] ()— Exploring dopants to improve bulk-insulation of Pb-based topological insulators
YAMASHITA, Tomoki [ A class; 100 (B), 0 (C) ] (99, 400)
— Development of surface and interface structure prediction methods
YAMATO, Takahisa [ A class; 100 (B), 50 (C) ] (325)— Non-uniform thermal transport properties in proteins
1. Energy transfer across nonpolar and polar contacts in proteins: role of equilibrium ﬂuctuations
P. Humanath, K. M. Reid, T. Yamato, and D. M. Leitner, J. Phys. Chem. B. 124, 9852 (2020).
DOI:10.1021/acs.jpcb.0c08091

YOSHIZAWA, Kanako [ A class; 100 (B), 50 (C) ] ()— Performance measurement of Quantum ESPRESSO

404

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

2 SCCMS Projects
FUJITA, Takatoshi [ 5500 (B), 0 (C) ] (330)— Investigation of charge photogeneration process in organic thin ﬁlm solar cells by large-scale GW/BetheSalpeter equation method— Computational Investigation of Charge Photogeneration in Organic Solar Cells by Fragment-Based
GW/BSE Method
1. Revisiting the Charge-Transfer States at Pentacene/C60 Interfaces with the GW/Bethe–Salpeter
Equation Approach
T. Fujita, Y. Noguchi, T. Hoshi Materials 13, 2728 (2020).
2.

First-Principles Investigations of Electronically Excited States in Organic Semiconductors
T. Fujita In: M. Hiramoto, S. Izawa (eds), Organic Solar Cells, (2021) 155-194, Springer, Singapore.

3.

FMO-Based Investigations of Excited-State Dynamics in Molecular Aggregates
T. Fujita, T. Hoshi In: Y. Mochizuki, S. Tanaka, K. Fukazawa (eds), Recent Advances of the
Fragment Molecular Orbital Method, (2021) 547-566, Springer, Singapore.

FUKUSHIMA, Tetsuya [ 4000 (B), 500 (C) ] (338)— Large-scale simulation for permanent magnets
1. Hole-mediated ferromagnetism in a high-magnetic moment material, Gd-doped GaN
A. Masago, H. Shinya, T. Fukushima, K. Sato, and H. Katayama-Yoshida, J. Phys.: Condens.
Matter 32, 485803 (2020).
DOI:10.1088%2F1361-648x%2Fabac8e2.

First-principles calculations of ﬁnite temperature electronic structures and transport properties
of Heusler alloy Co2 MnSi
H. Shinya, S. Kou, T. Fukushima, A. Masago, K. Sato, H. Katayama-Yoshida, and H. Akai, Appl.
Phys. Lett. 117, 042402 (2020).
DOI:10.1063/5.0017862

3.

Role of atomic-scale thermal ﬂuctuations in the coercivity
Y. Toga, S. Miyashita, A. Sakuma, and T. Miyake Npj Comput Mater 6, 1 (2020).
DOI:10.1038/s41524-020-0325-6

GOHDA, Yoshihiro [ 4000 (B), 500 (C) ] (112)— First-principles study of magnetic materials
1. First-principles determination of intergranular atomic arrangements and magnetic properties inrare-earth permanent magnets
Y. Gohda, Sci. Technol. Adv. Mater. 22, 113 (2021).
DOI:10.1080/14686996.2021.1877092
2.

Prediction of the Curie temperature considering the dependence of the phonon free energy onmagnetic states
T. Tanaka and Y. Gohda, npj Comput. Mater. 6, 184 (2020).
DOI:10.1038/s41524-020-00458-5

3.

Eﬀective quantum-well width of conﬁned electrons in ultrathin Ag(111) ﬁlms on Si(111)7x7 substrates
K. Sugawara, I. Seo, S. Yamazaki, K. Nakatsuji, Y. Gohda, and H. Hirayama, Surf. Sci. 704,

405

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

121745 (2020).
DOI:10.1016/j.susc.2020.121745
4.

First-principles study of magnetism-dependent phonons governed by exchange ligand ﬁeld
T. Tanaka and Y. Gohda, J. Phys. Soc. Jpn. 89, 093705 (2020).
DOI:10.7566/JPSJ.89.093705

5.

First-principles Calculations on High-temperature Desorption Loss from Iridium
I. Seo, S. Yokota, Y. Imai, and Y. Gohda, Comput. Mater. Sci. 184, 109897 (2020).
DOI:10.1016/j.commatsci.2020.109897

6.

First-principles study on magnetism of a crystalline grain-boundary phase in Nd–Fe–B permanent
magnets
Y. Ainai, S. Kou, Y. Tatetsu, and Y. Gohda Jpn. J. Appl. Phys. 59, 060904 (2020).
DOI:10.35848/1347-4065/ab9402

7.

First-principles study of the adsorption of 3d transition metals on BaO- and TiO2-terminatedcubic-phase BaTiO3(001) surfaces
R. Costa-Amaral and Y. Gohda, J. Chem. Phys. 152, 204701 (2020).
DOI:10.1063/5.0008130

IMADA, Masatoshi [ 9600 (B), 1300 (C) ] (184)— Studies on quantum spin liquids in three dimensions— Analyses on Superconducting Mechanism by Machine Learning
1. Single-Particle Spectral Function Formulated and Calculated by Variational Monte Carlo Methodwith Application to d-Wave Superconducting State
Maxime Charlebois and Masatoshi Imada, Phys. Rev. X 10 (2020) 041023.
2.

Charge dynamics of correlated electrons: Variational description with inclusion of composite
fermions
Kota Ido, Masatoshi Imada, Takahiro Misawa, Phys. Rev. B 101 (2020) 075124.

3.

Ab initio study of superconductivity and inhomogeneity in a Hg-based cuprate superconductor
Takahiro Ohgoe, Motoaki Hirayama, Takahiro Misawa, Kota Ido, Youhei Yamaji, Masatoshi
Imada, Phys. Rev. B 101 (2020) 045124.

MATUBAYASI, Nobuyuki [ 8000 (B), 0 (C) ] (337)— Evaluation of the polymer blend miscibility by using chain-increment method with all-atom molecular
dynamics simulation
MISAWA, Takahiro [ 2500 (B), 500 (C) ] (189)— Systematic derivation and analysis of low-energy eﬀective models for iron based superconductors andrelated materials
1. Application of First-Principles-Based Artiﬁcial Neural Network Potentials to Multiscale-ShockDynamics Simulations on Solid Materials
Masaaki Misawa, Shogo Fukushima, Akihide Koura, Kohei Shimamura, Fuyuki Shimojo, Subodh
Tiwari, Ken-ichi Nomura, Rajiv K. Kalia, Aiichiro Nakano, and Priya Vashishta, The Journal of
Physical Chemistry Letters 11, 4536 (2020).
2.

First-Principles Study of Pressure-Induced Amorphization of Fe2SiO4 Fayalite
Masaaki Misawa and Fuyuki Shimojo, Physica Status Solidi B-Basic Solid State Physics 257
2000173 (2020).

406

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoMIYAKE, Takashi [ 500 (B), 500 (C) ] (334)— Development of high-performance permanent magnets by large-scale simulation and data-driven approach
1. Spin-wave dispersion and exchange stiﬀness in Nd2 Fe14 B and RFe11 Ti (R=Y, Nd, Sm) from ﬁrstprinciples calculations
Taro Fukazawa, Hisazumi Akai, Yosuke Harashima and Takashi Miyake, Phys. Rev. B 103,0244187 (2021).
DOI:10.1103/PhysRevB.103.024418
2.

Data Assimilation Method for Experimental and First-Principles Data: Finite-Temperature Magnetization of (Nd,Pr,La,Ce)2 (Fe,Co,Ni)14 B
Yosuke Harashima, Keiichi Tamai, Shotaro Doi, Munehisa Matsumoto, Hisazumi Akai, Naoki
Kawashima, Masaaki Ito, Noritsugu Sakuma, Akira Kato, Tetsuya Shoji, and Takashi Miyake,Physical Review Materials 5, 013806 (2021).
DOI:10.1103/PhysRevMaterials.5.013806

3.

Monoclinic YFe12 phases predicted from ﬁrst principles
Takahiro Ishikawa, Taro Fukazawa, and Takashi Miyake, Physical Review Materials 4, 104408(2020).
DOI:10.1103/PhysRevMaterials.4.104408

4.

Role of atomic-scale thermal ﬂuctuations in the coercivity
Yuta Toga, Seiji Miyashita, Akimasa Sakuma and Takashi Miyake, npj Computational Materials
6, 67 (2020).
DOI:10.1038/s41524-020-0325-6

NAKAYAMA, Masanobu [ 3000 (B), 0 (C) ] (340)— Novel chloride solid electrolytes for all solid-state sodium metal battery
1. Eﬃcient Experimental Search for Discovering a Fast Li-Ion Conductor from a Perovskite-Type
Lix La(1−x) /3NbO3 (LLNO) Solid- State Electrolyte Using Bayesian Optimization
Zijian Yang, Shinya Suzuki, Naoto Tanibata, Hayami Takeda, Masanobu Nakayama, Masayuki
Karasuyama, and Ichiro Takeuchi, J. Phys. Chem. C 125, 152 (2021).
DOI:10.1021/acs.jpcc.0c08887
2.

High Formability and Fast Lithium Diﬀusivity in Metastable Spinel Chloride for Rechargeable
All-Solid-State Lithium-Ion Batteries
Naoto Tanibata, Masashi Kato, Shuta Takimoto, Hayami Takeda, Masanobu Nakayama, andHirofumi Sumi, Advanced Energy & Sustainability Research (2020).
DOI:10.1002/aesr.202000025

OGUCHI, Tamio [ 2500 (B), 500 (C) ] (331)— Electron Theory on Secondary-Battery Materials
1. First-principles study of magnetism and phase stabilities of V2 based antiferromagnetic Heusler
alloysF. Kuroda, T. Fukushima, and T. Oguchi, J. Appl. Phys. 127, 193904 (2020).
DOI:10.1063/1.5143826
2.

Ferroelectric atomic displacement in multiferroic tetragonal perovskite Sr1/2 Ba1/2 MnO3
D. Okuyama, K. Yamauchi, H. Sakai, Y. Taguchi, Y. Tokura, K. Sugimoto, T. J. Sato, and T.
Oguchi, Phys. Rev. Research 2, 033038 (2020).
DOI:10.1103/PhysRevResearch.2.033038

407

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

3.

Spin injection through energy-band symmetry matching with high spin polarization in atomicallycontrolled ferromagnet/ferromagnet/semiconductor structures
Michihiro Yamada, Fumiaki Kuroda, Makoto Tsukahara, Shinya Yamada, Tetsuya Fukushima,
Kentarou Sawano, Tamio Oguchi, and Kohei Hamaya, npg Asia Materials 12, 47 (2020).
DOI:10.1038/s41427-020-0228-5

4.

DFT-based Engineering of Dirac Surface States in Topological-insulator Multilayers
Takao Kosaka, Kunihiko Yamauchi, and Tamio Oguchi, J. Phys. Soc. Jpn. 89, 094701 (2020).
DOI:10.7566/JPSJ.89.094701

5.

Suppression of O-redox reactions by multivalent Cr in Li-excess Li2.4 M0.8 M ’0.8 O4 (M , M ’=Cr,
Mn, and Ti) cathodes with layered and cation-disordered rock-salt structures
Motoyuki Hamaguchi, Hiroyoshi Momida, Ayuko Kitajou, Shigeto Okada, and Tamio Oguchi,Electrochimica Acta 354, 136630 (2020).
DOI:10.1016/j.electacta.2020.136630

6.

Insight into the diﬀusion mechanism of sodium ion-polaron complexes in orthorhombic P2 layered
cathode oxide Nax MnO2
Huu Duc Luong, Van An Dinh, Hiroyoshi Momida, and Tamio Oguchi, Phys. Chem. Chem.
Phys. 22, 18219-18228 (2020).
DOI:10.1039/d0cp03208e

7.

Impact of Inter-site Spin-Orbit Coupling on Perpendicular Magnetocrystalline Anisotropy in
Cobalt-Based Thin Films
Thi Phuong Thao Nguyen, Kunihiko Yamauchi, Kohji Nakamura, and Tamio Oguchi, J. Phys.
Soc. Jpn. 89, 114710 (2020).
DOI:10.7566/JPSJ.89.114710

8.

Magnetocaloric eﬀect in MnCoGe alloys studied by ﬁrst-principles calculations and Monte-Carlosimulation
Hung Ba Tran, Tetsuya Fukushima, Yukihiro Makino, and Tamio Oguchi, Solid State Commun.
323, 114077 (2021).
DOI:10.1016/j.ssc.2020.114077

9.

Tuning structural-transformation temperature toward giant magnetocaloric eﬀect in MnCoGe
alloy: A theoretical study
Hung Ba Tran, Tetsuya Fukushima, Kazunori Sato, Yukihiro Makino, and Tamio Oguchi, J.
Alloys Compd. 854, 157063/1-9 (2021).
DOI:10.1016/j.jallcom.2020.157063

ONO, Kanta [ 2500 (B), 500 (C) ] (336)— Optimized design of magnetic materials based on the integration between quantum beam experimentand ﬁrst-principles calculation
1. (Sm,Zr)Fe12 − x Mx (M=Zr,Ti,Co) for permanent-magnet applications: Ab initio material design
integrated with experimental characterization
Munehisa Matsumoto, Takafumi Hawai, and Kanta Ono, Phys. Rev. Applied 13, 064028 (2020).
DOI:10.1103/PhysRevApplied.13.064028

OSHIYAMA, Atsushi [ 9600 (B), 1300 (C) ] (49)
— Quantum-theory-based multiscale simulation for next-generation power devices
1. Density-Functional Calculations for Structures and Energetics of Atomic Steps and their Implication for Surface Morphology on Si-face SiC Polar Surfaces
K. Seino and A. Oshiyama, Phys. Rev. B 101 (2020) 195307

408

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

DOI:10.1103/PhysRevB.101.195307
2.

Absence of oxygen-vacancy-related deep levels in amorphous (Al2 O3 )1−x (SiO2 )x : First-principles
exploration of gate oxides in GaN-based devices
K. Chokawa, T. Narita, D. Kikuta, T. Kachi, K. Shiozaki, A. Oshiyama and K. Shiraishi, Phys.
Rev. Applied 14 (2020) 014034
DOI:10.1103/PhysRevApplied.14.014034

3.

Screw dislocation that converts p-type GaN to n-type: Microscopic study on Mg condensationand leakagae current in p-n diodes
T. Nakano, Y. Harashima, K. Chokawa, K. Shiraishi, A. Oshiyama, Y. Kangawa, S. Usami, N.
Mayama, K. Toda, A. Tanaka, Y. Honda, and H. Amano, Appl. Phys. Lett. 117 (2020) 012105
DOI:10.1063/5.0010664

4.

Gallium-gallium weak bond that incorporates nitrogen at atomic steps during GaN epitaxial
growthK. M. Bui, K. Shiraishi and A. Oshiyama, Appl. Surf. Sci. 557 (2021) 149542
DOI:10.1016/j.apsusc.2021.149542

SHIBA, Hayato [ 6500 (B), 1000 (C) ] (327)— Large-scale molecular dynamics simulation of viscoelastic relaxation in a two-dimensional supercooled
liquid— Development of all atom molecular simulation framework on a mesoscale
1. 大規模分子シミュレーションによるガラス・ソフトマターの連続体特性の研究
芝 隼人, 分子シミュレーション学会会誌 “アンサンブル” 23, 1 (2020).
2.

Molecular-dynamics simulations on the mesophase transition induced by oscillatory shear inimidazolium-based ionic liquid crystals
M. Liu, H. Shiba, H. Liu, and H. Peng Phys. Chem. Chem. Phys. 23, 6496 (2021).

SUGINO, Osamu [ 4000 (B), 500 (C) ] (48)
— Functionality of transition metal oxides
1. Dopant arrangements in Y-doped BaZrO3 under processing conditions and their impact on proton
conduction: a large-scale ﬁrst-principles thermodynamics study
Shusuke Kasamatsu, Osamu Sugino, Takafumi Ogawa, and Akihide Kuwabara, J. Mater. Chem.
A 8, 12674-12686 (2020).
DOI:10.1039/D0TA01741H
2.

Quantum-Mechanical Hydration Plays Critical Role in the Stability of Fireﬂy Oxyluciferin Isomers: State-of-the-art Calculations of the Excited States
Y. Noguchi, M. Hiyama, M. Shiga, H. Akiyama, O. Sugino, J. Chem. Phys. (2020) 153, 201103
DOI:10.1063/5.0031356

3.

Advances and challenges for experiment and theory for multi-electron multi-proton transfer at
electriﬁed solid-liquid interfaces
K. Sakaushi, T. Komeda, S. Hammes-Schiﬀer, M. M. Melander and O. Sugino Phys. Chem.
Chem. Phys. 22, 19401-19442 (2021).
DOI:10.1039/d0cp02741c

4.

Hydrogen at Electrochemical Interfaces
O. Sugino J. Phys. Soc. Jpn. 89, 051013 (2020).
DOI:10.7566/JPSJ.89.051013

409

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

5.

Surface-state Coulomb repulsion accelerates a metal-insulator transition in topological semimetal
nanoﬁlms
S. Ito, M. Arita, J. Haruyama, B. Feng, W. -C. Chen, H. Namatame, M. Taniguchi, C. -M. Cheng,
G. Bian, S. -J. Tang, T. -C. Chiang, O. Sugino, F. Komori and I. Matsuda Science Advances 6,
eaaz5015 (2020).
DOI:10.1126/sciadv.aaz5015

6.

Challenge of advanced low temperature fuel cells based on high degree of freedom of group 4 and5 metal oxides
A. Ishihara, S. Tominaka, S. Mitsushima, H. Imai, O. Sugino and K.-I. Ota Curr. Op. ElectroChem.
DOI:10.1016/j.coelec.2020.03.005

7.

Completing density functional theory by machine learning hidden messages from molecules
R. Nagai, R. Akashi and O. Sugino npj Comput. Mater. 6, 43 (2020).
DOI:10.1038/s41524-020-0310-0

8.

First-Principles Calculation of Copper Oxide Superconductors That Supports the KamimuraSuwa Model
H. Kamimura, M. Araidai, K. Ishida, S. Matsuno, H. Sakata, K. Shiraishi, O. Sugino and J.-S.
Tsai Condensed Matter 5, 69 (2020).
DOI:10.3390/condmat5040069

TAKETSUGU, Tetsuya [ 2500 (B), 500 (C) ] (333)— Ab initio study toward abundant element nanocatalysts with less precious metals
1. Boron nitride for enhanced oxidative dehydrogenation of ethylbenzene
R. Han, J. Diao, S. Kumar, A. Lyalin, T. Taketsugu, G. Casillas, C. Richardson, F. Liu, C. W.
Yoon, H. Liu, X. Sun, and Z. Huang J. Energy Chem. 57, 477-484 (2021)
DOI:10.1016/j.jechem.2020.03.027
2.

Catalytic Activity of Gold Clusters Supported on h-BN/Au(111) Surface for Hydrogen Evolution
Reaction
M. Gao, M. Nakahara, A. Lyalin, and T. Taketsugu J. Phys. Chem. C 125, 13341344 (2021)
DOI:10.1021/acs.jpcc.0c08826

3.

Heterocyclic Ring-Opening of Nanographene on Au(111)
K. Sun, K. Sugawara, A. Lyalin, Y. Ishigaki, K. Uosaki, T. Taketsugu, T. Suzuki, and S. Kawai
Angew. Chem. Int. Ed. 60, 9427-9432 (2021)
DOI:10.1002/anie.202017137

YAMADA, Atsuo [ 6500 (B), 1000 (C) ] (123)— Theoretical analysis on ion conduction mechanism in aqueous electrolytes for sodium-ion battery— Theoretical analysis of unusual ion transport mechanism in hydrate melt electrolyte
1. Theoretical analysis of electrode-dependent interfacial structures on hydrate-melt electrolytes
N. Takenaka, T. Inagaki, T. Shimada, Y. Yamada, A. Yamada J. Chem. Phys. 152, 124706(2020).
DOI:10.1063/5.0003196
2.

Impact of anion asymmetry on local structure and supercooling behavior of water-in-salt electrolytes
D. Reber, N. Takenaka, R.-S. Kuhnel, A. Yamada, C. Battaglia J. Phys. Chem. Lett. 11, 4720
(2020).
DOI:10.1021/acs.jpclett.0c00806

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3.

Does spinel serve as a rigid framework for oxygen redox?
X. M. Shi, E. Watanabe, M. Okubo, A. Yamada, Chem. Mater. 32, 7181 (2020).
DOI:10.1021/acs.chemmater.0c00599

4.

First-principles study on the cation-dependent electrochemical stabilities in Li/Na/K hydratemelt electrolytes
K. Miyazaki. N. Takenaka, E. Watanabe, Y. Yamada, Y. Tateyama, A. Yamada ACS Appl.
Mater. Interfaces 12, 42734 (2020).
DOI:10.1021/acsami.0c10472

YOSHIMI, Kazuyoshi [ 2500 (B), 500 (C) ] (328)— Creating a Wannier function database toward material design411

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

2 Doctor Theses
1.

AL RASYID, Hasan
Electronic structures of spinel nickel cobaltite from a spin-polarized quasi-particle self-consistent
GW method
Kanazawa University, 2020-09

2.

ASAD, Md. Abdullah Al
First Principles Study on Water Intercalated Grain Boundary of Methyl Ammonium Lead Iodide
Perovskite
Okayama University, 2020-09

3.

FUKUI, Kiyu
Functional Renormalization Group Study on Kitaev Quantum Spin Liquid
The University of Tokyo, 2021-03

4.

GUO, Jiang
Optimal design of spectrally selective photonic structures for thermal radiation applications
The University of Tokyo, 2021-03

5.

HWANG, Jaekyun
Material Property Predictions and Discovery Using a Novel Descriptor “Elemental Fingerprints”
with Neural Networks
The University of Tokyo, 2021-03

6.

ISHIKAWA, Fumihiro
Exploration of Classical Integrable Systems Assisted by Neural Networks
The University of Tokyo, 2021-03

7.

JANG, Seonghoon
Materials design of f-electron based Kitaev-type magnets
The University of Tokyo, 2020-09

8.

KUDO, Koji
Topological invariants and adiabatic principle in correlated systems
University of Tsukuba, 2021-03

9.

NGUYEN Thi Phuong Thao
Theoretical Study on Electric Field Control of Magnetism in 2D Materials
Osaka University, 2021-03

10. OCHI, Masaki
Statistical-Mechanical Analysis of Structures of Directed Complex Networks
The University of Tokyo, 2021-03
11. OHUCHI, Marie
Anomalous Hall eﬀect on a vortex of supercurrent in type-II superconductors
Hokkaido University, 2021-03
12. OKUMURA, ShunChiral magnetism and quantum transport phenomena in noncentrosymmetric metals
The University of Tokyo, 2020-09
13. TAKENAKA, Masato

412

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Theoretical near-ﬁeld vibrational spectroscopy
Hokkaido University, 2021-03
14. TANAKA, Tomonori
Magnetism dependent phonons and their role in magnetic phase transition studied by ﬁrstprinciples thermodynamic formulation
Tokyo Institute of Technology, 2020-9
15. WIDIANTO, Muhammad Yusuf Hakim
First-Principles calculations of spin-polarized cation vacancies in wide-gap semiconductors
Kanazawa University, 2021-03
16. YASSIN, Abdulrahman Hikmat Basher
Mechanisms of Thermal Atomic Layer Etching (ALE) for Metals
Osaka University, 2020-08
17. YOSHIKAWA, Seiji
A Noise-Robust Data Assimilation Method for Crystal Structure Predictions Using Powder Diﬀraction Intensity
The University of Tokyo, 2021-03

413

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

2 Master Theses
1.

CAO, Ruixiao
Numerical study of two-dimensional quantum dimer model
The University of Tokyo, 2020-09

2.

CHIBANA, Yukiko
Classical ground states of the multiple-spin exchange model in a magnetic ﬁeld on a honeycomb
lattice
University of the Ryukyus, 2021-03

3.

DOE, Ryunosuke
Density Functional Theory Study of Surface States at Noble Metal Surfaces
Osaka University, 2021-03

4.

DOU, Ying
Theoretical approach for understanding group-III nitride device structures
The University of Tokyo, 2020-09

5.

ENRIQUEZ, John Isaac Guinto
First-principles Study of the Oxidative Etching Mechanism of the Diamond (100) Surface
Osaka University, 2020-09

6.

FUJIMORI, Shintaro
Non-uniform thermal transport in proteins
Nagoya University, 2021-03

7.

FURUUCHI, Rito
Numerical Study on the Magnetization Process of the Heisenberg Antiferromagnet on the Floret
Pentagon Lattice
University of Hyogo, 2021-3

8.

GOTO, Manami
Synthesis of MoS2 nanotubes by sulﬁrization of oxide precursors
Hokkaido University, 2021-03

9.

HALIM, Harry Handoko
Multi-scale Simulation of Equilibrium Steps Fluctuations on Cu(111) Surfaces
Osaka University, 2020-09

10. HAMAKAWA, Tom
Development of Analysis Method for Inelastic Phonon Transport
The University of Tokyo, 2021-03
11. HARA, Masahiro
Analyses of ion migration in Li3 PO4 under electric ﬁelds using neural network potentials
The University of Tokyo, 2021-03
12. HARADA, Tatsuki
Development of highly eﬃcient computational method for electron-phonon interaction matrix
elements
The University of Tokyo, 2021-03
13. HATSUSHIKA, Jyunna414

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

First-principles study of two photon absorption spectra in perovskite semiconductors
Chiba University, 2021-03
14. HIROSE, Tenshi
Isotope eﬀects in the hydrogenation of styrene on Rh intermetallic catalysts
Hokkaido University, 2021-03
15. HORIKAWA, Ryo
Consideration on Mechanism of Superconductivity in BiS2-Based Layered Superconductors byUsing Orbital Splitting Eﬀect: Spin ﬂuctuation and phonon mechanisms
Tokyo Metropolitan University, 2021-03
16. INAYOSHI, Ken
Theoretical Study of Equilibrium Order and Nonequilibrium Dynamics in the Quasicrystalline
Excitonic Insulator
Tokyo Institute of Technology, 2021-03
17. IRIGUCHI, Takuya
Density Functional Theory Study on Dehydrogenation Reaction of Methanol on Pt Surfaces
Osaka University, 2021-03
18. IWANO, Akito
Microscopic Origin of Stable High-Temperature Superconductivity in Multilayer Copper Oxides
The University of Tokyo, 2021-03
19. KADONO, Tomoyuki
Material design of α-SrSi2 based on theoretical calculations snd structural and electronic properties of Mg2Si doped with Sb and Zn by synchrotron radiation analysis
Tokyo University of Science, 2021-03
20. KATAOKA, Yuta
Surface reconstruction of Au(111) and quantum diﬀusion of adsorbed hydrogen
The University of Tokyo, 2021-03
21. KOFUJI, Akira
Eﬀect of strong correlation on the non-linear response in Weyl-Kondo semimetals
Kyoto University, 2021-03
22. KOJIMA, Ryota
A Computational Method for Constructing a Continuous Function Describing Cryo-Electron Microscopy Data: A Study using a Manifold Learning
Tohoku University, 2021-03
23. KOYAMA, Hiroaki
Implement of free volume calculation using higher neighbors and its application to the glassy
systems
Nagoya Institute of Technology, 2021-03
24. KUBOTA, Genki
Scaling of thermal transport through native contacts in proteins with equilibrium ﬂuctuations
Nagoya University, 2021-03
25. MANO, PoopodinFirst-principles analyses of strain eﬀects on properties of layered transition-metal dichalcogenides
The University of Tokyo, 2021-03

415

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

26. MATAYOSHI, Keita
Monte Carlo study of the multiple-spin exchange model in a magnetic ﬁeld on a honeycomb lattice
University of the Ryukyus, 2021-03
27. MIZUGUCHI, Atsuki
Machine Learning Construction of Electron-Temperature-Dependent Interatomic Potential
The University of Tokyo, 2021-03
28. MIZUGUCHI, Ryunosuke
Theoretical study for ground-state properties of the Heisenberg antiferromagnet on the the Cairo
Pentagon latticeTokyo University of Science, 2021-03
29. NAKATSU, Daisuke
Stability of TiAl-based multicomponent alloys from ﬁrst principles
Tokyo Institute of Technology, 2021-3
30. NISHINO, Koki
Analyses of thermal transport properties of carbon-based materials using neural Network Potentials
The University of Tokyo, 2021-03
31. NOZAKI, Misa
Electronic state analysis of organic molecules in angle-resolved photoelectron spectroscopy
Chiba University, 2021-03
32. OIKAWA, Takuya
First-principles study of diﬀusion and distribution of oxygen vacancies in metal oxides
Chiba University, 2021-03
33. OKADA, Naoki
Dynamical Variational Monte Carlo Approaches for Excitation Spectra of Many-Body Fermionsin Continuum SpaceThe University of Tokyo, 2021-03
34. OTANI, Yusuke
First-principles calculation of eﬀects on PdZn surface by intermediates of methanol steam reforming
Kagoshima University, 2021-03
35. SEO, InsungFirst-principles study on iridium loss at high temperatures
Tokyo Institute of Technology, 2020-9
36. SHIMAZU Ryoma
First-principles Calculation of Topological Insulator Hetero Structure with Spin Splitting Bands
Osaka University, 2021-03
37. SHIMIZU, Kotaro
Theoretical study on control of topological spin textures based on spin moire picture
The University of Tokyo, 2021-03
38. SHIMOMURA, Tadahisa
Local Atomic Structures and Magnetic Properties of Mn doped ZnSnAs2

416

Activity Report 2020 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Osaka University, 2021-03
39. SATO, Nao
Rational design of the peptide inhibitor targeting the interaction of the KIX domain of the transcriptional coactivator CBP with transcriptional activators
The University of Tokyo, 2021-03
40. TAKEHANA, Hiroki
Interaction of diamond and alkali metals and its application
Hokkaido University, 2021-03
41. TESHIMA, Ryo
Mechanical properties of Ir-based alloys from ﬁrst principles
Tokyo Institute of Technology, 2021-3
42. UEDA, KayoFirst-principles study on Schottky barrier modulation at metal/Ge interfaces
Chiba University, 2021-03
43. YAMADA, Tatsuru
Appearance of ferromagnetism and change in magnetism in Pt(100) thin ﬁlm by adsorbing organic
materials: Experimental and ﬁrst-principles studies
Keio University, 2021-03
44. YAMAZAKI, Ryo
Computational Studies on adsorption and diﬀusion properties of Li and Na atoms on Ti-based
MXene sheets
Hokkaido University, 2021-03
45. YOSHIDA, Akira
Thermodynamic functions of equilibrium and nonequilibrium solutions used modern thermodynamics
Ibaraki University, 2021-03
46. YOSHIDA, Shintaro
Development of Prediction Model for Thermal Conductivity with Graph Structure and Transfer
Learning
The University of Tokyo, 2020-09
47. ZHANG, Peiyu
Molecular dynamics simulation of water transport through ﬂuorous nanochannel
The University of Tokyo, 2020-09

417