Doctoral Dissertation
博士論文
Novel technique to purify liquid xenon for
the XENONnT dark matter search experiment(XENONnT 暗黒物質探索実験のための新しい液体キセノン純化手法)

A Dissertation Submitted for the Degree ofDoctor of Philosophy
December 2021
令和 3 年 12 月博士 (理学) 申請
Department of Physics, Graduate School of Science,
The University of Tokyo東京大学大学院理学系研究科
物理学専攻
Nobuyuki Kato
加藤伸行

Abstract
Numerous observations suggest the existence of dark matter, and oneof the most motivated candidates is Weakly Interacting Massive Particles(WIMPs). To search for WIMPs, a liquid xenon time projection chamber(TPC) has been the most successful technique. To enhance the sensitivity,
experiments with larger xenon mass and lower background are planned, suchas XENONnT. XENONnT is a successor to XENON1T and aims to achieve asensitivity to spin-independent WIMP-nucleon cross section of 1.4×10−48 cm2
for a 50 GeV/c2 mass WIMP. One of the main challenges in realizing large
xenon TPC is how to reduce electronegative impurities such as oxygen which
capture charge signals. In this thesis, we report a new method to remove
electronegative impurities in liquid xenon. Unlike standard purification in
the gas phase with hot getters, the new method utilizes a circulation in theliquid phase. Circulation in the liquid phase can easily realize a much higher
mass circulation speed compared to the gaseous phase thanks to ≈ 500 times
larger density of the liquid. Copper (Q5) and non-evaporable getter (St707)
materials were used as filters to remove impurities, and the application of
non-evaporable getters in the cryogenic fluid has never been reported before.
We confirmed that by using those two liquid purification filters, we can purify
8.6 t of liquid xenon to 13.5 ± 0.2 ms of a free electron lifetime which isequivalent to about 0.02 ppb of oxygen concentration, and thanks to the lowradon emanation rate of the St707 filter (0.24 ± 0.03 mBq per filter unit,
accomodating 3.0 kg of the St707 pellets), this technique is compatible withlow background experiments such as dark matter search. It was the firsttime to achieve such a high electron lifetime in liquid xenon detectors and it
is even more impressive considering the amount of xenon we had. The new
method developed in this thesis improved the sensitivity of the XENONnT
experiment by a factor of three compared to the conventional gas purification
only scenario and the purity of xenon is high enough to achieve the projected
sensitivity of XENONnT. Since this technique is so powerful, it seems to bepromising for future large-scale liquid xenon experiments such as nEXO andDARWIN.

i

Acknowledgements
First of all, I would like to express my gratitude to my supervisor, Prof.
Shigetaka Moriyama, for giving me an opportunity to work on a dark mattersearch in the XENON experiment. I am grateful for continuous support,
guidance and encouragement throughout my graduate course. I would liketo thank Prof. Masaki Yamashita for the tremendous support he gave toaccomplish this work. I learned so much from his knowledge and experienceon liquid xenon experiments as well as his attitude toward experiments. I
would like to thank Dr. Guillaume Plante, Dr. Masatoshi Kobayashi, Joey
Howlett and Micha Weiss. It was my privilege to work with them on thedevelopment of the liquid purification system. They gave me a lot of advice
to improve my work. They also helped my life in Italy like going to eat, giving
a ride, etc. I am grateful to Prof. Shingo Kazama, Dr. Jingqiang Ye, Lutz
Althuser and other analysis members who gave me important insights on
my analysis of the electron lifetime from TPC data. Their comments at theanalysis meetings were always valuable. I am thankful to Prof. Elena Aprile
and all the XENON collaboration members for welcoming me and giving me
an opportunity to work in a wonderful collaboration. It was my pleasure towork together underground and above ground to realize the experiment. I
would like to thank my friend, Satoru Kobayashi, who gave me information
about a trip abroad during the COVID-19 times. Without it, I was not able
to go to Italy to start the liquid purification of XENONnT which was themost important moment in my graduate course. I am also thankful to Cesare
Suleiman who kindly oﬀered me a room in Italy even during COVID-19 times
and assisted me a lot in every inconvenient moment. I am grateful to all the
Kamioka students and staﬀ for their support in my life in Kamioka. I wasable to have an enjoyable time. I am thankful to ALPS program and JSPS
fellowship for educational and financial aids. Finally, I would like to thankmy family for their continuous supports.

ii

Preface
OutlineThis thesis is structured as follows. As an introduction, chapter 1 discusses
evidence for dark matter and some of the popular dark matter candidates.
Then many diﬀerent attempts to detect dark matter are summarized, including direct searches in which the XENON experiment is categorized. We also
highlight the importance of this work to the success of XENONnT. In chapter 2, we will have a review of the XENONnT detector and clarify the roleof the liquid xenon purification system on which this thesis focuses. Next,
chapter 3 describes details of new liquid xenon purification system hardware,
especially liquid filters and a purity monitor which play main roles in thefollowing chapters.
In chapter 4, the results of liquid xenon purification commissioning tests
are shown. We also discuss some important lessons we learned from thesetests. Next in chapter 5, we present the result of purification in XENONnT.
The strategy taken for XENONnT purification is highly based on the findings
in chapter 4. In chapter 6, we also confirm the achieved purity using datafrom the XENONnT detector and then discuss how awesome the achievement
is. Finally, chapter 7 summarizes the achievements presented in this thesis.

Author’s contribution
This thesis is based on works done by the liquid purification working groupof XENON collaboration which the author belongs to. The author was onsite(Laboratori Nazionali del Gran Sasso, Italy) with a few other members forthe construction of the liquid purification system and the following commissioning tests. The results of the tests presented in chapter 4 are from analysis
performed by the author and based on those results, the author proposed thestrategy of filter usage which led to the success of XENONnT purification.
It is worth mentioning that all the purity data in chapter 4 (chapter 5 aswell) was taken by the liquid xenon purity monitor which has been develiii

oped and operated by the author. In 2020, despite the COVID-19 pandemic,
the author went onsite to start liquid purification of XENONnT. Results anddiscussions related to XENONnT purification shown in chapter 5 are basedon works by the author. Chapter 6 shows the analysis of purity (electron
lifetime) from XENONnT TPC data which was done by the author. The
author has been a responsible person for this topic in the data analysis working group to characterize XENONnT TPC response, which will ultimately
be used in all the physics search analyses.

iv

Contents
1 Introduction
1
1.1 Evidence of dark matter . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Cosmic Microwave Background . . . . . . . . . . . . . 1
1.1.2 Gravitational lensing . . . . . . . . . . . . . . . . . . . 2
1.1.3 Galaxy rotation curve . . . . . . . . . . . . . . . . . . 3
1.2 Dark matter candidates . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Neutrinos . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.2 Massive Compact Halo Objects . . . . . . . . . . . . . 5
1.2.3 Weakly Interacting Massive Particles . . . . . . . . . . 5
1.3 Dark matter detection experiments . . . . . . . . . . . . . . . 7
1.3.1 Collider experiment . . . . . . . . . . . . . . . . . . . . 7
1.3.2 Indirect search . . . . . . . . . . . . . . . . . . . . . . 7
1.3.3 Direct search . . . . . . . . . . . . . . . . . . . . . . . 9
1.4 From XENON1T to XENONnT . . . . . . . . . . . . . . . . . 13
2 XENONnT experiment
2.1 Detector principle . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 XENONnT infrastructure overvirew . . . . . . . . . . . . . . .
2.3 XENONnT TPC . . . . . . . . . . . . . . . . . . . . . . . . .
2.4 Water tank . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.1 Muon veto . . . . . . . . . . . . . . . . . . . . . . . . .
2.4.2 Neutron veto . . . . . . . . . . . . . . . . . . . . . . .
2.5 Cryogenic system . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Purification system . . . . . . . . . . . . . . . . . . . . . . . .
2.6.1 Gas purification . . . . . . . . . . . . . . . . . . . . . .
2.6.2 Liquid purification . . . . . . . . . . . . . . . . . . . .
2.6.3 Kr distillation . . . . . . . . . . . . . . . . . . . . . . .
2.6.4 Rn distillation . . . . . . . . . . . . . . . . . . . . . . .
2.7 Calibration system . . . . . . . . . . . . . . . . . . . . . . . .
2.7.1 Internal calibration . . . . . . . . . . . . . . . . . . . .
2.7.2 External calibration . . . . . . . . . . . . . . . . . . . .
v

18
18
23
23
25
26
26
27
28
28
28
30
30
31
31
32

CONTENTS
2.8
2.9

Background sources of XENONnT . . . . . . . . . . . . . . . . 33
Sensitivity of XENONnT . . . . . . . . . . . . . . . . . . . . . 34

3 Liquid xenon purification system
3.1 Xenon purity . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1 Electron lifetime . . . . . . . . . . . . . . . . . . . . .
3.1.2 Electron lifetime and sensitivity of XENONnT . . . . .
3.2 Liquid xenon purification system : overview . . . . . . . . . .
3.3 Liquid pump . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Liquid nitrogen heat exchanger . . . . . . . . . . . . . . . . .
3.5 Liquid filters . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5.1 Q5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5.2 St707 . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.6 Purity monitor . . . . . . . . . . . . . . . . . . . . . . . . . .
3.6.1 Working principle . . . . . . . . . . . . . . . . . . . . .
3.6.2 Purity monitor installation . . . . . . . . . . . . . . . .
3.6.3 Diﬀerent measurement modes . . . . . . . . . . . . . .

36
36
36
37
39
40
41
42
42
43
44
46
47
48

4 Commissioning with about 2 t of xenon
4.1 Filter eﬃciency estimations . . . . . . . . . . . . . . . . . . .
4.1.1 Filter eﬃciency from pre-filter measurements . . . . . .
4.1.2 Filter eﬃciency from post-filter measurements . . . . .
4.2 First test in October 2019 . . . . . . . . . . . . . . . . . . . .
4.2.1 Filling the cryostat . . . . . . . . . . . . . . . . . . . .
4.2.2 First purity measurements . . . . . . . . . . . . . . . .
4.2.3 Testing 18 g Q5 filter . . . . . . . . . . . . . . . . . . .
4.2.4 Testing 60 g Q5 filter (1) . . . . . . . . . . . . . . . . .
4.3 Second test in February 2020 . . . . . . . . . . . . . . . . . .
4.3.1 Outgassing measurement . . . . . . . . . . . . . . . . .
4.3.2 Testing 11 g Q5 filter . . . . . . . . . . . . . . . . . . .
4.3.3 Testing St707 filter . . . . . . . . . . . . . . . . . . . .
4.3.4 Testing 60 g Q5 filter (2) . . . . . . . . . . . . . . . . .
4.4 Lessons from two tests and next step . . . . . . . . . . . . . .
4.4.1 Strategy for the XENONnT purification . . . . . . . .
4.4.2 Contact time theory of the filter eﬃciency . . . . . . .

53
53
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54
56
56
57
58
63
65
67
67
68
69
71
73
73

5 Liquid purification in XENONnT
5.1 Period 1: Filter bypass mode . . . . . . . . . . . . . . . . . .
5.2 Period 2: Purification with Q5 . . . . . . . . . . . . . . . . . .
5.3 Period 3: Purification with St707 . . . . . . . . . . . . . . . .
5.4 Systematic uncertainty of purity monitor measurement . . . .

76
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78
80
84

vi

CONTENTS
5.5
5.6

St707 filtering eﬃcency . . . . . . . . . . . . . . . . . . . . . . 90
Radon rate in the detector . . . . . . . . . . . . . . . . . . . . 93

6 Electron lifetime from TPC data
97
6.1 Basic data selection . . . . . . . . . . . . . . . . . . . . . . . . 97
6.2 Electron lifetime from 83m Kr . . . . . . . . . . . . . . . . . . . 99
6.3 Electron lifetime from Radon alpha decays . . . . . . . . . . . 102
6.4 Electron lifetime from xenon activated lines . . . . . . . . . . 106
6.5 Time evolution . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.6 Comparison of the achievement with past and future experiments110
7 Conclusion

112

Appendix
115
A
Purity Monitor . . . . . . . . . . . . . . . . . . . . . . . . . . 115
A.1
Structure . . . . . . . . . . . . . . . . . . . . . . . . . 115
A.2
Optics . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
A.3
Electronics and DAQ . . . . . . . . . . . . . . . . . . . 118
B
Signal corrections in TPC analyses . . . . . . . . . . . . . . . 120
B.1
S1 position dependence correction . . . . . . . . . . . . 121
B.2
S2 position dependence correction . . . . . . . . . . . . 122

vii

List of Figures
1.1 Power spectrum of CMB anisotropy by Planck . . . . . . . . .
1.2 Concept of gravitational lensing . . . . . . . . . . . . . . . . .
1.3 Example of gravitational lensing at Abbel 370 . . . . . . . . .
1.4 Galaxy rotation speed. . . . . . . . . . . . . . . . . . . . . . .
1.5 Microlensing eﬀect . . . . . . . . . . . . . . . . . . . . . . . .
1.6 Mono jet in collider . . . . . . . . . . . . . . . . . . . . . . . .
1.7 Limits on dar matter cross section using neutrinos . . . . . . .
1.8 Diﬀerent energy channels used for dark matter searches . . . .
1.9 Neutron flux in the underground laboratories . . . . . . . . . .
1.10 Current limits on dark matter . . . . . . . . . . . . . . . . . .
1.11 Demonstarion of ER discrimination . . . . . . . . . . . . . . .

2
3
4
5
6
8
9
12
13
14
16

2.1
2.2

TPC working principle . . . . . . . . . . . . . . . . . . . . . . 19
Relationship between the electric field and the electron drift
velocity in liquid xenon . . . . . . . . . . . . . . . . . . . . . . 20
2.3 ER and NR band separation . . . . . . . . . . . . . . . . . . . 22
2.4 XENONnT infrastructure . . . . . . . . . . . . . . . . . . . . 24
2.5 XENONnT TPC . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.6 TPC electrode configuration . . . . . . . . . . . . . . . . . . . 26
2.7 Water tank . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.8 XENONnT purification system . . . . . . . . . . . . . . . . . 29
2.9 Decay chain of 222 Rn . . . . . . . . . . . . . . . . . . . . . . . 31
2.10 XENONnT background . . . . . . . . . . . . . . . . . . . . . . 33
2.11 XENONnT sensitivity curve . . . . . . . . . . . . . . . . . . . 35
2.12 Discrimination between solar axions and tritium with XENONnT 35
3.1
3.2
3.3
3.4
3.5

Attachment rate of electron and electronegative impurities . .
Overlap of ER and NR band at diﬀerent electron lifetime . . .
Electron lifetime vs WIMP sensitivity . . . . . . . . . . . . . .
Schematics of liquid xenon purification system . . . . . . . . .
Picture of liquid purification skid . . . . . . . . . . . . . . . .
viii

37
38
39
40
41

LIST OF FIGURES
3.6 Picture of Q5 filter . . . . . . . . . . . . . . . . . . . . . . . .
3.7 Q5 regeneration . . . . . . . . . . . . . . . . . . . . . . . . . .
3.8 Picture of St707 filter . . . . . . . . . . . . . . . . . . . . . . .
3.9 Picture and drawing of purity monitor . . . . . . . . . . . . .
3.10 Working principle of purity monitor . . . . . . . . . . . . . . .
3.11 Example waveform of the purity monitor . . . . . . . . . . . .
3.12 Drawing of purity monitor outer vessel . . . . . . . . . . . . .
3.13 Purity monitor installation . . . . . . . . . . . . . . . . . . . .
3.14 Flow path of the purity monitor pre-filter mode . . . . . . . .
3.15 Flow path of the purity monitor post-filter mode . . . . . . . .

43
44
45
46
48
49
50
51
52
52

4.1 Eﬃciency from post-filter measurement . . . . . . . . . . . . .
4.2 Comparison of filter geometries used in commissioning tests. .
4.3 ReStoX-1 mass during filling . . . . . . . . . . . . . . . . . . .
4.4 Filling cryostat from ReStoX-1 . . . . . . . . . . . . . . . . .
4.5 Liquid circulation filter bypass mode . . . . . . . . . . . . . .
4.6 Electron lifetime trend with GXePUR . . . . . . . . . . . . . .
4.7 Electron lifetime trend without GXePUR . . . . . . . . . . . .
4.8 18 g Q5 filter . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.9 Result of 18 g Q5 filter (post-filter measurement) . . . . . . .
4.10 Result of 60 g Q5 filter (pre-filter measurement) . . . . . . . .
4.11 Evolution of the eﬃciency in 60 g Q5 . . . . . . . . . . . . . .
4.12 Electron lifetime evolution in the second commissioning test .
4.13 Outgassing measurement in the second commissioning test . .
4.14 Time dependent eﬃciency of 11 g Q5 . . . . . . . . . . . . . .
4.15 Time dependent eﬃciency of the St707 filter . . . . . . . . . .
4.16 Time dependent eﬃciency of 60 g Q5 . . . . . . . . . . . . . .
4.17 Q5 filter eﬃciencies explained by contact time theory . . . . .

55
57
58
59
60
61
61
62
62
64
64
66
67
68
69
70
75

5.1 Electron lifetime in filter bypass mode . . . . . . . . . . . . .
5.2 Electron lifetime trend in Q5 era . . . . . . . . . . . . . . . .
5.3 Electron lifetime before and after the Q5 filter switch . . . . .
5.4 St707 vessel . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5 Electron lifetime trend since the beginning . . . . . . . . . . .
5.6 Does drift electrons reach anode without loss? . . . . . . . . .
5.7 Cathode-anode ratio QA /QC as a function of flow rate . . . .
5.8 Electron lifetime trend since February 2021 . . . . . . . . . . .
5.9 St707 eﬃciency as a function of correction factor α . . . . . .
5.10 Systematic uncertainty band of the electron lifetime measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.11 St707 eﬃciency estimation . . . . . . . . . . . . . . . . . . . .

77
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80
81
83
84
85
87
89

ix

89
91

LIST OF FIGURES
5.12 Radon alpha selection . . . . . . . . . . . . . . . . . . . . . . 95
5.13 222 Rn + 218 Po rate evolution. . . . . . . . . . . . . . . . . . . 96
6.1 S2 Width cut and S1 AFT cut . . . . . . . . . . . . . . . . . . 98
6.2 Example waveform of 83m Kr events. . . . . . . . . . . . . . . . 99
6.3 83m Kr double S1 population . . . . . . . . . . . . . . . . . . . 100
6.4 Electron lifetime from 83m Kr . . . . . . . . . . . . . . . . . . . 101
6.5 Eﬀect of electric field . . . . . . . . . . . . . . . . . . . . . . . 102
6.6 Rn alphas ROI . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6.7 S1 correction for alphas . . . . . . . . . . . . . . . . . . . . . . 103
6.8 Radon events in r2 vs corrected S1 space . . . . . . . . . . . . 104
6.9 Example electron lifetime fitting from 222 Rn . . . . . . . . . . 105
6.10 Selection of xenon activation lines . . . . . . . . . . . . . . . . 106
6.11 Electron lifetime evolution . . . . . . . . . . . . . . . . . . . . 108
A.1
A.2
A.3
A.4
B.5
B.6
B.7
B.8

Purity monitor structure . . . . . . . . . . . . . . . . . . . . . 116
Purity monitor grid . . . . . . . . . . . . . . . . . . . . . . . . 117
Xenon flash lamp . . . . . . . . . . . . . . . . . . . . . . . . . 119
Purity monitor circuit . . . . . . . . . . . . . . . . . . . . . . 120
TPC coordinate system . . . . . . . . . . . . . . . . . . . . . . 120
S1 light yield map . . . . . . . . . . . . . . . . . . . . . . . . . 121
S2 light yield map . . . . . . . . . . . . . . . . . . . . . . . . . 122
Distribution of S2 yield . . . . . . . . . . . . . . . . . . . . . . 123xList of Tables
1.1

Main factors that determine the sensitivity of the experiment.
XENON1T is also shown for comparison. The ER discrimination power is defined as a fraction of ER events that stay
above the median of the NR band. The ER background rateis calculated in between [1,13] keV recoil energy. . . . . . . . 15

2.1

XENONnT background rates . . . . . . . . . . . . . . . . . . 34

4.1

Summary of the commissioning tests. The results of filter tests
are summarized. Initial eﬃciencies were obtained under statedflow rates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

5.1

Summary of the filter eﬃciencies measured in this thesis. Bothresults from commissioning and XENONnT are shown. For
the eﬃciencies of Q5 and St707 in XENONnT, only lower limits are shown because we did not see any obvious sign of eﬃciency loss. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
St707 filter eﬃciency . . . . . . . . . . . . . . . . . . . . . . . 93
Energies of α rays from 222 Rn and its daughters. . . . . . . . . 94

5.2
5.3

7.1 Main achievements of this work. . . . . . . . . . . . . . . . . . 114
A.1 Applied voltages to each electrode in 100 V/cm operation . . . 118

xiChapter 1
Introduction
In this chapter, we introduce evidence for dark matter from observations
at diﬀerent scales. Some dark matter candidates are also discussed. Then,
we describe various approaches to detect dark matter. Finally, XENONnTis briefly introduced to emphasize the importance of the work presented inthis thesis to achieve the projected sensitivity of the experiment.

1.1

Evidence of dark matter

Numerous observations, ranging from cosmological to astronomical scales,suggest the existence of an unknown mass component in our universe, as
known as dark matter.

1.1.1

Cosmic Microwave Background

One of the most elegant evidence of dark matter comes from the measurement of temperature anisotropies of cosmic microwave background (CMB).
CMB directly reflects the matter distribution at the recombination of theuniverse which happened about 380,000 years after the Big Bang. By expanding the temperature anisotropies using spherical harmonics functions
Yl,m (θ, ϕ), power spectrum can be obtained. Figure 1.1 is such a spectrum
presented by Planck Collaboration [1].
The spectrum is very well explained by Λ cold dark matter (ΛCDM, Λ isa cosmological constant to explain the expansion of the universe) model andthe energy densities of each component of the universe are derived to beΩb h2 = 0.02237 ± 0.00015,Ωm h2 = 0.1430 ± 0.0011,ΩΛ = 0.6847 ± 0.0073,
1

(1.1)
(1.2)
(1.3)

1 Introduction
6000

D`T T [µK2 ]

5000
4000
3000
2000
1000

∆D`T T

0
600

60
30
0
-30
-60

300
0
-300
-600
2

10

30

500

1000

1500

2000

2500

`

Figure 1.1: (Top) Power spectrum of CMB anisotropy by Planck. DlT T isa spectrum at each moment l. The spectrum is well described by a model
called ΛCDM model (blue line). (Bottom) Plot shows residual of DlT T withrespect to the model. Figure taken from [1].
where Ωb , Ωm , and ΩΛ are the energy densities for baryons, matter, and darkenergy respectively, and h is the Hubble constant in units of 100 km/s/Mpc
and constrained as h = 0.6736 ± 0.0054.

1.1.2

Gravitational lensing

General relativity predicts that space-time gets distorted when there is amassive object nearby. Thus when light emitted from a source travels nearsuch an object, its path gets curved just like passing through lens (gravitational lensing, Fig. 1.2). As a result, an observer on the earth may see
distorted or multiple images from the same source (Fig. 1.3).
The mass of the massive object can be estimated in multiple ways. We
can use the degree of distortion by gravitational lensing but the light intensityof the object is another way. However, in most of the galaxy clusters, themass calculated from light intensity was less than the mass from gravitational
lensing, which indicates that there is additional mass that does not emit light.
This missing mass is also evidence of dark matter.

2

1 Introduction

Figure 1.2: Concept of gravitational lensing. The trajectory of light emitted
from the source is bent by the massive object on its way. The observer on
the earth may see distorted or multiple images.

1.1.3

Galaxy rotation curve

There is convincing evidence from smaller scales such as galaxy rotation
speed. From Newtonian dynamics, rotation speed v at a large radius r in aspiral galaxy should follow
1v(r) ∝ √ .
r

(1.4)

However, rotation speed measurements of spiral galaxies revealed thatrotation speed does not decrease as equation 1.4 but rather flat [3]. Rotation
curves for many galaxies are summarized in Fig. 1.4. The assumption underequation 1.4 is that mass is gathering at the center of the galaxy and few
objects exist at a large radius. The flat curve in Fig. 1.4 indicates that
this assumption is wrong. In order to have higher speeds at large r, we needadditional mass in the galaxy to balance the centrifugal force and the gravity.

1.2

Dark matter candidates

From the observations above, we can predict some basic properties ofdark matter.
3

1 Introduction

Figure 1.3: Example image of gravitational lensing at galaxy cluster Abbel
370 taken by Hubble Space Telescope [2].
• It should have mass.
• It should not emit light and thus should be charge neutral.
• It should be stable, or at least its lifetime is significantly longer than
the age of our universe.
There are several objects or particles that satisfy the requirements above
and are considered as candidates of dark matter. Here some of them are
introduced.

1.2.1

Neutrinos

Among standard model particles, neutrinos are the only ones that satisfy
the requirements above. However, the N-body simulation of the structureformation ruled out the scenario of neutrino dominated universe due to its
relativistic velocity [5]. In addition, the abundance of the relic neutrinos in
the universe is calculated to beΩν =Σ3i=1 mi
,
93 eV

(1.5)

where mi is the neutrino mass of each generation (i = e, µ, τ ) [6]. Recent
measurements by Planck satellites revealed that the sum of neutrino mass isconstrained by Σ3i=1 mi < 0.12 eV [1]. This indicates that neutrinos cannot
be a dominant component of our universe.
41 Introduction

Figure 1.4: Galaxy rotation speed for diﬀerent spiral galaxies [4]. Dashedline is a curve expected from visible matter. Ropt is a radius of the √galaxydefined using luminosity. It is clear that the curve does not follow 1/ r but
rather flat.
The other dark matter candidate of neutrino is a hypothetical particle
called sterile neutrinos. This was initially introduced to explain the small
mass of standard neutrinos. If sterile neutrino has the mass scale of keV, it
can be a candidate of warm dark matter [7].

1.2.2

Massive Compact Halo Objects

MAssive Compact Halo Objects (MACHOs) are massive objects in galaxy
halo that do not emit light (or too faint to observe). Objects such as neutronstars, brown dwarfs, and black holes can be MACHOs. Although they are notvisible directly with light, a gravitational eﬀect called the microlensing eﬀect
is useful to observe these types of objects. The concept of the microlensing
eﬀect is shown in Fig. 1.5. When a massive and invisible object passes acrossthe light trajectory from a luminous object, due to the gravitational lensing
eﬀect, its luminosity increases. We can estimate the mass of the invisible
object by luminosity changes. However, observations such as [8] excluded
the MACHOs dominant dark matter scenario in the galaxy.

1.2.3

Weakly Interacting Massive Particles

Weakly Interacting Massive Particles (WIMPs) are beyond standard model
particles which have a mass range of GeV/c2 to TeV/c2 and interact weakly
51 Introduction

Figure 1.5: Microlensing eﬀect by an object moving between Earth and a
distant star. The object serves as a lens and the luminosity of the starincreases. Figure from [9].
with ordinary matter. Supersymmetry (SUSY) is a theory that introduces
partner particles for standard model particles which can be a WIMP candidate. The supersymmetric partner diﬀers spin 1/2, such that the partnerof standard fermions would be supersymmetric bosons and the partner ofstandard bosons would be supersymmetric fermions. SUSY also introduces aquantum number called R-parity, where the standard model particles have Rparity of 1 and supersymmetric particles have an R-parity of -1. As R-parity
is conserved, the lightest SUSY particle cannot decay, and thus assumed to
be a stable particle and can be a very motivated candidate of dark matter.
In the early universe when the temperature was much higher than dark
matter mass, dark matter and other ordinary particles were in thermal equilibrium. However, after the universe was cooled down and expanded, dark
matter production and annihilation are no longer possible and such a state iscalled freeze-out. From [10], the relic density of dark matter can be expressedusingΩχ h2 ≃

3 × 10−27 cm3 · sec−1,< σA v >(1.6)

where < σA v > is the thermally averaged WIMP annihilation cross section.
If a cross section is < σA v >≃ 3 × 10−26 cm2 s−1 , typical of weak interaction,
the measured relic abundance of dark matter (Ωχ ) is well explained by thisnew particle.
6

1 Introduction
As WIMP is so motivated candidate, many experiments aim to detect
WIMP dark matter using diﬀerent techniques. In the next section, some ofsuch experiments are introduced.

1.3

Dark matter detection experiments

There are several approaches to detect dark matter but they can beroughly categorized into three groups.
• Collider experiments• Indirect searches• Direct searches

1.3.1

Collider experiment

Dark matter might be created using high-energy particle colliders such as
the Large Hadron Collider (LHC). If dark matter is created by the interactionof standard particle collisions, it leaves the detector without any signals.
Since energy-momentum should be conserved among all produced particles
including dark matter, apparently there must be a missing momentum in thedetector. Typically it would be observed as a mono jet or mono V (Fig. 1.6,[11]).
The advantage of collider search is that there is no lower limit to thedark matter masses to which they are sensitive. Also, it does not suﬀer
from astrophysical uncertainties that other detection methods have. On theother hand, the upper limit of dark matter masses is limited by collisionenergy. Additionally, even if such mono jet events are observed, it does notnecessarily mean that it is dark matter because such an invisible particle
might have a shorter lifetime compared to the age of the universe but longer
than the traveling time inside the detector.

1.3.2

Indirect search

In indirect dark matter search, we often observe γ rays or neutrinos fromdark matter annihilation. Since γ rays and neutrinos travel straight from thesource, it can be a nice probe of dark matter annihilation happening at highdark matter density locations.
First, we introduce dark matter search through neutrino observations [13].
Dark matter annihilation might happen at the center of the sun. Since the71 Introduction

Figure 1.6: (a) Feynman diagram of a jet event in colliders, q+q → χ+χ+jet.
Standard model particles such as γ, g, Z, W create a visible jet and dark
matter particles take invisible momentum. (b) Mono jet candidate in CMS
detector. The jet was produced to top left direction, thus there is missing
transverse momentum toward bottom (green arrow). Figure taken from [12].
sun is traveling through a dark matter cloud, although its interaction withnormal matter is small, there might be some amount of dark matter getting
trapped in the sun and it is possible that pair annihilation happens. By pairannihilation, heavy quarks or gauge bosons will be created and eventuallydecay into stable particles such as neutrinos. Such neutrinos travel straightto the earth so they can be detected using neutrino observatories such as
Super-Kamiokande and IceCube. Figure 1.7 shows some limits on thermallyaveraged dark matter annihilation cross section by neutrino observatories.
Gamma rays from pair annihilation are also a good probe of dark matter.
By observing galactic center, where there should be high dark matter density, using γ ray telescope such as Fermi LAT, Major Atmospheric Gammaray Imaging Cherenkov (MAGIC) Telescope, or Cherenkov Telescope Array(CTA), we might see a line of γ ray corresponding to the mass of dark matter.
Fermi LAT is a satellite telescope which can detect γ rays in the form of theelectron positron pair creation. On the other hand, MAGIC and CTA locate
on the surface of the earth. High energy γ rays cannot reach the surfaceof the earth but create electromagnetic showers when interacting with theatmosphere and charged particles in the shower generate Cherenkov lights,
which are detectable with surface telescopes. In both cases, the energy and81 Introduction

10-17
10

-19

10

<σA V> [cm3s-1 ]IceCube86 bb
Eur.Phys.J.C 77, 2017
+ IceCube86 W W
IceCube86 µ+µIceCube86 ν ν
ANTARES b b
arXiv:1912.05296+ ANTARES W W
ANTARES µ+µANTARES ν ν

SK bb+ SK W W
SK µ +µ -

-18

SK νν
-20

10

10-21

10-22
-23

10

10-24
-25

10

expectation for thermal relic scenario
-26

10

1

10

102

Mχ [GeV/c2]

3

10

104

Figure 1.7: Limits on thermally averaged dark matter annihilation crosssection using neutrinos. Figure taken from [14].
direction of the γ rays can be determined using the pattern and intensity ofthe signals. Although the observations have been performed for many years,
there is no clear evidence of dark matter from the γ rays yet.

1.3.3

Direct search

Direct search is an approach to detect the sign of rare interaction ofdark matter with ordinary matters in the laboratory. Since the XENON
experiment utilizes this detection approach, we focus a bit more on this.
We expect that the interaction of WIMPs with ordinary matters happensin the form of nuclear recoil. From [15], when dark matter interacts with aunit mass of ordinary matter, the recoil spectrum dR/dER per unit mass is9

1 Introduction
expected to bedR
R0 k0 1
(ER ) =
dER
E0 r k 2πv02∫

1f (⃗v , v⃗E )d3⃗v ,vmin <|⃗v |<vmax v(1.7)

where R0 is the recoil event rate per unit mass of the target (for v⃗E = 0 andvmax = ∞) and can be written as
R0 =2 N0 ρD
σ0 v0 ,
1/2
π
A MD

(1.8)

N0 is Avogadoro number, A is a mass number of target media, ρD is amass of dark matter per unit volume, MD is a mass of dark matter, σ0 isa“zero momentum transfer cross section” of target and dark matter, v0 is aparameter to describe the spread of dark matter velocity distribution, andf (⃗v , v⃗E ) is a velocity distribution of dark matter in the laboratory frame. It
is typical to write this distribution in the form of Maxwell distribution in therest frame of our galaxy and taking into account that the earth is moving
with velocity of v⃗E in this frame, we can describe f (⃗v , v⃗E ) asf (⃗v , v⃗E ) = e−(⃗v+v⃗E ) /v0 .
2

2

Next, k is a sort of normalization parameter and defined as∫
k = f (⃗v , v⃗E )d3⃗v .

(1.9)(1.10)

Note that only |⃗v + v⃗E | < vesc is allowed. This comes from the request thatdark matter is constrained in our galaxy and vesc is the escaping velocity inthe position of the earth, which is vesc = 544 km/s. k0 (= (πv02 )3/2 ) is k whenvesc = ∞. Then E0 = 1/2MD v02 is a typical kinetic energy of dark matter,and r is a dimensionless parameter which can be described asr=

4MD MT(MD + MT )2(1.11)

using dark matter mass MD and target atom mass MT .
Finally, we describe the parameters related to the integral range of 1.7.
The upper boundary vmax is a velocity limit coming from the requirementthat dark matter is constrained in our galaxy and the lower boundary vmin is
the minimum required velocity of dark matter to create recoil energy of ER
and can be written as vmin = (ER /E0 r)1/2 v0 .

10

1 Introduction
Next, we will simplify equation 1.7 to quickly see the shape of the recoil
spectrum. We assume that v⃗E = 0 and take vmax to infinity. Then equation
1.7 can be easily integrated and we obtaindR
R0 −ER /E0 r(ER ) =
e
.
dER
E0 r

(1.12)

Obviously, the energy spectrum decreases exponentially and this is still almost true when more precise corrections are taken into account.
We have been using the cross section σ0 between the target nucleus anda WIMP. However, it is useful to convert σ0 to the cross section between
a WIMP and nucleon, σn , in order to compare diﬀerent experiments using
diﬀerent target elements. Normally in case of spin independent scattering,
σ0 and σn has a relationship described as
σ0 ∝ σn · A2 ·

µ2A
,
µ2n

(1.13)

where µA is a reduced mass of target nucleus and WIMP, and µn is a reduced
mass of nucleon and WIMP. This implies that the experiment becomes moresensitive when the target elements are heavy.

Next, we will see the diﬀerent techniques of the direct dark matter searchexperiments. Although there are many diﬀerent techniques, the goal is thesame: how to detect rare and faint signals of WIMP recoils. Main detectablechannels can be classified into three: heat, light, and charge. Detectors use
one or more of these channels to detect WIMPs and reject possible backgrounds (Fig. 1.8).
We can identify backgrounds caused by γ or β rays because they interact with the electrons of the target. However, neutrons interact with thetarget nucleus via nuclear recoil and thus, they are indistinguishable from
WIMP recoils when neutron interaction happens only once in the detector.
To reduce neutron background, dark matter detectors are usually in underground laboratories because rocks around the underground laboratories stopcosmic muons and consequently reduce the muon induced neutrons. Figure
1.9 shows the depth and muon flux of underground laboratories in the world.
Currently, many experiments are ongoing to grasp the sign of dark matter.
Figure 1.10 shows a summary of results from recent direct dark matter detection experiments. The figure shows the limits on spin-independent WIMP
nucleon cross section as a function of the WIMP mass. Green shaded parameter space is excluded at 90% confidence level. The regions labeled as
11

1 Introduction

Figure 1.8: Diﬀerent energy deposit channels used for dark matter searches.
Experiments utilize one or more of these channels to detect dark matter.
Figure taken from [16].
”DAMA” are preferred parameter space by DAMA/LIBRA’s annual modulation search [18] but many other experiments presented negative results.
Although there are many techniques to search for dark matter, liquid
xenon is attracting attention as a promising detection media. Here are somereasons why liquid xenon has advantages in searching for dark matter. First,
its higher atomic number makes the cross section in equation 1.13 larger andthus more sensitive. In addition, a higher density of liquid xenon stops γ
rays from outside eﬀectively and makes the inner volume of the detector low
background. Combining with position reconstruction, we can define fiducial
volume to reduce backgrounds. Moreover, since liquid xenon is fluid, we cancirculate it to remove impurities such as Kr and Rn further (more details inlater chapters). In the case of solid detectors such as solid scintillators, wehave to be extremely careful when growing crystals because impurities inside
can never be removed after crystals are formed.
There are mainly two methods of liquid xenon dark matter detection, one
is single phase and the other is dual phase detector. XMASS has been search12

1 Introduction

Figure 1.9: Neutron flux in the underground laboratories. Deeper the laboratory, less neutron flux. Figure taken from [17].
ing for dark matter using single phase technique [21]. Dual phase technique
is utilized by XENON1T [22], LUX [23] and PandaX-II [24] experiments, andthey are at the leading position in the WIMP search (Fig. 1.10). Their successors, XENONnT [25], LUX-ZEPLIN [26] and PandaX-4T [27], are planned
and aim to improve their sensitivities to WIMP dark matter by more than
one order of magnitude. The competition toward WIMP detection is very
fierce now.

1.4

From XENON1T to XENONnTIn this section, we compare XENON1T and its upgrade, XENONnT
which the author is working on, although more details are described in thenext chapter. It emphasizes what makes the XENONnT sensitivity muchbetter than XENON1T and how the work presented in this thesis is related
to it. Detector parameters are taken from [22, 25, 28].
The XENONnT experiment aims to probe WIMP dark matter with thesensitivity to spin-independent WIMP-nucleon cross section of 1.4 × 10−48
cm2 at 50 GeV/c2 WIMPs and the following factors are crucial to achieve
the highest ever sensitivity: larger exposure, lower background and stronger
electronic recoil event discrimination power. Table 1.1 compares those factors
13

1 Introduction

Figure 1.10: Current limits on spin independent WIMP nucleon cross section. Dashed line represents the neutrino floor [19], where neutrino coherent
scattering with the target nuclei becomes irreducible background. Figure
taken from [20].
for XENONnT and XENON1T. It is worth mentioning that both experiments
are in a background-limited regime at the exposures shown in the table.
First of all, XENONnT plans to have 20 times larger exposure thanks to
the larger detector (4 t of fiducial mass) and longer exposure (5 y). The next
one is an electronic recoil (ER) discrimination power. In the detector such as
XENONnT, ER events (the main source of background) can be distinguishedfrom nuclear recoil (NR) events (recoil type of WIMPs) as shown in Fig.
1.11. Using two observables of the experiment, scintillation photon (S1) andcharge (S2), ER (red) and NR (black) are separated from each other (moredetails in section 2.1). The degree of ER/NR discrimination can be evaluatedwith a parameter called ER discrimination power. It is defined as a fractionof ER events that stay above the median of NR band (black line in Fig.
1.11) in the range of interest (S1 in [3,100] PE). Although we do not define
event window to search for dark matter (or estimate sensitivity) but use
the profile likelihood method with the expected S1-S2 distributions of signal
and background as inputs, it can be a benchmark to evaluate the ER event
leakage and from Table 1.1, we can roughly say that ER background rate issuppressed by a factor of three by stronger discrimination power comparedto XENON1T.
14

1 Introduction
Table 1.1: Main factors that determine the sensitivity of the experiment.
XENON1T is also shown for comparison. The ER discrimination power isdefined as a fraction of ER events that stay above the median of the NR
band. The ER background rate is calculated in between [1,13] keV recoil
energy.
XENONnT
XENON1T
Exposure (fiducial mass × time)
4 t × 5 y 1.3 t × 0.77 y
ER discrimination power [%]
99.9
99.7
−1 −1 −1
ER background rate [keV t y ]
12.3
76
2
2
−48
−47
Sensitivity (50 GeV/c WIMP) [cm ] 1.4 × 10
3.6 × 10The last one is an absolute rate of the ER background. Although there is
an NR background as well, the ER background dominates the total budget ofbackground in XENON1T/nT even after taking into account the discrimination power. Therefore we only focus on the ER background and the rate was
76 events keV−1 t−1 y−1 for XENON1T and it is expected to be 12.3 events
keV−1 t−1 y−1 for XENONnT in the electronic recoil energy range of [1,13]
keV (no discrimination considered). This is about a factor of six reduction
and it is mainly driven by a reduction of 222 Rn activity, from 13 µBq/kg(XENON1T, 83% of total ER rate) to 1 µBq/kg (XENONnT, 37% of total
ER rate) in the liquid xenon target. Due to its 3.8 d half-life, 222 Rn emanated from every detector material surface can reach the sensitive volumeof the detector and subsequent β decay of its progeny, 214 Pb, can be a significant ER background. The reduction of 222 Rn can be realized thanks tointense eﬀorts to mitigate it such as material screening [29] and novel radon
distillation (section 2.6.4).
The high discrimination power, 99.9%, and low radon rate, 1 µBq/kg, arenecessary to reach the projected sensitivity of 1.4 × 10−48 cm2 (50 GeV/c2
WIMPs) with 20 t y exposure and the work presented in this thesis is related
to both of them. For ER discrimination, the electronegative impurities are
responsible for its deterioration, because such impurities capture drift electrons which eventually become the S2 signal of the detector. The reductionof electrons is characterized by a parameter called electron lifetime (definition in section 3.1.1), which is a typical time-scale of electron attenuation
due to the capture by impurities. A longer electron lifetime means better
purity and less attenuation, and thus, higher resolution and discrimination
power. If we assume the same electric field as XENON1T, it is necessary tohave about 3 ms of the electron lifetime to achieve 99.9% of discrimination
power, therefore the target electron lifetime is set to be > 3 ms. On the

15

10

Charge Signal (log (S2 [PE]))

1 Introduction

4

3.5

3

2.5

2

1.5

10

20

30

40

50

60

70
80
90
100
Scintillaiton Signal (S1 [PE])Figure 1.11: Demonstration of ER discrimination. Red points are from ER
and black points are from NR. Black line is a median of NR distribution
which defines the ER discrimination power.
other hand, XENON1T could only reach about 660 µs of the electron lifetime and we expect to reach an even worse electron lifetime (expected to bearound 400 µs) if we use the existing purification system (section 2.6.1) only
because of the larger xenon mass. If we reach only 400 µs of the electron
lifetime in XENONnT, the corresponding discrimination power is 99.2% and
the WIMP sensitivity deteriorates by a factor of three (see section 3.1.2).
The novel purification technique presented in this thesis would purify xenon
much more eﬃciently and realize the target electron lifetime and eventually
the projected WIMP sensitivity.
Since it is also important to reduce the absolute ER background rate toachieve high sensitivity, the new purification technique should not have alarge 222 Rn emanation rate. Unfortunately, the purification technique withthe same concept, circulation/purification in the liquid phase, utilized impurity removal filters with a huge 222 Rn emanation rate and is not suitable forlow background experiments such as dark matter search. The establishmentof low 222 Rn emanating purification method helps to achieve the projected222
Rn rate, 1 µBq/kg, which is also necessary to realize the projected sensitivity. The target radon emanation rate of the filter was set to be < 1 mBq
so that the contribution from the filter becomes subdominant compared to16

1 Introduction
the total emanation rate of the entire XENONnT system (see section 3.5).
To summarize, the novel purification technique presented in this thesis is
crucial for probing WIMP dark matter with a sensitivity of 1.4 × 10−48 cm2(50 GeV/c2 WIMPs, XENONnT projected sensitivity). Without this work,
the sensitivity is expected to deteriorate by a factor of three compared to theprojected sensitivity. In the next chapter, details of the XENONnTexperiment are described and the following chapters explain topics more related to
the novel purification technique such as design, commissioning test results,
and full-scale purification in XENONnT.

17

Chapter 2
XENONnT experiment
XENONnT was constructed at Laboratori Nazionali del Gran Sasso (LNGS)
as a successor of the XENON1T experiment, which recorded the highest sensitivity to WIMP dark matter to date. It is expected to improve its sensitivity by another order of magnitude to grasp the sign of dark matter. In thischapter, we will see the details of the XENONnT experiment.

2.1

Detector principle

XENONnT detector is categorized as a dual phase xenon Time Projection
Chamber (TPC). In this section, the working principle of TPC is summarized.
The detector typically has a cylindrical shape and its side is surroundedby polytetrafluoroethylene (PTFE) reflectors. The top and bottom of thecylinder are covered with arrays of photomultiplier tubes (PMTs) to detect
light signals. Liquid xenon is filled inside the cylinder up to a certain level
and thus it contains gaseous xenon at the top part. This is the reason why
we call “dual phase” xenon TPC. The electric field is applied inside the TPC
to drift free electrons. Schematic drawing of TPC is shown in Fig. 2.1.
When WIMPs, as well as background particles (β, γ, neutrons, etc.),
deposit energy in a liquid xenon medium, the energy takes the form of heat,
scintillation, and ionization. Although heat is undetectable in this type ofdetector, scintillation and ionization can be detected.
Scintillation photons in xenon are produced in two processes [31]. The
first process starts with excited xenon atoms (Xe*) and follows the process
in equation 2.1.
Xe∗ + Xe + Xe → Xe∗2 + Xe
Xe∗2 → 2Xe + hν
18

(2.1)

2 XENONnT experiment

Figure 2.1: TPC working principle. TPC typically has a cylindrical shapeand there are PMT arrays to detect light signals. There is an electric field
inside the TPC to drift electrons. Deposited energy is detected in the formof light (S1) and charge signals (S2) and its interaction point is determinedby the S2 pattern (horizontal) and the time diﬀerence between S1 and S2.
Figure taken from [30].
The second process involves the ionized xenon atoms Xe+ and its recombination as in equation 2.2.
Xe+ + Xe + Xe
−
Xe+
2 +e
Xe∗∗
Xe∗ + Xe + Xe
Xe∗2

→
→
→
→
→

Xe+
2 + XeXe∗∗ + Xe
Xe∗ + heatXe∗2 + Xe
2Xe + hν.

(2.2)

Both processes generate photons through de-excitation of Xe∗2 and its
wavelength is 178 nm [32]. They are produced at the position of the interaction and detected by the top and bottom PMT arrays. To enhance the lightyield, the surrounding PTFE wall serves as a reflector. This signal is called
S1 as in the left part of the Fig. 2.1.
The other detection channel is ionized electrons. When particles interact
with a xenon atom, nearby xenon atoms get ionized and thus emit electrons.
19

2 XENONnT experiment
A fraction of those electrons can be drifted by the electric field in the TPC
before recombination with xenon ions nearby. Drift electrons reach the surface of the liquid and are extracted to the gaseous phase and accelerated
at the anode electrode to generate proportional scintillation light called S2.
The process is illustrated in the right part of Fig. 2.1.
Using S1 and S2 information, we can reconstruct the 3D position of theinteraction. The depth z can be estimated by z = td /v, where td is thetime diﬀerence between S1 and S2 (drift time), and v is the drift velocity ofelectrons in the liquid xenon at a given electric field. The drift velocity ofelectrons in liquid xenon is shown in Fig. 2.2. For example, ≈ 1.5 m TPC
has a maximum drift time of ≈ 1.2 ms when the electric field is around 100
V/cm. Horizontal (x-y) position reconstruction can be done by looking at thepattern of S2 signals observed by the top PMT array. Top PMTs near the x-y
position of the interaction tend to detect more photons compared to PMTs
far away from the interaction point. In XENON1T, position reconstruction
resolution was better than 1 cm for S2s larger than 1000 photoelectrons (PEs)[33].

3This work, T=184 K
EXO-200, 167 K

Electron drift velocity [mm/µs]

2.5

LUX, 175 K

2

1.5

1
XENON10, 177 K
XENON100, 182 K

0.5

Miller et al, 163 K
Gushchin et al, 165 K

0
10−2

10−1

1

10

Electric field [kV/cm]

Figure 2.2: Relationship between electric field and electron drift velocity inliquid xenon. Figure taken from [34].
The most important feature of S1 and S2 is that we can use them to reject
electron recoil (ER) events from nuclear recoil (NR) events. This directly
leads to strong discrimination of background events from WIMP candidates20

2 XENONnT experimentbecause WIMPs are expected to interact with xenon via NR and other major
background sources interact via ER. Figure 2.3 shows the result of 220 Rn (forlow energy ER), AmBe (for low energy NR) calibration, and the science dataof dark matter search in XENON1T first run. The ER band and NR band
are clearly separated and ER exclusion rate was 99.6% when NR acceptance
wa 50% [35]. The diﬀerence of response to ER and NR are coming frommicrophysics of liquid xenon and summarized in articles such as [36].

21Corrected S2 bottom [PE]2 XENONnT experiment

8000

10

8

keVee

4000

12

2000
1000
400
200

(a) 220 Rn calibration

100
1

8000

2

40

4

5

6

50

60

Corrected S1 [PE]

keVnr

4000

3

2000
1000
400
200

(b) 241 AmBe calibration

Corrected S2 bottom [PE]

100
10

5

8000

40

20

25

30

50

60

Corrected S1 [PE]

keVnr

4000

15

2000
1000
400
200

(c) Dark matter search

100
50

0 3

5

10

10

20

15

30

20

40

25

50

30

60

70

Corrected S1 [PE]Figure 2.3: Observed data in corrected S1 vs corrected S2 bottom space.
The corrected S1 is S1 signal corrected by its position dependence. The
corrected S2 bottom is S2 observed with bottom PMT array with position
dependent corrections (see appendix B). (a) Beta ray events from 212 Pb in
220
Rn calibration. (b) Neutron events from AmBe calibration. (c) Data indark matter search runs. Lines indicate the median (solid) and ±2σ (dotted)
quantiles of event distributions. Red lines are for NR and blue lines arefor ER. ER and NR bands are separated from each other and useful forbackground rejection. The purple distribution in (c) indicates the 50 GeV/c2
WIMP signal model. Figure is taken from [35].

222 XENONnT experiment

2.2

XENONnT infrastructure overvirew

In this section, we will see the overview of the XENONnT infrastructure and in the following sections, more details about each subsystem are
explained.
The XENONnT experiment is operated in the Hall B of the undergroundlaboratory of LNGS. The XENONnT infrastructure is roughly divided into
three regions (Fig. 2.4).
• Water tank
• Service building• Outside the service building
In the center of the water tank, there is a cryostat that accommodates
TPC. Some veto systems and external calibration systems are also present
in the water tank. On the ground floor of the building, there is a Kr distillation system, liquid xenon purification system and a xenon storage systemcalled ReStoX-1. On the middle floor of the building, there are all DAQ
and slow control systems. On the top floor, we have a cryogenic system,
gas xenon purification system, Rn distillation system, and internal source
calibration system. We have a new storage system called ReStoX-2 outsideof the building.

2.3

XENONnT TPC

The principle of TPC is already described in this chapter so we focus
more on the specific features of the XENONnT TPC.
Figure 2.5 is the drawing of the XENONnT TPC. TPC is accommodated
in the double-walled stainless steel cryostat. The active region of the TPC
is surrounded by 24 PTFE reflector panels. On the top and the bottom of
the TPC, there are PMT arrays which have 253 and 241 3-inch Hamamatsu
R11410-21 PMTs respectively. Those PMTs have low radioactivity [37] andhigh quantum eﬃciency for xenon scintillation of 178 nm wavelength [38, 39].
PMT positions are arranged in a compact hexagonal structure to maximize
light collection eﬃciency (LCE). The dimension of the TPC is about 1.5 mtall and 1.3 m in diameter and the amount of xenon necessary to fill thecryostat is about 8600 kg although we can only keep about 5900 kg in theactive volume of the TPC. Thanks to the high stopping power of liquid xenon,
we expect to have about 4 t fiducial mass.
23

2 XENONnT experiment

Figure 2.4: The XENONnT infrastructure in the Hall B of the undergroundlaboratory of LNGS. In the back of this picture, there is a water tank. In
front of the water tank, there is a three-floor service building, and there is anarea outside the building as well which hosts a new storage system. Picture
credit: Kai Martens (Kavli PMU, University of Tokyo)
We have several electrodes to create drift field in the TPC (Fig. 2.6). The
main drift region is in between two electrodes, cathode and gate. The gate
is located a few mm below the liquid surface and the cathode is located 1485
mm below the gate. There are many field shaping rings between the gate andcathode to create a drift field. The anode electrode is located in the gaseous
phase, 8 mm above the gate. A strong electric field between the gate andanode (order of kV/cm) extracts drift electrons from liquid to gas. Finally,
we have top and bottom screening electrodes next to the top and bottom
PMT arrays to protect the PMTs from the field produced by the anode andcathode.
Finally, we have to keep the liquid surface level stable in between the gate
and anode to achieve reliable electron extraction. We utilize the technique24

2 XENONnT experiment

Figure 2.5: The XENONnT TPC. The dimension of the TPC is about 1.5
m tall and 1.3 m in diameter. Detailed explanations are in the main text.
Figure taken from [25].
of diving bell to control the liquid level. By controlling the pressure of thevolume inside the bell, we can actively control the level of liquid.

2.4

Water tank

We have a TPC in a water tank to reduce backgrounds further (Fig. 2.7).
Both height and diameter of the water tank are approximately 10 m. It cancontain Gd loaded water and eﬀectively protects TPC from environmental
γ rays and neutrons in the experimental hall. Previously, it was typical tocover the detector with Pb blocks but in recent large scale experiments, it ismore common to put the detector in the water shield, pioneered by XMASS[40].
The water tank has several additional roles and they are discussed in thefollowing subsections.
25

2 XENONnT experiment

Figure 2.6: Configuration of the XENONnT TPC electrodes.

2.4.1

Muon veto

The water tank is equipped with 84 PMTs deployed on the lateral walls
and serves as an active Cherenkov muon veto (Fig. 2.7). The inner surfaceof the water tank is covered with reflective foil. We can reject muon eventswith eﬃciency of ϵ > 99.5% and muon induced neutrons with eﬃciency ofϵ > 70 %[41]. This system already existed in XENON1T and is reused in
XENONnT.

2.4.2

Neutron veto

Neutron veto is a new sub-detector in XENONnT and constructed in thewater tank surrounding the cryostat. The system consists of ePTFE reflectors
surrounding the cryostat and 120 PMTs mounted on it, as seen in Fig. 2.7.
Moreover, 0.2% of gadolinium (0.5% of gadolinium sulfate octahydrate) will
be dissolved in the water tank because Gd has a large cross section withneutrons and emit 8 MeV γ rays after neutron capture. This technique was
first developed by EGADS [42] for Super-Kamiokande.
Neutrons can be a dangerous background of the WIMP search. Since
neutrons interact with xenon atoms via nuclear recoil, they cannot be distinguished from WIMP interaction when recoil only happens once in thedetector. Those neutrons escape the cryostat and are captured by Gd, thensubsequent γ rays are emitted. Those γ rays induce Cherenkov lights andthey are detected by PMTs after reflecting several times with ePTFE reflec26

2 XENONnT experiment

Figure 2.7: We have muon veto and neutron veto system in the water tankof XENONnT. Figure taken from [25].
tors. By using these signals, we can veto neutron single scatter events. It
is expected that neutron veto reduces neutron single scatter events by 87%[25], which corresponds to the neutron event rate from 0.321 (t·y)−1 to 0.041(t·y)−1 in the energy region of interest (ROI) and 4 t fiducial mass.

2.5

Cryogenic system

The cryogenic system already existed in XENON1T and is used unchanged for XENONnT. We have two redundant pulse-tube refrigerators(PTRs) to keep liquid xenon in the cryostat cold. Each PTR has about 250
W of cooling power [43] and we can stably operate the experiment with only
one PTR.
We also have a backup liquid nitrogen cooling system to keep the systemsafe in case of sudden pressure increase due to PTR failure, loss of vacuum
insulation, etc. The temperature of the liquid nitrogen cold finger is usually
set a few degrees above the liquefaction temperature of the liquid xenon
and when the system detects emergencies, the liquid nitrogen flows and thetemperature of the cold finger decreases quickly to reduce pressure.
To operate the experiment, we need to keep purifying the xenon in the27

2 XENONnT experimentcryostat (more details in the next section). One such system utilizes hotgetters, and therefore we need to evaporate and condense xenon gas to circulate xenon between the cryostat and the getters. By exchanging heat ofevaporation and condensation using a heat exchanger, it reduces a heat loadto the cryostat. The heat exchanger is 96% eﬃcient and reduces heat input
to 0.39 watts per standard liter per minute (slpm) [44].

2.6

Purification system

We need to keep purifying xenon for several reasons and there are dedicated subsystems.

2.6.1

Gas purification

To enhance the performance of the TPC, we need to have a good lightyield. Water is the main contaminant in liquid xenon which absorbs scintillation light emitted by xenon atoms. In addition, in order to have a good S2yield even from the deepest part of the detector, we also need to have a reasonably low level of electronegative impurities such as oxygen because suchmolecules capture drift electrons and reduce the size of S2 signals. Those
contaminants are constantly supplied into liquid xenon as outgassing so continuous purification is necessary. Gas purification system removes such kindof impurities and has been used since XENON1T.
The left part of Fig. 2.8 is a schematic drawing of XENON1T/nT gas
purification system. A magnetically coupled piston pump [45], which has a
low radon emanation rate, extracts xenon from the liquid and gaseous phaseof the cryostat. Extracted liquid xenon is evaporated by the heat exchanger
and flown into hot zirconium getters manufactured by SAES. The gettereﬃciently removes oxygen, water, oxide, carbide, and nitride. The purified
xenon returns to cryostat after being condensed by the heat exchanger. Thismode is called liquid phase gas purification (L/GXePUR). In addition, thissystem can extract xenon gas also from the gaseous phase of the cryostat(G/GXePUR) simultaneously. The maximum circulation rate was about 85
slpm, which was achieved during Science Run 2 of XENON1T (R&D phaseof XENON1T following the main data taking period).

2.6.2

Liquid purification

From the experience of XENON1T, we were sure that the existing gas
purification system was not fast enough for even bigger detectors such as28

2 XENONnT experiment

Figure 2.8: The XENOnT purification system. (Left) The gas purification
system purifies xenon in the gaseous phase. Xenon can be extracted bothfrom the liquid and gaseous phases of the cryostat. (Right) New liquid xenon
purification purifies xenon in the liquid phase.
XENONnT. A liquid purification system is newly developed for the XENONnT
experiment to enhance the purification speed.
As shown in the right side of Fig. 2.8, this system circulates xenon in
the liquid phase only. Taking advantage of the fact that the density of liquid
xenon is approximately 500 times larger than that of gaseous xenon, by circulating liquid xenon with 2 L/min flow rate, we may achieve a gas-equivalentcirculation speed of 1000 slpm. This concept has already been realized insome noble liquid experiments such as MEG (removing water from xenon[46]) and ICARUS (removing water and oxygen from argon [47]). However,those experiments used filter materials that typically emanate a huge amountof 222 Rn which is the biggest source of background in XENONnT. In orderto realize this concept in low background liquid xenon experiments, it wasnecessary to find a way to eﬃciently remove electronegative impurities suchas oxygen in liquid xenon while having low radon emanation. Such an R&D
is the main content of this thesis and is described in the following chapters.
Additionally, in XENON1T, we learned that cleaning the gaseous phaseof the detector (G/GXePUR) is very important to keep liquid xenon pure.
Since detector materials that touch the gaseous phase have a higher temperature, there is more outgassing and those outgassing molecules can dissolve
into the liquid. Therefore purifying the gaseous phase of the detector indirectly purifies the liquid phase. However in XENON1T, we needed to share29

2 XENONnT experiment
the limited flow speed of the gas purification system by L/GXePUR and
G/GXePUR, and thus faster purification of G/GXePUR meant to sacrifice
the speed of L/GXePUR. If we have a liquid xenon purification system in
XENONnT, since it has an overwhelmingly faster speed compared to gas
purification, we can use the gas purification system for cleaning the gaseous
phase without sacrificing liquid phase purification speed.

2.6.3

Kr distillation

Ambient krypton nat Kr contains β decay isotope 85 Kr (10.76 y half life)
with natural abundance of 10−11 . Commercial xenon contains nat Kr with
about 1 ppb (parts per billion) to 1 ppm (parts per million) level, thus 85 Kr
also exists in our xenon and becomes a source of background [48]. To remove
85
Kr, there is a krypton distillation column [49] in the XENON infrastructure,
which was originally developed by XMASS [48]. Since Kr has lower boilingpoint compared to xenon, after the distillation process, Kr concentrates ingas phase and removed as oﬀ-gas. This system is used when we first remove
Kr from the commercial xenon bottles but can also be operated during stable
operation periods as an online distillation. In XENON1T, the achieved Kr
level was nat Kr/Xe = 0.66 ± 0.11 ppt (parts per trillion) [22] and the targetof XENONnT is Kr/Xe = 0.1 ppt [25].

2.6.4

Rn distillation

As you will see in section 2.8, 222 Rn is the main source of background in
XENONnT. To be more precise, a 214 Pb, one of daughters of 222 Rn (Fig. 2.9),
decays via β emission, and can be a background. Since 222 Rn has a relatively
long half-life of 3.82 days, 222 Rn is emanated from detector materials and caneasily reach the sensitive volume of the detector. Intense screening eﬀorts
enabled the reduction of 222 Rn emanation from the material surface. Moreover, in XENONnT, a new system called Rn distillation is installed. The
principle of the system is essentially the opposite of Kr distillation. Since Rn
has a higher boiling point compared to xenon, after the distillation process,Rn atoms concentrate in the liquid phase and stay in the liquid until they
decay. This system is used online and aims to reduce 222 Rn activity of thedetector to 1 µBq/kg. This concept is already demonstrated in XENON100[50] and XENON1T.

30

2 XENONnT experiment

Figure 2.9: Decay chain of 222 Rn and its daughters. Since β ray from 214 Pb
is a dominant background of the experiment, we want to remove 222 Rn as
much as possible. Figure taken from [51].

2.7

Calibration system

We have several calibration sources in XENONnT. We can roughly divide them into two: internal and external calibration. Internal calibration
introduces source isotopes inside the detector while external calibration puts
sources in the water tank near the cryostat.

2.7.1

Internal calibration

Thanks to the high self-shielding ability of liquid xenon, we can obtaina volume with low background at the center of the detector. However, thismakes calibration from outside more challenging because radiations from thesource cannot reach the inner volume of the detector eﬃciently. To perform
31

2 XENONnT experimentuniform calibration of the entire detector volume, we have internal calibration
sources. We list three important sources : 83m Kr [52], 220 Rn [53] and 37 Ar. Allof the sources are installed in the gas purification loop and they are exposed
to gas flow only when we want to use them.
83m
Kr (half-life: 1.8 h) is a daughter nucleus of 83 Rb and it decays into
the ground states with the emission of 32.1 keV and 9.4 keV conversion
electrons. 83m Kr is introduced into the system and spread uniformly in thesensitive volume of the detector. It enables low energy and monoenergetic
ER calibration of the detector. It is also useful to characterize detector
properties such as xenon purity, light correction maps, field distortions, etc.
220
Rn (half-life: 56 s) is emanated from 228 Th source and introduced in
the detector with the same manner as 83m Kr. Subsequent decays of 220 Rn
include many decay modes (α, β, γ) and are useful for diﬀerent calibration
purposes but probably, the most important decay in this chain is β decay of212
Pb. Since the Q value of the decay is 560 keV, this can be used to calibrate
the low energy ER response of the detector and we can determine the low
energy ER band shape. The time scale of this decay chain is determined by
212
Pb, which has a half-life of 10.6 h. Therefore after isolating 228 Th source,
the activity becomes negligible within a few days.
37
Ar decays via electron capture and releases x-rays from the captureof the K-shell, L-shell electrons at 2.8224 keV and 0.2702 keV [54]. Those
x-rays produce ER and can be used for very low energy calibration. In
2020, XENON1T reported unexpected low energy ER event excess at a few
keV [55]. This excess could be due to new physics such as solar axions but
the tritium background hypothesis is also not excluded. One of the main
purposes of the first run of XENONnT is to further investigate this excess
and thus precise understanding of detector response at such low energy isvery important. The concept of 37 Ar calibration is demonstrated in [54] andalso tested in XENON1T. Although 37 Ar has a relatively long 35 d of half-life,
it can be eﬀectively removed by distillation process as Kr.

2.7.2

External calibration

Although it is not eﬀective to calibrate the detector from outside, we havea few of such calibrations. They are guided along belts around the cryostat.
The most important external calibration is NR calibration using neutrons.
As WIMP recoil is expected to be NR, we have to know precisely the responseof the detector to NR through neutron (n) calibrations.
First calibration source is a neutron generator [56]. This utilizes thenuclear fusion of two deuteriums to generate neutrons (equation 2.3) andgenerated neutrons have 2.2 MeV and 2.7 MeV energy peaks.
32

2 XENONnT experiment2

D + 2 D → 3 He + n(2.3)

By tuning the parameters of the device, the neutron rate can be varied from
10 n/s to 107 n/s. Another neutron source is AmBe. Using α rays from241
Am and (α,n) reaction of Be atoms, we can obtain fast neutrons. For
external ER calibrations, we have γ sources such as 228 Th and 137 Cs.

2.8

Background sources of XENONnTExpected background sources for WIMP search in XENONnT is summarized in [25]. Figure 2.10 shows the recoil energy spectrum of background in
the ROI.

Figure 3: Energy spectra of the ER and NR backgrounds in the 4 t fiducial volume of the XENONnTFigure2.10:
Energyspectra to
ofthe
the
ERsearchand energy
NR backgrounds
4 tERsfidudetector.
Unshadedareas correspond
WIMP
ROI: (1, 13) and (4,in50)thekeV forNRs, respectively.
(Left)The largest detector.
ER backgroundUnshaded
is due to the 1regionµBq/kg activity
concentration
cialandvolume
ofthe
XENONnT
shows
the
WIMP
of 222 Rn (orange line). Additional backgrounds arise from solar neutrinos(green), double-beta decay
222
85
searchROI.
The
background
comes
from
Rn. ForNR,
theof 136 Xe(blue),
Krlargest(red) due ER
to a 0.1
ppt concentrationof nat Kr,
double-electron
capturein 124
Xe big124(olive),anddetector
components(purple).
A
GaussiansmearingoftheXe
spectrum,
based
on
the
contribution comes from radiogenic neutrons and CEνNS of neutrinos. Atm
XENON1T energy resolution [48], is shown in dotted lines. The total ER spectrum (solid black line)
andis used
DSN
standtheforfinalatmospheric
neutrinos
diﬀusesupernova
neutrinos
to produce
ER background model
presentedandin section
5. (Right)
The NR backgroundcontributions
come
from
radiogenic
neutrons
(red)
and
CE⌫NS
of
solar
neutrinos(orange),
specificallyrespectively.
Figure taken from [25].
8B (dashed) and hep (dotted), atmospheric (dashed blue) and diﬀuse supernova neutrinos (dottedblue). The neutron spectrum accounts for the NV tagging eﬃciency.

For ER backgrounds, the largest contribution comes from 1 µBq/kg of
Rn and solar neutrinos follow. The overall rate is about 1/6 of XENON1T.
ForRadonNR, the big contribution comes from radiogenic neutrons and coherent
elastic neutrino-nucleus scattering222(CEνNS) of solar neutrinos.
Due to its 3.8 d half-life, the emanation of
Rn from detector materials results in a distribution
Background rate is integrated over
ROI and summarized in Table 2.1.
of 222 Rn and its decay products within the whole LXe volume. The most significant backgroundcontribution
is from thedecay
of 214 Pb the
into theground state of 214power
Bi, whichofoccurs
a beta-decay
Evenafter taking
intoaccount
discrimination
ER viaandNR, 222 Rn
with Q-value of 1.02 MeV. The branching ratio (BR) for this channel,
fromtheimported
ENSDF,
isis still
the largest source of background. Since 222 Rn is such a dangerous
10.9%. The shape of the beta spectrum at low energy reflects the calculation in ref. [49]. We neglect222

the contribution from 214 Bi beta-decay, as it can be identified by its short time separation from thesubsequent 214 Po alpha decay. In this study, we assume the XENONnT target 222 Rn concentration of
1 µBq/kg. This design goal is based on the 4.5 µBq/kg
33 level reached in XENON1T [20], ongoing radon
emanation measurements of new detector components (xenon recirculation pumps, radon distillation
column, TPC, inner cryostat, cables), and the estimated performance of the online radon distillation
column. The expected background rate due to 222 Rn is the largest contribution to the total rate in
the energy ROI (see table 3) and amounts to 4.6 (keV t y) 1 . We assign a 10% systematic uncertainty
to this prediction, driven by the uncertainty in the BR of the 214 Pb beta-decay [27, 50].

The radon isotope 220 Rn can similarly emanate from materials as part of the 232 Th decay chain.
The beta-emitting 212 Pb, product of this isotope, can contribute to background events at low energies.
In XENON1T, we measured a 220 Rn concentration relative to 222 Rn of ⇠ 0.3%. Assuming this relative
concentration, the corresponding rate of 212 Pb events is about 1% of that expected from 214 Pb. We

2 XENONnT experiment
background source, one of the important points of this thesis is to establish
a fast purification technique without big 222 Rn emanation.
Table 2.1: Integrated background rates in 4 t fiducial volume of XENONnT.
Table taken from [25].
SourceER background
Detector radioactivity
222
Rn
85
Kr
136
Xe
124
Xe
Solar neutrinos
Total
NR background
Neutrons
CEνNS (Solar ν)
CEνNS (Atm + DSN)
Total

2.9

Rate [(t y)−1 ]25 ± 355 ± 613 ± 1
16 ± 24±1
34 ± 1148 ± 7(4.1 ± 2.1) × 10−2
(6.3 ± 0.3) × 10−3
(5.4 ± 1.1) × 10−2
(1.0 ± 0.2) × 10−1

Sensitivity of XENONnTUsing background estimation of the previous section, the sensitivity of
XENONnT is calculated (Fig. 2.11, [25]). With the target exposure of 20
t y, the expected sensitivity to spin-independent WIMP-nucleon interaction
cross section reaches 1.4 × 10−48 cm2 for 50 GeV/c2 mass WIMP at 90%
confidence level. This value is more than one order of magnitude lower thanthe current best limit set by XENON1T. From the right figure of Fig. 2.11,
if the WIMP-nucleon cross section is just below the limit set by XENON1T,
we would have a 50% chance of observing 5σ excess after three months of
exposure (assuming 4 t fiducial volume).
Although the XENONnT detector is primarily designed to search for dark
matter, it is an urgent topic to test the unexpected ER event excess reported
by XENON1T, as mentioned in section 2.7.1. If solar axions were responsible
for the excess, it is expected that only a few months of XENONnT data
would exclude the tritium hypothesis with 3σ (Fig. 2.12) because of diﬀerent
spectrum shapes and lower ER background level of XENONnT.
34

2 XENONnT experiment

Figure 6:

Projections of the XENONnT sensitivity and discovery power in the search for spin-

Figure2.11: WIMP-nucleon
XENONnTcouplings.
sensitivity(Left)
Expectedspin-independent
independent(Left) curve.
Median 90%
CL exclusion
limit (blacksolid line) fora20ty
exposure,
with
the
1
(green)and2(yellow)bands.
The
current
strongest
limit,
WIMP-nucleon interaction cross section with 20 t y exposure.exclusion(Right)Senobtained with XENON1T2[3], is shown in blue. The gray dashed-dotted line represents the discovery
sitivity
50 GeV/cmass
WIMP
a function
exposure.
limit ofto
an idealized
LXe-based
experiment
withasCE⌫NS
as unique of
backgroundsource Figure
and a 1000takentyexposure
from[25].[70]. The improvement of the discovery potential with increasing exposure below that line
would be significantly slowed down by the atmospheric neutrino background. (Right) Sensitivity as
a function of exposure, for the search of a 50 GeV/c2 WIMP in the assumed 4 t fiducial mass. The
dashed (dotted) black lines in both panels indicate the smallest cross-sections at which the experiment
would have a 50% chance of observing an excess with significance greater than 3 (5 ). A two-sided
profile construction is214
used to compute the confidence intervals.

12

Pb: 1 Bq/kg (XENONnT goal)

214Pb: 3 Bq/kg
atmospheric neutrinos214and DSN (44%), due to the impact of the neutron-X population. A fraction of
Pb: 5 Bq/kg (achieved in SR2)
71% of the CE⌫NS PDF from solar neutrinos falls inside the reference signal region, even though it isconfined to very small cS1 and cS2b signals. Numbers in this portion of the observable space can only
give an indication of performance, but are useful for comparison with other detectors. The sensitivity
study presented below does not use any ER discrimination cut or specific signal region selection, but
it is based on the profile likelihood analysis in the full (cS1, cS2b ) observable ROI.
The neutron and CE⌫NS background rates are primarily constrained by ancillary measurements,
as discussed in section 4.3, and likelihood terms are included to account for the relative uncertainties
reported in table 4. On the other hand, even a short first run of XENONnT will constrain the ER
rate better than the 10% prediction uncertainty, therefore we do not include a related term in thelikelihood. Systematic uncertainties on the detector response to NRs primarily impact the search for
low-mass WIMPs. However, such uncertainties were sub-dominant in the XENON1T WIMP search
results and we therefore neglect them in this work.

10

Expected

8

5.2

6
4
2

Statistical model

The likelihood-based statistical modeling of the experiment uses an extended unbinned likelihood, L,with PDFs in x = (cS1, cS2b ):"#NY
X µc ( DM , ✓)L( DM , ✓) = Pois(N | µtot ( DM , ✓)) ·· fc (xi |✓) · Lanc (✓) ,(5.1)µtot ( DM , ✓)c
i=1P
where µtot ( , ✓) ⌘c µc ( , ✓) and the ancillary term Lanc is defined as

0

1

2

3

4

Exposure [t y]56

Y discrimination between solar axion and
Figure 2.12: The significanceof ⌘theLanc (✓)
Gaus(µ̂k | µk , ⇠k ) ,(5.2)
ktritium as a function of the exposureand the background level. This also
shows the scenarios with diﬀerent 214 Pb background rate. XENONnT goal is
1 µBq/kg and the lowest achieved value in XENON1T was 5 µBq/kg during
Science Run 2 (SR2) of XENON1T.– Figure
taken from [57].
15 –

35

Chapter 3
Liquid xenon purification
systemFirst, this chapter explains the importance of purity to achieve high sensitivity of XENONnT. Then, details of novel liquid xenon purification hardware are described. Although there are many contexts of purification in the
XENON experiment such as Kr and Rn removal (to reduce backgrounds),
from this chapter, we will focus on the removal of electronegative impurities
which capture drift electrons and deteriorate the detector performance.

3.1

Xenon purity

3.1.1

Electron lifetime

Electronegative impurities such as oxygen capture drift electrons and reduce S2 signal size. Electron lifetime τe is a parameter to quantify such a
reduction of drift electrons. The electron lifetime is defined as follows. Let
N (t) denote a number of free electrons in liquid xenon at time t [s] and Si [M](M = mol/L) denote a concentration of ith electronegative impurity. The
time derivative of N (t) follows
dN (t) = −Σi Ki Si N (t)dt,(3.1)

where Ki is an attachment rate [M−1 s−1 ] of ith impurity which shows its
aﬃnity to electrons (Fig. 3.1). Solving this diﬀerential equation, it is shownthat the number of drift electrons exponentially decreases with time,
N (t) = N (0)e−Σi Ki Si t = N (0)e−t/τe ,1
τe =· · · Electron lifetime,
Σi Ki Si
36

(3.2)
(3.3)

3 Liquid xenon purification system

Figure 3.1: Attachment rate of a few electronegative impurities in liquid
xenon (△ : SF6 , □ : N2 O, ◦ : O2 ). X-axis is drift field and y-axis isattachment rate. This figure shows that electron lifetime not only depends
on the concentration of impurities but also depends on electric field. Figure
taken from [58].
and the time constant τe is called electron lifetime. Liquid xenon with 1 ppb
of oxygen has approximately 300 µs of electron lifetime when the electricfield is 100 V/cm.
This thesis is entirely devoted to improving electron lifetime to achieve
the highest sensitivity of the experiment. We also assume that oxygen is the
only responsible electronegative impurities because it is the most abundant
electronegative molecule in the atmosphere.

3.1.2

Electron lifetime and sensitivity of XENONnTDue to electronegative impurities in liquid xenon, S2 signal size has drift
time dependence and the correction is necessary to evaluate the S2 signal
independent from the drift time. However, if the electron lifetime is shorter,a significant amount of electrons is lost during the drift and it requires larger
correction. In XENON1T, for example, only ≈ 35% of electrons generated37

3 Liquid xenon purification systemat the bottom of the TPC could reach the liquid surface. As a result, theresolution of the S2 band gets poorer, and electronic and nuclear recoil bands
overlap more (Fig. 3.2). Since the electronic recoil background discrimination
is based on the separation of those two bands, larger overlap means lower
sensitivity.
500 #

10000 #Figure 3.2: Overlap of electronic (red) and nuclear (black) recoil bands (50GeV/c2 WIMP) at τe = 500 and 10000 µs. X-axis is corrected S1 (cS1), which
is S1 signal size corrected with 3D position dependence. Y-axis is corrected
S2 bottom (cS2b), which is S2 signal observed by bottom PMT array andcorrected with electron lifetime and S2 horizontal position dependence. We
often use S2 bottom because it has less xy position dependence. Descriptions
about S1/S2 correction is summarized in appendix B. From this figure, we
can see that longer electron lifetime makes less overlapped bands and thus
better discrimination. Figure taken from [59], which was generated based on
XENON1T simulator.
The relationship between the electron lifetime and the WIMP sensitivity of XENONnT is discussed in [59]. For 50 GeV/c2 WIMP mass, the
XENONnT sensitivity improves as the electron lifetime gets longer but it
does not have a big impact when the electron lifetime is above 3 ms (Fig.
3.3). This is because the maximum drift time in the detector is about 1 ms
and if the electron lifetime is significantly longer than this, the reductionof drift electrons is not so relevant. So let us set a goal of the XENONnT
purification program to τe = 3 ms.
If we do not lose many electrons, we might benefit especially when we
search for low energy events. Searches for WIMPs with masses of < 10
GeV/c2 and coherent elastic neutrino-nucleus scattering (CEνNS) of solar 8 B
neutrinos [60] are good examples. Another example is S2 only analysis, which
successfully lowered the detection threshold of XENON1T further [61, 62].
38

3 Liquid xenon purification system

WIMP-nucleon Cross Section [cm2]100GeV.txt

10

10

− 47

− 48

10

2

10

3

10

4

Electron Lifetime [µ sec]

Figure 3.3: The sensitivity for 50 GeV/c2 WIMP as a function of electron lifetime with 20 t·y exposure of XENONnT. Sensitivity improves up to around3 ms but it does not have a big impact when electron lifetime is higher than
this. Green and yellow bands are 1σ and 2σ band, respectively. The sensitivity is calculated under the electric field of 81 V/cm (XENON1T field).
Figure taken from [59].
S2 only analysis does not require scintillation signals (S1s) but only uses
ionization signals and XENON1T searched for interactions with lighter dark
matter. In such events, only a small number of electrons is expected to begenerated, and thus we do not want to lose any electron signals. A longer
electron lifetime would be extremely helpful to improve the sensitivities of
those searches.

3.2

Liquid xenon purification system : overview

Figure 3.4 is a schematic view of liquid xenon purification system. It
mainly consists of four components: liquid pump, oxygen filter, purity monitor, and liquid xenon/liquid nitrogen heat exchanger. All the liquid flow
pipes (most of them are 3/4” tubes) have double-wall vacuum insulation andare wrapped with super-insulating mylar to reduce heat input from outside.
Flow rate is measured by a diﬀerential pressure measurement across a venturi tube. Figure 3.5 shows the picture of liquid purification skid. Two tall39

3 Liquid xenon purification system
containers that stand out the most are the outer vacuum vessels for liquid filters. We also see a purity monitor and liquid pumps. The following sections
describe each part of liquid xenon purification.

GN2

LN2

Figure 3.4: Schematics of the liquid xenon purification system. Liquid xenon
is drawn from the bottom of the cryostat by a pump and flown into a filter
to remove oxygen. In the flow path, there is a purity monitor which measures electron lifetime online. All the liquid lines have double-wall vacuum
insulation to reduce heat input from outside.

3.3

Liquid pump

We utilize a magnetically-coupled cryogenic liquid pump (BNCP-32C000) manufactured by Barber Nichols [63] to circulate liquid xenon. The
pump circulates liquid xenon with a volumetric flow rate of up to about 4
L/min in our system. Two redundant pumps allow us to continue the purification process in case of periodical maintenance. Changing the frequency ofthe pump along with proportional valve openings makes it possible to control
40: Liquid pump

: Particulate filter

LXe/LN2
Heat exchanger: Proportional valve

Purity monitor

Venturi: Valve: Oxygen filter

Cryostat

3 Liquid xenon purification system

Figure 3.5: Picture of a liquid purification skid.
the flow rate. This type of pump was used for the purification of noble liquids
in some experiments such as MEG (xenon, [46]) and ICARUS (argon, [47]).

3.4

Liquid nitrogen heat exchanger

Since the liquid purification system has positive heat input (for example,
heat from the liquid pump), we have a liquid xenon/liquid nitrogen heatexchanger to cool down liquid xenon. A part of liquid xenon drawn fromcryostat is flown into a heat exchanger loop and cooled down. The heat exchanger loop not only kills the heat input from the liquid purification system
but makes heat input negative and helps the refrigerator of the cryogenic
system. By changing the temperature of liquid xenon at the heat exchanger
from -99 to -103 ◦ C, we were able to gain more than 100 W of cooling powerin the cryostat.

41

3 Liquid xenon purification system

3.5

Liquid filters

The liquid filters are one of the most important parts of the system because they actually remove oxygen. However, since we did not know whichmaterial can eﬀectively remove oxygen while satisfying some requirements(reasonable filter eﬃciency, Rn emanation, etc), many tests were performed
in order to determine filter candidates and how to use them. At the downstream of the oxygen filter, a particulate filter is installed in order to catch
possible dust from the oxygen filter. Similar to liquid pumps, we have two
redundant filter vessels and this allows us to perform almost uninterrupted
purification processes. When one filter shows a sign of saturation with impurities, we can switch to the other filter and while using the other filter, we
can regenerate saturated one. In the following sections, details of each filter
candidate are described.

3.5.1

Q5

Figure 3.6 is a picture of Q5 commercial reagent (also known as BASF
Cu-0226 S) which is alumina pellet coated by copper. This candidate wastested in the purification of liquid argon [64]. The principle of oxygen removal
is essentially the oxidation of copper.
2Cu + O2 → 2CuO

(3.4)

When Q5 got saturated with oxygen, we can regenerate it by flowing argon
and hydrogen mixture gas.
CuO + H2 → Cu + H2 O

(3.5)

Regeneration was typically done under 200 ◦ C with 5 L/min Ar+H2 mixture
gas flow for about 90 minutes. After that, dry nitrogen gas was flown to cool
down the filter. Figure 3.7 is the picture during the regeneration. During
regeneration, we saw droplets of water from the outlet which indicated thatregeneration was really going on.
Thanks to the big surface area of alumina, Q5 is expected to remove alarge amount of electronegative impurity, but it has a huge 222 Rn emanation
because alumina typically emanates a large amount of 222 Rn. 222 Rn emanation measurement of this material was performed and we obtained O(100)mBq/kg. Since total radon emanation rate of XENONnT system is 35.7+4.5−5.9
mBq [29], acceptable 222 Rn emanation rate from the filter is set to be 1
mBq in order not to increase 222 Rn significantly from the filter. This meansthat we can use only about 10 g of Q5 at maximum. So we tested Q5 in
42

3 Liquid xenon purification system
the commissioning (see chapter 4) to understand the oxygen removal ability
especially when the amount is small.

Figure 3.6: Picture of the Q5 filter. In this picture, color of pellets is black
because it is oxidized. When it is regenerated, fresh copper appears at thesurface and it shows copper color.

3.5.2

St707

St707 (Fig. 3.8) is a non evaporable getter (NEG) material produced by
SAES Getters [65] whose nominal composition is zirconium, vanadium andiron. NEG is normally used to remove outgassing molecules in vacuum chambers or to purify gas and we have the same material in our gas purification
getters to remove impurities in xenon gas.
After the production of St707 at the manufacturer, the surface is coveredby a passivation layer and does not have reactivity. However, after it isheated up to around 350 ◦ C or higher (activation), the passivation layer
diﬀuses into the bulk and a fresh surface appears. The fresh surface of St707
43

3 Liquid xenon purification system

Figure 3.7: Q5 regeneration. Q5 is regenerated by flowing argon and hydrogen mixture gas while heating up the vessel to 200 ◦ C. Interestingly, we seecondensed water droplets from the outlet, which indicates that regenerationis really going on.
is very reactive that it can remove almost any kind of gas molecules except
for inert gases. Once the surface of St707 is saturated, we need to repeat theactivation process in order to diﬀuse the reacted surface into the bulk andgenerate a fresh surface again.
In the XENONnT liquid purification system, we tested this material asan oxygen removal filter in liquid. However, NEG material has never beenused in such a low temperature liquid as xenon. We did not know what is theoxygen removal eﬃciency as well as oxygen removal capacity. To understandthe characteristics of this filter, we also tested it at the commissioning (seechapter 4). The advantage of St707 is its low Rn emanation rate (0.24 ± 0.03
mBq per 3 kg getter material with a container [29]) because it is an alloy
made of metal only. The disadvantage is its cost (about 20,000 USD).

3.6

Purity monitor

A purity monitor (Fig. 3.9) is a device to monitor the electron lifetimeof liquid xenon online and is located inside the flow path of the liquid purification system. Such a device was developed in liquid argon experiments[66, 67] and the development of the purity monitor for XENONnT is discussed in [59]. The purity monitor is very important from many points of
view.
44

3 Liquid xenon purification system

Figure 3.8: Picture of St707 filter pellets.
• We did commissioning tests of the liquid purification system to understand the characteristics of liquid filter candidates. In the commissioning tests, we did not have TPC in the cryostat so the purity monitor was
the only device to know the electron lifetime. Without it, we cannot
get any information from the tests.
• Even in the XENONnT commissioning with TPC in the cryostat, without the water tank filled, we cannot estimate the electron lifetime using
TPC because of the large amount of high-energy γ-ray background fromthe environment. The purity monitor enables us to know the purity ofxenon even in the early stage of the experiment and makes decisions
easier.
• By observing the trend of electron lifetime, we can tell when to regenerate/reactivate the filter.
• In case of a sudden drop of electron lifetime, we can detect it quickly.
• In XENONnT, data from TPC is processed online so that we can analyze it immediately. To correct the vertical position dependence of
S2 signal size, the electron lifetime is necessary. Electron lifetime frompurity monitor can be used for the online correction as an approximate
value, and for more matured analysis, we can use the electron lifetime
obtained by the oﬄine analysis of TPC data.
45

PRODUCED BY AN AUTODESK STUDENT VERSIONPRODUCED BY AN AUTODESK STUDENT VERSION

3 Liquid xenon purification system

PRODUCED BY AN AUTODESK STUDENT VERSION

Figure 3.9: Picture (left) and drawing (right) of the purity monitor. Drawing
shows drift region inside as well.
• There was a discrepancy between the electron lifetimes from radonalphas and 83m Kr [33], but the reason is not yet understood. The
purity monitor could give another insight into this problem.

3.6.1

Working principle

The working principle of the purity monitor is described in Fig. 3.10. The
purity monitor is essentially a liquid xenon drift chamber with about 20 cm
drift length. Pulsed UV light (10 Hz) from a xenon flash lamp generates
photoelectrons from a gold photocathode on a cathode and drifted throughthe field cage. The electronegative impurities in xenon capture drift electronsand only a fraction of electrons can reach an anode. By measuring charge
at the cathode (QC ) and anode (QA ) and drift time (td ), we can calculate46

3 Liquid xenon purification systemelectron lifetime τe using
τe =

−td
.
log(QA /QC )(3.6)

In real measurements, we averaged 200 waveforms before calculating cathode and anode charge in order to reduce noises, and Fig. 3.11 shows such
waveforms. To calculate the height of each pulse as well as the time diﬀerence
between them, waveforms are fitted independently using
f (t) = a0 + a1 t +b0exp(−(t − b2 )/b3 ).
1 + exp(−(t − b2 )/b1 )(3.7)

First, we fit the period before the pulse with linear function (obtain a0 anda1 ), then using that function as a baseline, we fit the pulse with FermiDirac×exponential function. This formula was chosen to express both therise of the pulse and the decay of the charge amplifier signals. Red lines inFig. 3.11 are the fitted functions for both the cathode and anode. Charges
are calculated from the heights and the drift time is calculated from the time
diﬀerence of b2 from the cathode and anode.
The DAQ algorithm is implemented so that we can start measurements
whenever the flash lamp is turned on by a slow control system (see appendix
A.3). The purity monitor can measure electron lifetime above 25 µs withthe frequency of every two minutes at maximum. In the standard operation of XENONnT, the measurement was conducted every 15 min and eachmeasurement required 30 s of the xenon lamp flashing time.

3.6.2

Purity monitor installation

The purity monitor was installed in the outer vacuum vessel particularly
designed for the purity monitor. As you can see in Fig. 3.12, the outer vessel
has enough space to accommodate high voltage (HV) cables (to apply HVto electrodes) and an optical fiber (to introduce UV light to purity monitor).
In addition, the vacuum insulation of the purity monitor is completely separated from the other vacuum insulation volumes so that in the case of purity
monitor maintenance, we can just bypass the purity monitor and can avoid
stopping the entire liquid circulation. In normal operation, the outer vacuum vessel of the purity monitor is continuously pumped to keep the vacuum
level good enough so that discharges do not occur. Figure 3.13 is a pictureof purity monitor installation in the outer vessel.

47

3 Liquid xenon purification system

Optical fiber

Cathode grid

Anode

Anode grid

CathodeDrift electrons
Cathodecharge amplifierAnodecharge amplifier

HV

HV

HV

HV

Figure 3.10: Working principle of purity monitor. Photoelectrons generated
at the photocathode on the cathode are drifted toward the anode but some ofthem are captured by electronegative impurities. By measuring the numberof electrons at the cathode and anode, we can estimate the electron lifetimeof liquid xenon in the purity monitor.

3.6.3

Diﬀerent measurement modes

One important feature of the purity monitor is that we can position it
either before or after the liquid filter by changing valve configurations. Figure
3.14 shows a purity monitor pre-filter mode. In this mode, the purity monitor
measures the electron lifetime of the liquid just after the extraction fromcryostat and therefore we can consider this measurement as the electron
lifetime inside the cryostat. We use this mode for most of the lifetime of theexperiment because we are mostly interested in the electron lifetime of xenon
inside the cryostat.
We can also put the purity monitor downstream of the liquid filter asshown in Fig. 3.15, so-called post-filter mode. In this mode, we can measure
the electron lifetime of clean xenon just after the filter and it is useful when48

3 Liquid xenon purification system

Figure 3.11: Example waveform of the purity monitor. The bottom and toplines are averaged waveforms of the cathode and anode. The red lines are
fitting functions.
we want to know the eﬃciency of the liquid filters. If we have the electron
lifetime of xenon before (τe,before ) and after (τe,after )the filter, we can calculate
the eﬃciency ϵL of the filter using
ϵL = 1 −τe,before.
τe,afterThis mode was frequently used in the commissioning tests.

49

(3.8)

3 Liquid xenon purification system

Flow

Flow

Feedthroughs

Optical feedthroughHV feedthroughFigure 3.12: Drawing of a purity monitor outer vessel. There is enough space
to accommodate cables and a fiber.
PRODUCED BY AN AUTODESK STUDENT VERSION

50

PRODUCED BY AN AUTODESK STUDENT VERSIONPRODUCED BY AN AUTODESK STUDENT VERSIONPRODUCED BY AN AUTODESK STUDENT VERSION

3 Liquid xenon purification system

Figure 3.13: Purity monitor installation in the outer vacuum vessel.

51

3 Liquid xenon purification system: Oxygen filter

GN2

LN2

: Liquid pump

: Particulate filter

LXe/LN2
Heat exchanger: Proportional valve

Purity monitor

Venturi: Valve

Cryostat

Figure 3.14: Flow path of the purity monitor pre-filter mode. Open valves
are shown in green. The electron lifetime inside the cryostat is measured andthis mode is used in the most of the stable period of the experiment.

: Oxygen filter

GN2

LN2

: Liquid pump

: Particulate filter

LXe/LN2
Heat exchanger: Proportional valve

Purity monitor

Venturi: Valve

Cryostat

Figure 3.15: Flow path of the purity monitor post-filter mode. Electron
lifetime of the liquid after the filter is measured and this mode is usefulespecially when we want to study the eﬃciency of the liquid filters.

52

Chapter 4
Commissioning with about 2 tof xenon
To characterize the performance of the system, especially two filter candidates, Q5 and St707, we conducted liquid purification commissioning tests
using about 2 t of liquid xenon. First, in section 4.1, we explain the methods
for filter eﬃciency estimation which are used in the following sections. In thenext two sections, section 4.2 and 4.3, we report the results from those tests
performed in October 2019 and February 2020. The eﬃciency of the filter
candidates and their possible degradations were evaluated. In section 4.4, thepurification strategy for XENONnT is discussed based on the commissioning
test results.

4.1

Filter eﬃciency estimations

The main purpose of the tests is to understand how eﬃciently the filter
candidates remove impurities. In this section, detailed methods of filter efficiency estimation are described. First method uses the trend of electron
lifetime in purity monitor pre-filter measurements (section 4.1.1) and thesecond one uses the post-filter measurements (section 4.1.2).

4.1.1

Filter eﬃciency from pre-filter measurements

We can estimate filter eﬃciency by looking at the evolution of electron
lifetime in the cryostat (pre-filter measurements). The simplest way to describe the time evolution of the amount of impurity isNNdN= −ϵl − ϵL + Λ,
dt
τl
τL
53

(4.1)

4 Commissioning with about 2 t of xenon
where N is the amount of impurity, τl = M/fl and τL = M/fL are the times
necessary to process all the xenon in the cryostat by gas/liquid purification
system (M : total xenon mass, fl : flow rate of gas purification system (liquid
phase), fL : flow rate of liquid purification system) and Λ is an outgassing
rate, and this equation explains the impurity transfer to and from the liquid.
The outgassing rate refers to the sum of any kind of electronegative impurity
that transfers to the liquid phase of the detector. Thus it includes not only
impurities emanated from the detector components that touch liquid but also
impurity transfer from the gas phase to the liquid phase. The eﬃciency ofthe liquid purification filter is expressed by ϵL , and the eﬃciency of the gas
purification getter, ϵl , is assumed to be 1. When the gas or liquid purification
system was not in use, we can neglect related terms by ϵl = 0 or ϵL = 0.
For simplicity, we assume that the electronegative impurity is oxygen (mostcommon in the environment), and the amount of impurity can be converted
into electron lifetime using equation 3.3. Equation 4.1 has an analyticalsolution()
t
N (t) = (N0 − τ Λ) exp −+ τ Λ,
(4.2)
τ
1
ϵl ϵL
= + ,
τ
τl τL

(4.3)

when the flow rate, outgassing and eﬃciency terms are constant (N0 is initialamount of impurity).
By fitting the solution of the equation 4.1 to a measured electron lifetime
trend, we can obtain the liquid filter eﬃciency ϵL . However, it is better tohave an independent measurement of the outgassing rate because there isa correlation between outgassing rate and eﬃciency when both are fitting
parameters. In addition, we often use a short period of time to fit the trend
so that the filter eﬃciency can be considered constant over that time.

4.1.2

Filter eﬃciency from post-filter measurements

This method essentially compares pre- and post-filter electro lifetime values as briefly explained in section 3.6.3, but we explain it slightly more indetail using an example. Fig. 4.1 is an example of post-filter measurement(data taken from a 60 g Q5 test in February 2020, see section 4.3.4). Beforet = 11.5 h, the electron lifetime in the cryostat had been measured and theelectron lifetime was decreasing because there was no purification at all (liquid filter bypassed). At around t = 11.5 h, the liquid filter was integrated
into the circulation loop and the electron lifetime was measured in post-filter
mode. Finally, at around t = 18 h, the purity measurement was changed54

4 Commissioning with about 2 t of xenon
to pre-filter mode. To obtain eﬃciency using equation 3.8 and post-filter
measurements, we need not only post-filter values but also pre-filter values.
However, since liquid purification is fast, the pre-filter electron lifetime sometimes could change significantly while a post-filter measurement is going on,
and in that case, we need to estimate time-dependent pre-filter values.

Post-filterτ e,after

Pre-filter
Pre-filter(=cryostat)Pre-filter
Pre-filter(=cryostat)τe,before
w/o GXePUR
w/o LXePUR

w/o GXePUR
w/ LXePUR

Figure 4.1: Post-filter measurement. Black points are the electron lifetime
measurements with the purity monitor. From around t = 11.5 to 16 h, themeasurement was in post-filter mode, and otherwise, it measured the electron
lifetime of the liquid directly from the cryostat. Red line is a prediction of thepre-filter electron lifetime (=cryostat) which is necessary for the post-filter
eﬃciency estimation.
The red line in Fig. 4.1 is such an estimation of pre-filter values. The firstdecreasing part comes from extrapolating the trend at t = 0 to 10 h. The
outgassing rate Λ can be obtained by fitting the trend from t = 0 to 10 h withequation 4.1, and the trend can be extrapolated by using the same equation.
After the integration of the liquid filter, the post-filter measurement started
and there are no pre-filter values (electron lifetime in the cryostat). Although
the pre-filter values still should follow equation 4.1, ϵL is unknown. However,
we have direct access to Nafter , which is a total amount of impurity in thecryostat with the electron lifetime equivalent to the post-filter value, andϵL N in equation 4.1 can be substituted with N − Nafter . Then we can solve
equation 4.1 numerically and obtain the increasing part of the red line in55

4 Commissioning with about 2 t of xenon
Fig. 4.1. Now that both pre- and post-filter values (τe,before and τe,after ) areavailable at the same timing, we can calculate the eﬃciency using equation
3.8.
The advantage of this method is that we can get eﬃciency with a better
time resolution. Another good point is that it can be free from the outgassing
rate when the measurement is done under a regime that the electron lifetime
does not change quickly, because it is not necessary to consider the estimationof time-dependent pre-filter values described in the previous paragraph which
require outgassing rates. The disadvantage is that we need to change the flow
path from the pre-filter measurement which is our standard.

4.2

First test in October 2019

The liquid xenon purification system was turned on for the first time in
October 2019. The main purpose of the test was to understand the performance of the Q5 filter. Some prerequisites of the test are listed here.
• We filled 2.1 t of liquid xenon in the cryostat. We reduced it to 1.2 t
just before starting the test mentioned in section 4.2.4.
• During the test, TPC electrodes were immersed in liquid xenon in thecryostat to perform some cryogenic tests of the electrodes. Therefore
many cables and supporting structures were also present in the cryostat
and could be sources of outgassing.
• We tested the Q5 filters with diﬀerent amount and container shape ((a)
and (b) of Fig. 4.2).

4.2.1

Filling the cryostat

In prior to filling the cryostat with liquid xenon, the inner volume of
the cryostat was pumped by a turbo molecular pump for about 10 days toreduce outgassing molecules on the wall. Then we started to fill 2.1 t ofliquid xenon in the cryostat. Although there was no weight scale for thecryostat, we had it for a xenon reservoir called ReStoX-1 where xenon wasstored and filled from. Fig. 4.3 shows the weight of ReStoX-1 decreasing as
filling proceeded. First, the cryostat was filled with about 2 bar of gas xenon.
Then the cryostat was slowly cooled down using the PTR of the cryogenic
system. In this process, the pressure of gas decreased and the cooling became
ineﬃcient, thus gas xenon was refilled several times to increase pressure.
Once the bottom of the cryostat was cold enough to keep liquid, we switched56

4 Commissioning with about 2 t of xenon(a) Q5 18g, Oct. 2019(e) St707 2.4 kg, Feb. 2020(d) Q5 60g, Feb. 2020(b) Q5 60g, Oct. 2019
17.2

190

238

𝜙97.4

𝜙22.1

𝜙76.5

122.2

𝜙10.2

(c) Q5 11g, Feb. 2020

𝜙28.6
20.4

Figure 4.2: Geometry comparison of filters used in the commissioning tests.
Filter pellets are accommodated in cylindrical space and the liquid flows invertical direction. Unit in mm.
to heat exchanger filling mode. Liquid xenon from ReStoX-1 was extracted
by the gas purification pump, flown through hot getters, and then went tothe cryostat after liquefaction. Cooling power from vaporization was used tocondense the post-getter xenon gas at the heat exchanger. Overview of xenon
filling is summarized in Fig. 4.4. The filling process was basically the samefor the next liquid purification commissioning test as well as XENONnT.

4.2.2

First purity measurements

The first electron lifetime measurement was performed with the purity
monitor using filter bypass mode (see Fig. 4.5) and it was 29.0 ± 0.3 µs. The
electron lifetime was calculated using equation 3.6. To obtain an error, weassigned errors as ∆C,A = 0.1 mV (cathode (C) and anode (A) pulse height)and ∆td = 0.7 µs (drift time td ), and calculated the electron lifetime error
using the propagation rule of errors. Although xenon gas was purified with
hot getters when filled, due to outgassing from materials in the cryostat aswell as the cryostat wall itself, the electron lifetime was such a low value atthe beginning.
Then, we started liquid-phase gas purification (L/GXePUR) while monitoring electron lifetime evolution overnight. The flow rate of gas purification
was 45 slpm. Fig. 4.6 shows the increasing trend of electron lifetime. The
speed of purity improvement was consistent with the flow rate, assuming
100% getter eﬃciency. This was the first good indication that the purity
monitor was working reliably.
Another good example of this system, besides purification, is an out57

4 Commissioning with about 2 t of xenon

6.0
5.5
5.0
4.5

Finish filling

Fill xenon gas and start cooling

ReStoX-1 mass [t]6.5Fill xenon gas using heat exchanger

7.0

-25
9-0
9
20
1

-22
9-0
9
20
1

-19
9-0
9
20
1

-16
9-0
9
20
1

-13
9-0
9
20
1

-10
9-0
9
20
1

20
1

9-0
9

-07

4.0

Figure 4.3: ReStoX-1 mass during xenon filling.
gassing measurement. If we leave the system without purification (liquid
circulation only), the electron lifetime is expected to decrease due to outgassing. We did such a measurement to see if we can estimate the outgassing
rate of the system. Fig. 4.7 shows the result of the overnight measurement.
The electron lifetime was slowly decreasing and the outgassing rate was calculated to be 0.19 ± 0.04 mg/day oxygen equivalent (we can only say in theunit of oxygen equivalent because any kind of electronegative impurities cancontribute to electron capture and we can only measure the total contributions). In this measurement, the uncertainty was large because the purity ofxenon was already low and the outgassing was not so significant to lower the
purity further. If we repeat the same measurement in much higher purity
conditions, we would get a more accurate outgassing rate in a short time.

4.2.3

Testing 18 g Q5 filter

The first purification test was performed with 18 g of Q5 filter. As we
mentioned before, due to the high radon emanation rate of Q5, we wanted toknow the performance with a small mass. Figure 4.8 shows the picture of 18
g of Q5 filter mounted on the skid. Q5 pellets were accommodated in the 1/2
inch tube (Fig. 4.2 (a)), capped with 90 µm particulate filter from both sides.
It was ideal to regenerate Q5 after being mounted on the skid to minimize
contact with air after regeneration. However, due to safety restrictions of thelaboratory, we decided to regenerate it outside the underground laboratory58

4 Commissioning with about 2 t of xenon

Figure 4.4: Filling cryostat from ReStoX-1. Liquid xenon in ReStoX-1 isextracted by the pump, go through getters and filled in the cryostat afterliquefaction. Heat exchanger saves cooling power of the cryogenic system.
and mount it while flowing nitrogen gas. This method was used for all the
Q5 installations.
We attempted to measure the eﬃciency of this filter by comparing theelectron lifetime before and after the filter (section 3.6.3). Unfortunately,
because of huge pressure loss across the filter (about 1 bar), we were not able
to establish a stable flow and there was a big instability every 10 minutes
or so. Fig. 4.9 shows such instability in the flow rate as well as the electron
lifetime measurement. Spikes in the flow rate might come from bubbles in
the flow pipe, especially the venturi flow meter part.
Although it is diﬃcult to estimate pre-filter values during an unstablecondition, it is fair to assume that the pre-filter value sits in between the prefilter electron lifetime before (31.6 µs) and after (33.0 µs) this test. Therefore,
the pre-filter electron lifetime was estimated to be τe,before = 32.3 ± 0.7 µs.
Fig. 4.9 also shows the result of the post-filter measurement. Despite theinstability, using stable periods, we were able to estimate the electron lifetime
after the filter and it was τe,after = 49.0 ± 0.5 µs. The uncertainty comesfrom the maximum and minimum among the highest values in each cycle.
The filter eﬃciency ϵL can be calculated via ϵL = 1 − τe,before /τe,after and we
obtained ϵL = 0.34 ± 0.02 at 0.6 L/min flow rate.
We learned from this test that a small amount of Q5 still had nonnegligible filtering eﬃciency in a liquid xenon environment. However, we
also learned that we needed to be careful when designing filter chambers
59

4 Commissioning with about 2 t of xenon

GN2

LN2

Figure 4.5: Liquid circulation filter bypass mode.
because thin structures could make huge pressure loss across the filter. Although maximum acceptable pressure loss is not measured, it is ideal to be
below 0.2 bar.

60

: Liquid pump

: Particulate filter

LXe/LN2
Heat exchanger: Proportional valve

Purity monitor

Venturi: Valve: Oxygen filter

Cryostat4 Commissioning with about 2 t of xenon

32.5

Electron lifetime [ s]

32.0
31.5
31.0
30.5
30.0
29.5
29.0

0810/10:00

0610/10:00

0410/10:00

0210/10:00

0010/10:00

2210/09:00

2010/09:00

28.5

Figure 4.6: Electron lifetime trend with GXePUR running overnight. The
electron lifetime increased and the speed of improvement was consistent withthe gas flow rate.

34.0

Electron lifetime [ s]

33.5
33.0
32.5
32.0

0810/11:00

0610/11:00

0410/11:00

0210/11:00

0010/11:00

2210/10:00

2010/10:00

31.5

Figure 4.7: Electron lifetime trend without gas xenon purification. The speedof electron lifetime decrease can be converted to outgassing rate of the system
and it was 0.19 ± 0.04 mg/d oxygen equivalent.

61

4 Commissioning with about 2 t of xenon

Figure 4.8: 18 g Q5 filter mounted on the skid. Red arrow indicates the filter
part. It was contained in the 1/2 inch tube, capped with 90 µm filter fromboth sides.

50
48
Electron lifetime [ s]Flow rate [L/min]

2.0
1.5

46

1.0

44
42

0.5

40
0.0

10/10
15:19

10/10
15:24

10/10
15:29

10/10
15:34

10/10
15:39

10/10
15:44

10/10
15:49

10/10
15:54

Figure 4.9: Result of 18 g Q5 filter in the post-filter measurement. Although
there was a big instability about every 10 minutes, we were able to measure
the electron lifetime after the filter using stable periods.

62

4 Commissioning with about 2 t of xenon

4.2.4

Testing 60 g Q5 filter (1)The next one was a 60 g Q5 filter. To solve the pressure loss problem
we encountered in the previous test, we adopted a disk shape filter chamber
to increase the cross section of the filter. Superficial flow velocity vs = Q/A(Q: volumetric flow, A: cross section) becomes small when the cross section
is large and as a consequence, pressure loss becomes small. The detailed
formula of pressure loss in packed beds such as Q5 is described by Ergun
equation [68] and it is approximately proportional to quadratic of vs in ourcase. We also increased the mass of Q5 to see how eﬃciency would change.
The geometry of filter volume was 76.5 mm diameter and 17.2 mm heightcylinder (Fig. 4.2 (b)), made by ConFlat flanges. The filter had 100 µm
particulate filters on both inlet and outlet. The filter was mounted on theskid in the same manner as the previous one, using nitrogen gas flow.
Note that before starting this test, we reduced the amount of xenon in
the cryostat from 2.1 to 1.2 t. After that, we conducted pre- and post-filter
measurements of 60 g Q5. We obtained the filter eﬃciency of ϵL = 0.24±0.01
at 1.5 L/min flow rate. Fortunately, we did not encounter the problem ofpressure loss in this filter. After this measurement, we switched back to prefilter measurement and continued to monitor the trend of electron lifetime.
The result is shown in Fig. 4.10. The electron lifetime increased from 45
to above 100 µs but it looked that the electron lifetime was approaching its
plateau. The flow rate was 2.0 L/min in this measurement.
The electron lifetime trend was divided every 5 hours and each term wasfitted with equation 4.2 (red lines in Fig. 4.10, used the method described in
section 4.1.1). For the outgassing rate, we used the value obtained previously,Λ = 0.19 ± 0.04 mg/d. The eﬃciency showed the decreasing trend as shownin Fig. 4.11.

63

4 Commissioning with about 2 t of xenon

Fitting lines
Purity monitor

Electron lifetime [ s]

100
90
80
70
60
50
0

5

10
15
20
Time [h] since 2019/10/17 02:00:00

25

30

Figure 4.10: Electron lifetime trend with 60 g Q5 filter in the pre-filter
measurement. It improved very quickly but almost reached its plateau ataround 105 µs. Red lines are fitting lines used for the eﬃciency estimations.

0.30

Q5 60 g efficiency

0.25
0.20
0.15
0.10
0.05
0.00

0

5

10
15
20
Time [h] since 2019/10/17 02:00:00

25

30

Figure 4.11: Evolution of the 60 g Q5 eﬃciency at 2.0 L/min. The eﬃciency
decreased with time.

64

4 Commissioning with about 2 t of xenon

4.3

Second test in February 2020

To further understand the liquid purification system, another test was
conducted in February 2020. Basic information is listed here.
• We filled 1.5 t of liquid xenon in the cryostat.
• The cryostat was empty and only liquid xenon was filled. No big components were present such as electrodes in the previous test.
• We tested two Q5 filters with diﬀerent amounts and container shapes(11 g and 60 g). We also tested the St707 filter for the first time. Filter
geometries are listed in Fig. 4.2 as well as in the text.
The cryostat was filled in the same manner as in the last test and we
started the liquid xenon circulation. Fig. 4.12 shows the full electron lifetime
trend measured with the purity monitor during the second commissioning
test. Thick color periods correspond to the post-filter measurement. We
briefly summarize the overview of the test and then go into details of filter
tests in the following sections.
On February 1st, we started to test the 11 g Q5 filter (grey in Fig. 4.12)
after confirming the electron lifetime in the cryostat. On February 2nd, we
switched the liquid circulation pump to the spare one which we have neverused before. Since it was the first time to use this pump as well as the flowlines, the electron lifetime dropped significantly by this operation. The purity
tends to drop when new components are used because the flow might clean
those components at the beginning. We turned on and oﬀ the gas purification
system (from February 3rd to 6th) and verified that electron lifetime trend
was consistent with these operations (e.g. purity improved faster when gas
purification is on, etc.).
We bypassed 11 g Q5 and started the test of the St707 filter on February
6th (green in Fig. 4.12). The test lasted until February 7th afternoon andthen St707 was bypassed. A few hours later, gas purification was also stopped
to estimate the outgassing rate of the system. Then on February 8th, westarted 60 g Q5 filter test (orange in Fig. 4.12). As usual, we did both preand post-filter measurements to understand the eﬃciency. The test lasted
until February 9th.

65

66

0

50

100

150

200

250

Pump switch test
2020-02-02

2020-02-03

Start GXePUR
2020-02-04

Restart GXePUR
2020-02-05

Bypass Q5 11 g and start St707
2020-02-06

2020-02-07

Stop GXePUR
2020-02-08

Start Q5 60 g

Bypass St707

Stop GXePUR

Start Q5 11 g

2020-02-09

Figure 4.12: Electron lifetime evolution in the second commissioning test. Grey, green and orange periods correspondto 11 g Q5, St707 and 60 g Q5 respectively. Thick color periods correspond to post-filter measurement of each filter.

Electron lifetime [ s]measured with purity monitor

300

4 Commissioning with about 2 t of xenon

4 Commissioning with about 2 t of xenon

4.3.1

Outgassing measurement

For the analysis of the filter eﬃciency, we sometimes need the outgassing
rate. The useful measurement was conducted from February 7th to 8th when
we did not have any purification(liquid filter bypassed, no gas purification).
Fig. 4.13 is the electron lifetime trend in this period. The electron lifetime
before and after the gas purification interruption was well described by theoutgassing rate of 0.19 ± 0.01 mg/day oxygen equivalent. To model the
lifetime trend, we modified the equation 4.1 as ϵL,l = 0. For the analysis of
the second commissioning test, this value was used when the outgassing rate
was necessary.

160
140
120

100 5.0

No gas purification

180
Gas purification(45 slpm)

Electron lifetime [ s]200

7.5 10.0 12.5 15.0 17.5 20.0 22.5
Time [h] since 2020-02-07 12:00:00

Figure 4.13: Outgassing measurement in the second commissioning test. We
stopped gas purification at around February 7th ,19:00. Black points areelectron lifetime from purity monitor. Red line is electron lifetime modelfrom outgassing rate of 0.19 mg/day oxygen equivalent.

4.3.2

Testing 11 g Q5 filter

As a first test in the 2nd commissioning, we tested a 11 g Q5. The filter
chamber has 28.6 mm diameter and 20.4 mm height cylinder space inside toaccommodate the Q5 filter (Fig. 4.2 (c)). The particulate filter used in thistest was same as the one used in the 60 g filter in the first commissioning
test.
First, we conducted pre- and post-filter measurements to evaluate theeﬃciency. This time, the eﬃciencies were measured at diﬀerent flow rates
because the flow rate could aﬀect the eﬃciency. Then we switched back to
pre-filter mode and continued to monitor the electron lifetime trend. The
67

4 Commissioning with about 2 t of xenon
flow rate was 2.0 L/min in pre-filter mode. Fig. 4.14 shows the eﬃciency of
the filter (red: eﬃciencies using post-filter mode with various flow rates, blue:
eﬃciencies at 2.0 L/min). Each color band indicates the period of post-filter
measurements with diﬀerent flow rates. To evaluate the eﬃciencies, we used
the outgassing rate obtained from data on February 7th to 8th (see section
4.3.1) although outgassing is subdominant in such a low purity condition.
The initial eﬃciency was about 0.1 at 1.5 L/min but decreased with time.
This filter stayed in the flow path of liquid for several more days but
since eﬃciency was already low, it was subdominant compared to the gas
purification system as you can see from February 4th to February 6th before
the St707 test (Fig. 4.12).

Q5 11 g efficiency

0.20
0.15

Efficiency of the filter: After filter measurements with various flow rates
Efficiency of the filter: Flow rate = 2.0 L/min
Fitting blue points with exponential curve( = 30.1 [h])

0.10
0.05
0.0010.0 12.5 15.0 17.5 20.0 22.5 25.0 27.5 30.0
Time [h] since 2020-02-01 00:00:00

Figure 4.14: Time dependent eﬃciency of 11 g Q5. Red data points are
eﬃciency calculated with post-filter mode. Note that the measurement was
conducted under diﬀerent flow rates. Yellow, blue, green, red and magenta
periods indicate the measurement with 1.0, 1.5, 2.0 ,2.5 and 2.8 L/min flow
rates respectively. Blue points are eﬃciency calculated with post- (t < 20 h)
and pre-filter (t > 20 h) mode under 2.0 L/min. The black line is a result of
exponential fit.

4.3.3

Testing St707 filter

St707 filter was tested for the first time in the liquid environment. The
amount of filter was 2.4 kg and it was contained in the chamber with adiameter of 97.4 mm and 122.2 mm height inner volume (Fig. 4.2 (e)). The
geometry of St707 pellets was 4 mm diameter and 2 mm height cylinder. The
old SAES getter cartridge was opened and the pellets were filled in our filter
chamber. After being mounted on the skid, the filter was activated at 400◦ C
68

4 Commissioning with about 2 t of xenon

ST707 efficiency

for four hours in a gaseous xenon environment. For the eﬃciency studies,
we repeated what we did for 11 g Q5. The result of eﬃciency measurement
was shown in Fig. 4.15. The initial eﬃciency was 0.67 ± 0.01 at 1.5 L/minflow rate, the highest among what we tested so far. The slope of purity
improvement was exceptionally steep at the beginning. However, similar toother filters, the eﬃciency decreased quickly.

1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.010

Efficiency of the filter: After filter measurement with various flow rates
Efficiency of the filter: Flow rate = 1.5 L/min
Fit blue points with exponential curve( = 11.1 [h])

15
20
25
30
35
Time [h] since 2020-02-06 00:00:00

40

Figure 4.15: Time dependent eﬃciency of the St707 filter. Red data points
are eﬃciencies calculated with post-filter measurement. Note that the measurement was conducted under diﬀerent flow rates. Yellow, blue, orange andgreen periods indicate the post filter measurement with 1.0, 1.5, 1.8 and 2.0
L/min flow rates respectively. Blue points are eﬃciencies calculated with
post- (t < 19 h) and pre-filter (t > 19 h) measurement mode under 1.5
L/min. The black line is a result of exponential fit.

4.3.4

Testing 60 g Q5 filter (2)We tested a larger mass Q5 filter which is 60 g. It was contained in 22.1
mm diameter, 190 mm length tube (Fig. 4.2 (d)). The result of eﬃciency
measurement is shown in Fig. 4.16. The eﬃciency was ϵL = 0.385 ± 0.005 at
1.5 L/min flow rate but again decreased with time.

69

4 Commissioning with about 2 t of xenon

0.5
Q5 60 g efficiency

0.4

Efficiency of the filter: After filter measurement with various flow rates
Efficiency of the filter: Flow rate = 1.5 L/min
Fit blue points with exponential curve( = 14.4 [h])

0.3
0.2
0.1
0.010

15
20
25
30
35
Time [h] since 2020-02-08 00:00:00

40

Figure 4.16: Time dependent eﬃciency of 60 g Q5. Red data points are
eﬃciency calculated with post-filter measurement. Note that the measurement was conducted under diﬀerent flow rate. Yellow, blue, orange and green
bands indicate the post filter measurement with 1.0, 1.5, 1.8 and 2.0 L/minflow rate respectively. Blue points are eﬃciency calculated with post (t < 17h) and pre-filter (t > 17 h) measurement mode under 1.5 L/min. The blackline is a result of exponential fit.

70

4 Commissioning with about 2 t of xenon

4.4

Lessons from two tests and next step

Although we were not able to achieve O(1) ms of electron lifetime in thesecommissioning tests, we learned several important lessons. The Q5 filter hada reasonable filtering eﬃciency even with several tens of grams. However, theeﬃciency dropped quickly after using it for one day or so. It might indicate
a lack of capacity. A larger amount of the Q5 filter would solve this problem
but due to the high radon emanation rate, this was not a viable option. For
the St707 filter, we learned that 2.4 kg of St707 had high initial eﬃciency
but it decreased quickly similar to Q5. The results are summarized in Table
4.1.
After these tests were finished, we opened the cryostat and found that
there was a lot of dust probably coming from the Q5 filter. Such dust might
have bad eﬀects on TPC operation such as electrode discharges and we must
avoid them. The particulate filter we adopted was 90 to 100 µm and this was
not fine enough. For the coming purification with TPC, we decided to use
0.5 µm filter with a large cross section. Also, we learned that we should be
careful about filter container design to avoid big pressure loss as experienced
in the 18 g Q5 filter tested in October 2020.

71

Filter Mass [g] Initial eﬃciency Flow rate [L/min] Filter lifetime [h] Initial purity [µs]Q5180.34 ± 0.02
0.6
Not measured
32
Q560
0.24 ± 0.01
1.5
22
46
Q5
11
0.105 ± 0.005
1.5
30
34
Q5
60
0.385 ± 0.005
1.5
14
150
St707
2400
0.67 ± 0.01
1.5
11
55

Reference
Section 4.2.3
Section 4.2.4
Section 4.3.2
Section 4.3.4
Section 4.3.3

Table 4.1: Summary of the commissioning tests. The results of filter tests are summarized. Initial eﬃciencies wereobtained under stated flow rates.
4 Commissioning with about 2 t of xenon

72

4 Commissioning with about 2 t of xenon

4.4.1

Strategy for the XENONnT purification

Since we wanted to use St707 for the long-term operation of XENONnT
because of the low radon emanation rate, the following strategy was proposed.
STRATEGY
1. Use large amount (O(100 − 1000) g) of Q5 to quickly remove the impurities that are present before purification (bulk cleaning).
2. Once the purity reaches O(1) ms, switch to the St707 filter and use it
for a longer operation.
This strategy is based on the assumption that we observed short lifetime of the filters because we used those filters under low purity
condition and they got saturated quickly.
The Q5 filter in the first step is expected to have very high eﬃciency andlarge capacity thanks to the large mass of the filter material. It will remove
impurities that are already present in the liquid before purification (clean
the bulk impurities) and thanks to a larger capacity, it would not saturateeven when the bulk impurities are almost removed and the electron lifetime
reaches above O(1) ms. Although radon emanation must be huge, we ignore
this for the moment.
When switching to St707, we expect to already have high purity and thus
no need to clean the bulk anymore. St707 should only deal with outgassing
molecules and may not saturate quickly. For example, 8.6 t of liquid xenon(XENONnT mass) with 60 µs electron lifetime contains about 10 mg oxygen
equivalent of impurities. If we assume that the outgassing rate is 0.1 mg/day,cleaning the bulk is equivalent to dealing with outgassing for about threemonths. Due to 3.8 days of half-life, 222 Rn emanated from Q5 would be
negligible if we operate St707 for a month.

4.4.2

Contact time theory of the filter eﬃciency

Apart from the purification strategy, we also attempted to create a modelto understand the initial Q5 filter eﬃciency under diﬀerent mass and flow
rate. The model is based on the hypothesis that the eﬃciency of a fresh
filter is determined only by the time that liquid stays in the filter volume(contact time). The contact time is proportional to M/f (M : filter mass,f : flow rate). It is also natural to assume that if contact time t is α times
longer (t → αt), the survival probability p of impurities becomes p → pα .
Therefore, if the initial eﬃciency was measured to be ϵ′L (f ′ , M ′ ) when the73

4 Commissioning with about 2 t of xenon
flow rate is f ′ and the mass is M ′ , the eﬃciency under any f and M can be
described in the equation 4.4.
(M/f )/(M ′ /f ′ )ϵL (f, M ) = 1 − (1 − ϵ′L (f ′ , M ′ ))(4.4)

We can consider that(f ′ /M ′ )a = (1 − ϵ′L (f ′ , M ′ ))(4.5)

is a single free parameter and equation 4.4 can be rewritten as
ϵL (f, M ) = 1 − a(M/f ) .

(4.6)

We fitted the initial Q5 eﬃciency values measured in those commissioning tests with equation 4.6. The result is shown in Fig. 4.17. Although weused diﬀerent amounts and geometries of the filter (see Fig. 4.2 which summarizes the filter geometries/amounts used in the tests), eﬃciencies seem tobe determined by contact time only. Since the value obtained from 60 g Q5
in October 2020 was on a diﬀerent trend, it was removed from fitting data.
It is unknown why the value from 60 g Q5 in October 2020 is not on thetrend. A possible explanation could be the incomplete regeneration or thatthe installation procedure was not perfect and some air was introduced in thefilter during the installation. This model is very useful because it enables us
to predict the Q5 filter eﬃciencies at the design stage. For example, we canpredict ϵL > 0.9 if the filter mass is M > 360 g and the flow rate is f = 2.0
L/min.

74

4 Commissioning with about 2 t of xenon

1.0

18 g filter, Oct. 201960 g filter, Oct. 201911 g filter, Feb. 2020
60 g filter, Feb. 2020
Fitting with model: (f, M) = 1 0.987M/f

Efficiency

0.8
0.6
0.4
0.2
0.0

0

20

40
60
M/f [g/(L/min)]

80

100

Figure 4.17: The initial Q5 filter eﬃciencies can be explained by the contact
time theory (black line). The only exception is the value from 60 g Q5 in
October 2019 (yellow point). The reason is unknown but could be due topoor regeneration or installation procedure.

75

Chapter 5
Liquid purification in
XENONnTIn March 2020, XENONnT TPC was assembled and placed in the cryostat. After pumping the inner volume for a while, we started to cool down
and fill the cryostat with liquid xenon. Despite many interruptions and inconveniences due to the COVID-19 pandemic, the detector was completely
filled with 8.6 t of liquid xenon in early October 2020. We started the liquid
circulation in the middle of October.
We proceeded with the XENONnT purification in the following order.
First, we used conventional gaseous phase purification only and liquid purification filters were bypassed. Then we started liquid phase purification with
Q5 and later switched to the St707 filter. The operation and electron lifetime
evolution in each period are described in section 5.1 (bypass), 5.2 (Q5) and5.3 (St707).
In section 5.4, we discuss systematic uncertainties of the purity monitor.
The purity monitor has been the only way to know the electron lifetime and itis necessary to understand the systematic uncertainties. Section 5.5 provides
additional discussions on the St707 filter eﬃciency. Since one of the main
challenges is how to reduce radon while achieving high purity, the evolutionof radon event rate is described in section 5.6.

5.1

Period 1: Filter bypass modeFirst of all, we bypassed liquid filters and only circulated liquid withthe flow rate of 2.0 L/min. The bottom plot of Fig. 5.1 shows the electron
lifetime trend in no liquid filter term. The initial electron lifetime was about
72 µs. Before October 15th, there was no gas purification at all. Thus the76

5 Liquid purification in XENONnT
decrease of the electron lifetime can be attributed to outgassing. On October
15th, liquid phase gas purification (L/GXePUR) started with 60 slpm. The
electron lifetime dropped significantly just after turning on L/GXePUR but
soon began to increase. The purity often drops after turning on new systems
probably because new gas lines were not clean enough before use. On October
18th, gaseous phase gas purification (G/GXePUR) started as well with 2.0
slpm. In this condition, xenon was extracted at 58 slpm from the liquid phaseand 2 slpm from the gas phase. In general, the electron lifetime continuously
increased but there was some disturbance especially on October 19th and21st. In those two timings, there were some operations that disturbed theliquid level of the detector. Impurities on the detector components, especiallynear the liquid surface, could have been released by vertical movements of
the liquid surface.
Fitting function: (t) = 0/(1 + t/ ) + C

2020-10-15

2020-10-18

2020-10-21

110
100
90
80

2020-10-24

2020-10-27

2020-10-30

2020-11-02

2020-11-05

Start G/GXePUR (2 slpm)

Start L/GXePUR (60 slpm)

Electron lifetime [ s]Outgassing rate (mg/day)

0.5
0.4
0.3
0.2
0.1
0.0
120

70
60

5
0-1
1-0
20
2

2
0-1
1-0
20
2

0
0-1
0-3
20
2

7
0-1
0-2
20
2

4
0-1
0-2
20
2

1
0-1
0-2
20
2

8
0-1
0-1
20
2

20
2

0-1
0-1

5

50

Figure 5.1: Electron lifetime in the filter bypass mode. The bottom plotshows the electron lifetime evolution and the top plot shows the oxygen
equivalent outgassing rate calculated from the trend in each grey period.
The red line is a fitting function of the outgassing rate trend.
The grey bands in Fig. 5.1 correspond to the periods when the lifetime
trend was relatively smooth. Outgassing rates were estimated for each grey
period by fitting lifetime trend with equation 4.1 and shown in the top plot77

5 Liquid purification in XENONnTof Fig. 5.1 (black points). The trend of outgassing decrease was fitted with
Λ(t) = Λ0 /(1 + t/τ ) + C and shown with the red line. The outgassing rate
decreased quickly at the beginning and it was estimated to be 0.09 ± 0.02
mg/day oxygen equivalent at the end of this period, calculated as an averageof the last three data points in the top plot of Fig. 5.1. This number issmaller than in the commissioning tests (see chapter 4) despite many detector
components inside. One of the main reasons would be that we were forced
to pump the inner volume of the cryostat for about two months in total
due to the COVID-19 interruptions. In the commissioning tests, we only
pumped for a week or so, which resulted in higher outgassing rates. We
also circulated room temperature xenon gas between the cryostat and thegas getters to enhance the reduction of impurities on the surface of detector
components.

5.2

Period 2: Purification with Q5

The Q5 filter was used at first to clean the bulk of liquid as stated in
section 4.4. The cylindrical vessel (ϕ = 47.5 mm and h = 341.3 mm) was
filled with 475 g of Q5 and both sides were capped with 100 µm particulate
filter. The regeneration was conducted using the method described in Fig.
3.7. The Q5 filter was mounted on the skid along with 0.5 µm particulate
filter downstream to catch possible dust from the Q5 filter (lesson from commissioning tests, see section 4.4). This filtering size was much smaller thanwhat we used in the commissioning tests.
We started to use the Q5 filter since November 6th with 2.0 L/min flowrate (we kept gas purification at 60 slpm as before). The electron lifetime
trend is shown in Fig. 5.2. The electron lifetime increased dramatically fast
after Q5 was in use and reached above 5 ms in one week.
To understand the electron lifetime trend better, electron lifetime trend
before and after Q5 integration was fitted with the evolution model describedin equation 4.1 (Fig. 5.3). Following outgassing function was used as Λ ofequation 4.1,
Λ(t) = Λ0 + Λ1 δ(t − t1 ).

(5.1)

The second term, Λ1 δ(t − t1 ), is related to the drop of the electron lifetimeat t = t1 = 7.5 d mentioned later, and it is modeled as an instantaneous
injection of impurities described by the delta function.
To fit the model to data, we used the Aﬃne invariant Markov chain
Monte Carlo Ensemble sampler called emcee [69]. We used the lifetime data
before and after we switched to Q5 (black points in Fig. 5.3), and fitted the
78

103

Restart G/GXePUR

Change flow to 3 L/min
Stopped G/GXePUR

Start Q5 (2 L/min)Electron lifetime [ s]104Fill additional Xe

5 Liquid purification in XENONnT

-29
20

20

-11

-26
20

20

-11

-23
20

20

-11

-20
20

20

-11

-17
20

20

-11

-14
20

20

-11

-11
20

20

-11

-08
20

20

-11

20
20

-11

-05

102

Figure 5.2: Electron lifetime trend when the Q5 filter was in use. The electron
lifetime increased to about 7 ms with 2.0 L/min and beyond 10 ms with 3.0
L/min. On October 29th, there was a bit of xenon filling to the cryostat.
outgassing rate and filter eﬃciency simultaneously but did not use data verymuch close to filter switching operations because there was some disturbanceto the system related to them. Solid red line in Fig. 5.3 is the result of thefitting with ϵL = 1, Λ0 = 0.11 mg/d, Λ1 = 0.06 mg, which are obtained fromthe fitting. The model seems to explain the data.
We also performed post-filter measurement with various flow rates but
unfortunately (or fortunately!), the electron lifetime of xenon was so highthat we could not measure it reliably (anode/cathode ratio was nearly one).
However, this was another indication that the eﬃciency of the Q5 filter wasconsistent with 100%.
The drop of the electron lifetime on November 9th in Fig. 5.2 is related
to the operation of liquid xenon purification skid. We stopped pumping theouter vacuum insulation of the skid at this timing for some maintenance andthe outer vacuum level got worse quickly, which caused a slight increase in thetemperature of the system. This might have caused the release of impurity
molecules and the electron lifetime dropped. After resuming outer vacuum
pumping, the electron lifetime started to increase again.
On October 16th, we increased liquid flow from 2.0 L/min to 3.0 L/min.
We stopped gaseous phase gas purification (G/GXePUR) at the same timing.
The electron lifetime decreased slightly and did not increase anymore. After
resuming G/GXePUR, the electron lifetime started to increase again andreached around 10 ms. This was another clue that cleaning the gas phase of
the cryostat is important, especially when purity is high.

79

5 Liquid purification in XENONnTElectron lifetime [ s]104

Purity monitor
Model

Flow rate :Gas purification : 58(LXe) + 2(GXe) slpm
Liquid purification : 2.0 L/min

103

Q5 efficiency: 100%
Outgassing model : 0.11 mg/d O2 equiv.

102
0

2

4

6

Time [d]

8

10

12

14

Figure 5.3: Electron lifetime before and after the Q5 filter switch. X-axis istime since November 2nd, 2020. The black points are the electron lifetimes
measured with the purity monitor and the red solid line is the best fit model.

5.3

Period 3: Purification with St707

St707 was the filter which came after the Q5. This filter has a low radon
emanation rate and was planned to be used for longer operations (see section
4.4.1). In the commissioning test, we used 2.4 kg of St707 and the initialeﬃciency was 0.67 at 1.5 L/min, which was not small at all. Based on thisknowledge, we decided to use a similar amount, 3.0 kg, for the filter. The
design of the filter chamber was decided to be 60.2 mm inner diameter and
480 mm tall. There was a 0.5 µm particulate filter downstream of St707,
similar to the Q5 case. The filter was mounted on the liquid purification skid
as shown in Fig. 5.4.
To activate the filter, we heated up the filter chamber up to 200 ◦ C for
24 h. Then we increased the temperature to 355 ◦ C for another 24 h. All
the operations were done under the gas xenon environment. In fact, themanufacturer suggests that heating for 1 h at 355 ◦ C is more than enoughto fully activate the getter pellets. However, to stand on the safe side, we
decided to adopt the activation procedure stated here.

80

5 Liquid purification in XENONnTFigure 5.4: St707 vessel mounted on the skid. The left one with black tape(heater) is the St707 vessel. The right one is the particulate filter locateddownstream.
We switched the filter from Q5 to St707 on December 2nd, 2020. The
trend of electron lifetime is shown in the yellow period of Fig. 5.5 along withthe full trend of electron lifetime from the filter bypass period to January
2021. We saw a quick drop in the electron lifetime just after the filter switch
because of poor operation skills. After switching to St707, the Q5 filter
was still connected to the system waiting for the liquid in Q5 to vaporize
and temperature increase. It seemed that Q5 emanated impurities during
warming up. Although the electron lifetime decreased at the beginning, itsoon reached a plateau and started increasing again. The initial flow rate
was 1.5 L/min but increased to 2.0 L/min on December 9th. The electron
lifetime seemed to plateau at around 4.5 ms. This value is already above thegoal we set in section 3.1.2, τe = 3 ms.
There was a downtime of liquid circulation at the beginning of 2021 due
to some maintenance and there was no gaseous phase purification as wellin this term. Thus the electron lifetime was decreased to about 1.5 ms but
81

5 Liquid purification in XENONnT
it recovered quickly after resuming liquid purification. The electron lifetime
reached 7 ms at the end of January. In this period, the extraction rate of
GXePUR from the gas phase (G/GXePUR) increased to 17 slpm and thismight have helped to gradually reduce the amount of impurity coming fromthe gas phase. There was no clear sign of eﬃciency drop at this point, whichindicates that this filter can handle more than two months of outgassing
burden.
Figure 5.5 also shows the expected electron lifetime trend if we kept thegas purification only (dashed line). The assumption is 60 slpm gas purification rate and 0.09 mg/d outgassing rate (obatined in section 5.1). It is
expected that the electron lifetime would only reach around 0.4 ms after a
few months of operation. The comparison between this result and the gas
purificaiton only scenario emphasizes again the power of this technique.

82

Figure 5.5: Electron lifetime trend since the beginning of XENONnT purification. The first grey period corresponds
to liquid filter bypass mode. The red period corresponds to Q5 and the yellow period corresponds to St707. The grey
period in January 2021 is a maintenance and liquid circulation was completely stopped as well as gas purification.
The dashed line shows the expected electron lifetime trend in gas purification only scenario.

5 Liquid purification in XENONnT83

5 Liquid purification in XENONnT

5.4

Systematic uncertainty of purity monitor
measurement

Ideally, we want to calibrate the purity monitor by supplying liquid witha known electron lifetime but it is diﬃcult to prepare such liquid. The pointof calibration is whether the diﬀerence of measured charges at cathode andanode can only be attributed to the electron capture by impurities. If theelectric field inside the purity monitor is distorted and some fraction of drift
electrons cannot reach the anode (Fig. 5.6), the measured electron lifetime
would be lower than the reality. The possible bias of charge measurements
could also aﬀect the result. These are sources of systematic uncertainty andwe want to constrain them.

Figure 5.6: If there are drift electrons that do not reach anode but end up in
grids or field shaping rings, it biases the purity measurement. Although theelectric field simulation of the purity monitor suggests that there is no lossof electrons drifting from the cathode to anode, we need to make sure about
this from measurements.
In this section, we discuss a data-driven way of constraining such a systematic uncertainty. Note that the following discussions are only valid fora current field configuration (100 V/cm, all the purity monitor measurements in this thesis is done under this condition). We assume that measured(QA /QC )meas is biased due to drift electron losses or other measurement systematics, and the true ratio (QA /QC )true that should be used for electron
lifetime calculation is expressed by (QA /QC )true = α × (QA /QC )meas . Let’sconstrain the factor α from the data. Figure 5.7 shows the (QA /QC )meas and84

5 Liquid purification in XENONnT

1.00253.5

1.00000.9975

Flow rate [L/min]

3.0

0.99502.5

0.99002.0

QA/QC

0.99250.98751.5

0.98500.9825
10:30

11:00

11:30

12:00

12:30

13:00

13:30

14:00

1.0
14:30

Figure 5.7: Measured cathode-anode ratio QA /QC of the purity monitor as
a function of flow rate. The measurement was performed in the post-filter
mode with Q5 in November 2020. The black points are QA /QC and the redline is the flow rate. Even though we increase the flow rate, we did not see
any QA /QC decrease, which means that there was no measurable electron
lifetime decrease.
the flow rate of the liquid purification system during post filter measurementof the Q5 filter. The measured ratio (QA /QC )meas in Fig. 5.7 is distributed
around 0.9977 and (QA /QC )true (= α × (QA /QC )meas ) should not exceed 1
from the definition of (QA /QC ). Therefore, α is constrained as 0.9977α < 1.
We obtained this strict upper constraint thanks to the very high eﬃciencyof the Q5 filter.
The next step is to constrain the lower boundary of α. The idea is to
use the fresh St707 eﬃciency values measured at diﬀerent purity levels andrequire that they agree with each other. Since the electron lifetime is calculated via τe = −td / log(QA /QC ) (equation 3.6), electron lifetime values
become very vulnerable to small systematics of QA /QC when the purity ishigh and the argument of log, QA /QC , is close to 1. On the other hand, theelectron lifetime is not so strongly aﬀected when the purity is low. We vary α
and find the lower boundary of α that the agreement of the St707 eﬃciencies
in high and low purity holds.
We use such data obtained in April and May 2021. However, before going into details let’s overview what happened to the electron lifetime of thedetector after the period of Fig. 5.5. Fig. 5.8 is the electron lifetime trend
from February 2021, following Fig. 5.5. After the introduction of the Rn distillation column (section 2.6.4), the electron lifetime decreased significantly
due to huge outgassing from the Rn distillation column. After Rn column
85

5 Liquid purification in XENONnT
operations were over it was disconnected from the system on March 19th.
Unfortunately, the St707 filter looked to be saturated by a large amount of
impurity from the Rn column (see the diﬀerence of slope from March 19th
(saturated) and April 12th (fresh) in Fig. 5.8).
After some maintenance of the liquid purification system from the end of
March, we resumed liquid purification with St707. Since the St707 filter got
saturated by the impurities from the Rn column, we re-activated St707 byheating up to about 350 ◦ C before using it. The electron lifetime improved
quickly but the speed of improvement slowed down after a few days (theyellow periods from April 12th in Fig. 5.8). The eﬃciency seemed to decrease because it was used under low purity conditions but this was anotherconfirmation that the strategy we stated in section 4.4 is reasonable.
Since we failed to use St707, we returned to our original strategy: use Q5
filter first, switch to St707 when τe = O(1) ms. We did not regenerate
Q5 because we expected that its large adsorption capacity was still available.
The electron lifetime increased very quickly and soon reached around 5 ms
(red periods from April 16th in Fig. 5.8). While operating with Q5, the St707
filter was activated again in the same manner. After switching back to St707(yellow periods from April 21st in Fig. 5.8), we were able to keep the purity
above τe = 5 ms. At the end of April, gas purification was turned on (bothliquid (≈60 slpm) and gas phase (≈20 slpm)). The electron lifetime started
to increase slowly but this could not be due to the introduction of liquid
phase gas purification (L/GXePUR) because the time scale of purification τlis much longer than that of liquid purification. Our interpretation is that thisimprovement is due to the purification of the gas phase and the outgassing
source in the gas phase gradually reduced.
Let’s return to constraining the systematic uncertainty. As mentioned
above, important information to constrain the lower boundary of α is theeﬃciency of the fresh St707 filter just after the reactivation. The first suchdata is taken on April 12th, just after starting with reactivated St707. The
second one is the post-filter measurement performed on May 1st (gap at the
beginning of May in Fig. 5.8). Although almost 10 days had passed since it
was used, we assume that it is still fresh because we only used it in high purity
condition and that with this filter, we did not see a clear sign of eﬃciency
drop for more than four months (see final remark in section 6.5). Both data
are taken under 2.0 L/min flow rate. For the first data, we fit the electron
lifetime trend to get the eﬃciency of the filter as mentioned in section 4.1.1.
To be conservative, we assume that the outgassing rate is zero. The blueline in Fig. 5.9 is the eﬃciency of the filter just after the first reactivation(April 12th) as a function of α. The band is 1σ uncertainty obtained fromfitting. Since the electron lifetime was low at that time (a few hundred µs),
86

87

-0
2021

2-13
-0
2021

2-27

Disconnect Rn column

3-13

-0
2021

Purification maintenanceNo circulation, no purification

3-27

-0
2021

4-10

Restart with activated St707

-0
2021

Switch back to
re-activated St707

4
-04-2
1
2
0
2

Start GXePUR

Switch to Q5

Electron lifetime [ s]Figure 5.8: Electron lifetime trend after Rn distillation integration in February 2021. The yellow periods correspondto when St707 was in use and red corresponds to Q5. After the Rn distillation column started its operations,
unfortunately, electron lifetime dropped significantly. After removing the Rn column from the global system andreactivating St707, the purification resumed in April. The dashed line is the expected electron lifetime with gas
purification only scenario (same dashed line in Fig. 5.5).

102

103

Start Rn distillation

104

Expected electron lifetime
trend w/o LXePUR
Measured electron lifetime

5 Liquid purification in XENONnT

5 Liquid purification in XENONnTthe eﬃciency is not so sensitive to α. For the second data in May 1st, we
calculate the eﬃciency with the post-filter measurement following equation
3.8. The result is shown in the orange line of Fig. 5.9. Since the electron
lifetime was high for both pre- and post-filter measurement (pre: ≈5 ms, post:≈12 ms) at that time, small biases could lead to a big change in the electron
lifetime measurement (argument of log in equation 3.6 approaches one) as
well as filter eﬃciency estimations. That is the reason why the eﬃciency is
so sensitive to α.
We require that the eﬃciency from both measurements agrees with eachother. The contour in Fig. 5.9 is a 68% confidence region derived from theblue and orange band both assuming Gaussian distribution. Therefore, thelower boundary of α can be set to α > 0.9970, which is the smallest valueof the contour. We said that the zero outgassing assumption is conservative
because lower outgassing makes lower eﬃciency, and the boundary of α becomes the smallest when outgassing is zero. By combining these boundaries,
we obtain
0.9970 < α < 1.0023.
(5.2)
In addition, we observed instabilities in the QA /QC measurement a few
times. Since they were clear jumps rather than gradual changes, they are
most likely due to some deviations in the purity monitor condition such as
noise condition, systematic change in amplifiers or xenon lamp, but the truecause is unknown. Although this jump is small (0.1 to 0.3% in QA /QC ), it
was considered as another source of systematic uncertainty.
By combining these two systematics we can obtain the systematic uncertainty of the purity monitor measurement α′ . For α, we assume that it has
uniform distribution in the range of equation 5.2 and for systematics regarding jumps mentioned in the previous paragraph, gaussian uncertainty with
σ = 0.3% was assigned to QA /QC measurement. The [16,84]% interval of α′
is calculated to be
0.9963 < α′ < 1.0030,(5.3)
and the corresponding systematic uncertainty band of Fig. 5.5 is shown in
Fig. 5.10. For instance, at τe =1 and 10 ms, the systematic uncertainty bands
were [-2.3,1.9]% and [-19,23]% respectively.

88

5 Liquid purification in XENONnT

0.60

2021/04/12(Fitting trend)
2021/05/01(Post filter meas.)St707 efficiency

0.58
0.56
0.54
0.52
0.50
0.994

0.995

0.996

0.997 0.998 0.999
Correction factor

1.000

1.001

1.002

Figure 5.9: St707 eﬃciency as a function of correction factor α. The blueline corresponds to the eﬃciency with 2021/04/12 data and the orange is theeﬃciency from post filter measurement (2021/05/01). The bands show 1σ
uncertainties. The purple line is a 68% contour derived using the overlap of
blue and orange bands. The lower boundary of α is set to be 0.9970, whichis the left-most side of the contour.

Electron lifetime [ s]

104

103

102

14
10-

0202

28

10-

0202

1

1-1

0-1
202

25

11-

0202

09

12-

0202

3
2-2

0-1
202

-06
-01
1
2
20

20

01-

1202

Figure 5.10: Systematic uncertainty band of the electron lifetime measurement by the purity monitor. The red line inside the band is a smoothed
trend of electron lifetime from measured QA /QC .

89

5 Liquid purification in XENONnT

5.5

St707 filtering eﬃcency

Let’s constrain the absolute eﬃciency of the St707 filter. We use data in
May 1st (post-filter measurement, gap at the beginning of May in Fig. 5.8)
which was also used for the systematic uncertainty study of purity monitor
in section 5.4. This period was chosen rather than April 12th (pre-filter,
another data used to constrain systematics), because the post-filter measurement is independent of the outgassing rate which we don’t know for surearound that period. Using equation 3.8 and taking also into account the systematic uncertainty of purity monitor derived in section 5.4, the eﬃciencyof the St707 filter in XENONnT can be calculated. The orange line in Fig.
5.11 shows the relationship between the systematic factor α′ and the St707
eﬃciency (identical to the orange line in Fig. 5.9). The factor α′ is obtained
as equation 5.3, and a [16,84]% allowed region is described as the verticalblue band. Therefore, a corresponding St707 eﬃciency becomes the horizontal grey band, which is ϵL = 0.560+0.075−0.056 . The uncertainty is relatively large
because the measurement was conducted under high purity. The eﬃciencies
of filters used in XENONnT are summarized in Table 5.1 along with thecommissioning test results. In addition, we were able to continuously use
the St707 filter for more than four months without any sign of purity drop,
which is acceptable from the point of view of operation (see final remark ofsection 6.5).
It is desirable if we can discuss filter capacity (degradation) more quantitatively. However, from the nature of St707, it is hard to constrain thecapacity of the filter only from data of electronegative impurity taken by the
purity monitor because any non-inert molecules can react with St707 andcontribute to the saturation of the filter. Therefore we propose a measurement that would be useful to give further insights into the St707 capacity.
The idea is to partially saturate the fully-activated filter by supplying aknown amount of outgassing molecules such as oxygen, nitrogen and water(or any other kind) which are typical of outgassing in a vacuum system, andwe measure the eﬃciency in liquid afterward. If the process of saturationis conducted at room temperature, the diﬀusion of reacted surface does nottake place, and the eﬃciency of partially-saturated St707 can be measured.
From the experience of St707 filter operation from April 12, 2021 (see Fig.
5.8), the electron lifetime increased from 230 to 500 µs which corresponds tothe oxygen removal of about 1.5 mg, and thus the capacity of the St707 filter
used in XENONnT is at least 1.5 mg of oxygen. It is possible to supply such
an amount of oxygen if we flow 1 m3 of argon gas with 1 ppm of oxygen. By
this test, we expect to get a relationship between the eﬃciency and adsorbed
quantity.
90

5 Liquid purification in XENONnT

0.70

St707 efficiency

0.65
0.60
0.55
0.50
0.45
0.40
0.990

0.992

0.994

0.996 0.998 1.000
Systematic factor '

1.002

1.004

Figure 5.11: St707 eﬃciency estimation. The orange line is the relationshipbetween systematic correction factor α′ and St707 eﬃciency from data of
May 1st 2021. The vertical blue band is 1σ allowed region of α′ derived
in the previous section. The horizontal grey band is a corresponding St707
eﬃciency interval.

91

Filter
Mass [g] Initial eﬃciency Flow rate [L/min] Filter lifetime Initial purity [µs]
XENONnT
Q5
475
1
2.0
> 1 month130+0.075St707
3000
0.560−0.056
2.0> 4 month
5000
Commissioning
Q5
18
0.34 ± 0.02
0.6 Not measured
32
Q560
0.24 ± 0.01
1.5
22 h
46
Q5
11
0.105 ± 0.005
1.5
30 h
34
Q5
60
0.385 ± 0.005
1.5
14 h
150
St707
2400
0.67 ± 0.01
1.5
11 h
55

92

Section 4.2.3
Section 4.2.4
Section 4.3.2
Section 4.3.4
Section 4.3.3

Section 5.2
Section 5.5

Reference

Table 5.1: Summary of the filter eﬃciencies measured in this thesis. Both results from commissioning and XENONnT
are shown. For the eﬃciencies of Q5 and St707 in XENONnT, only lower limits are shown because we did not see
any obvious sign of eﬃciency loss.

5 Liquid purification in XENONnT

5 Liquid purification in XENONnTIn the commissioning test presented in the last chapter, we tested theSt707 filter of diﬀerent amounts and geometry. The initial eﬃciency was
ϵL = 0.67 ± 0.01 at 1.5 L/min (see section 4.3.3). Table 5.2 shows the measurements of the initial eﬃciency of St707 along with basic information aboutpellet geometries. If the contact time theory (see section 4.4.2) is correct forSt707 as well, we are able to explain the XENONnT St707 eﬃciency by theeﬃciency measured in the commissioning. Unlike Q5, the St707 pellets usedin the commissioning and XENONnT had diﬀerent geometry, thus the mass
is not proportional to the surface area of the filter. Since filtering reaction
happens at the surface of the material, it would be more reasonable to use
total surface area S rather than mass M in the equation 4.4. If we denotethe total surface area of St707 in XENONnT and the commissioning by S
and S ′ , the predicted eﬃciency of XENONnT (ϵL ) can be expressed as inequation 5.4(S/f )/(S ′ /f ′ )ϵL (f, S) = 1 − (1 − ϵ′L (f ′ , S ′ ))

,

(5.4)

using the eﬃciency in the commissioning (ϵ′L ), where f = 2.0 L/min andf ′ = 1.5 L/min are the flow rates of liquid xenon in XENONnT and thecommissioning. The ratio of total surface area S/S ′ is 1.04 from the geometrical calculation. Then, the eﬃciency of St707 for XENONnT at 2.0 L/min ispredicted to be ϵL = 0.58 ± 0.01, which agrees with the actual measurement.
This result, combined with the Q5 results, indicates that the contact time
theory is generally applicable to predict the filtering eﬃciency of diﬀerent
material amounts and flow rates.
Table 5.2: St707 filter eﬃciency
Date
Phase
Amount [kg]Diameter [mm]Height [mm]Flow rate [L/min]Eﬃciency

5.6

2020/02/06 2021/05/01
Commissioning XENONnT
2.4
3.0
4
6
2
2
1.5
2.0
+0.0750.67 ± 0.01 0.560−0.056

Radon rate in the detector

One important aspect of this work is how to achieve high xenon purity
while keeping a low 222 Rn rate because the radon daughter, 214 Pb, is the93

5 Liquid purification in XENONnTbiggest source of background (see section 2.8). Although TPC can discriminate 214 Pb events (ER) from NR, a small fraction of ER events can leak into
the NR region, and it becomes the background. Since 222 Rn and some of
their daughters are α decay isotopes (summarized in Table 5.3 or Fig. 2.9),
they leave characteristic S1s in the detector.
Fig. 5.12 shows the Area Fraction Top vs Area of S1s. Area is a sum of
number of photoelectrons seen by both top and bottom array of the TPC,
and Area Fraction Top is the fraction of photoelectrons seen by the top arrayof PMTs and can be used as a measure of vertical position. Events withsmall Area Fraction Top (bottom events) tend to have larger Area becauseinteractions happen closer to the bottom PMT array. Events with large Area
Fraction Top (top events) have smaller Area due to reflection at the liquidsurface, even though the interactions happen closer to the top PMT array.
We use the population in red dashed lines (210 Po+222 Rn+218 Po) to calculateradon rate. The selection window can shift with time in case small changes
in light yield occurs.
Table 5.3: Energies of α rays from 222 Rn and its daughters.
Isotopes [MeV]
210
Po
5.3
222
Rn
5.5
218
Po
6.0
214
Po
7.7
The event rate evolution inside the red dashed lines of Fig. 5.12 is shownin Fig. 5.13. It is very clear that the event rate increase dramatically afterQ5 was in use (at around t = 0 d), which is consistent with our expectationof its huge radon emanation rate. The rate reached above 700 mHz andflattened. At around t = 26 d, we switched to St707 and the event rate
gradually decreased to the original level. It means that St707 does not havea significant impact on the overall 222 Rn budget and can be used for long-term
operation.
The event rate evolution model can be described by
(if t < t0 ),
R0
(5.5)
R(t) = R1 · (1 − exp(−λRn222 (t − t0 ))) + R0 (if t0 < t < t1 ),
R2 · exp(−λRn222 (t − t1 )) + R3
(if t1 < t),where λRn222 = ln 2/τ1/2 (τ1/2 is half-life of 222 Rn). The transition timingt0 (=-0.75 d) and t1 (=25.8 d) are the timings when Q5 and St707 were94

5 Liquid purification in XENONnTFigure 5.12: ROI of S1s for α’s from 222 Rn and its daughters. There are a
few clusters which correspond to those events. Events in red dashed lines
are α’s from 210 Po+222 Rn +218 Po. The cluster next to 210 Po+222 Rn+218 Po
is 214 Po.
integrated. The first equation is for before the Q5 filter and R0 is the baseline
rate. The second equation is for the Q5 term and R1 is the equilibrium ratefrom Q5. The third equation is for the St707 term. The parameter R2 is therate from the remnant Q5 radon at the beginning of this term and R3 is a
new baseline with St707. Apparently, we have four fitting parameters but
we can eliminate R2 by requiring continuity at t = t1 ;R2 = R0 − R3 + R1 · (1 − exp(−λRn222 (t1 − t0 ))),

(5.6)

and we fitted R0 , R1 and R3 to the data. The red line in Fig. 5.13 is the best
fit rate evolution model. As you can see, the rise and the drop of the event
rate can be explained well by the model of 222 Rn half-life. Equilibrium rates
from Q5 and St707 filter were obtained to be 749 ± 5 mHz and 2 ± 4 mHz
respectively.
Thanks to the low 222 Rn emanation rate of the St707 filter, as well asother 222 Rn screening eﬀorts and the novel radon distillation system (section
2.6.4), we finally achieved 1.7 µBq/kg at the point of thesis writing, whichis the lowest ever achieved 222 Rn level in the liquid xenon TPC [70]. For
95

5 Liquid purification in XENONnT
comparison, in the Science Run 1 (SR1) of XENON1T on which most of
the physics results from XENON1T were based, the concentration was 13µBq/kg [22]. Note that at this stage, the radon distillation system removed
222
Rn only from the gas phase of the cryostat. It is expected that the radon
distillation from the liquid phase would reduce 222 Rn activity by anotherfactor of two and the ultimate goal, 1 µBq/kg, would be achieved.

Rate [Hz]100

Model with Rn decay time
Rate in the selection region

10 1

0

10

20
30
40
Days since 2020/11/06

50

60

Figure 5.13: Evolution of the combined event rate from 210 Po+222 Rn +218 Po
alpha decays. Q5 was in use since t = −0.75 d. At t = 25.8 d, the filter was
switched to St707. Blue points are measured rates and red line is a model toexplain the trend with 222 Rn decay time.

96Chapter 6
Electron lifetime from TPC
data
Up to this chapter, the electron lifetime was measured with the purity
monitor installed in the liquid purification circuit. However, once the TPC is
operational, the electron lifetime can be calculated by looking at events frommonoenergetic decays in the TPC. Charge signal (S2) size must decrease exponentially with drift time and the decay constant is essentially the electron
lifetime. Although high purity was already confirmed with the purity monitor, it is necessary to check it in TPC data because this is what we exactly
want to achieve. Furthermore, since the electron lifetime is a key parameterof the TPC response, it will ultimately be used in any physics data analysis.
In this chapter, electron lifetime is calculated using various sources (83m Kr(section 6.2), radon alphas (section 6.3) and xenon activated lines (section6.4)). In section 6.5, we show the time evolution of the electron lifetime from
TPC data. In section 6.6, the achieved electron lifetime is compared withpast experiments. We also discuss the applicability of the new purification
technique to future large-scale liquid xenon experiments.
Note that the electric field inside the TPC was about 23 V/cm which
is much lower than the design (200 V/cm) and purity monitor (100 V/cm).
This is because we had diﬃculty in raising the cathode voltage further but
still we showed that TPC is operational under such a low field.

6.1

Basic data selection

We have dedicated selection rules for each source. However, there aresome common data selections which are deeply related to the detector principle. In this section, S2 Width cut and S1 Area Fraction Top (AFT) cut976 Electron lifetime from TPC data
are introduced as such cuts.
S2 Width is defined as a time diﬀerence between 25% and 75% of S2 pulse
cumulative area. S2 Width has correlation with drift time because the widthof pulses get wider due to diﬀusion of drift electrons. Fig. 6.1a shows such a
correlation (data from activation line study in section 6.4). Width σ of theS2 pulse can be characterized by
√
2DL t
σ=
+ σ02 ,
(6.1)
vd2
where t is the drift time, vd is the drift velocity, DL is the diﬀusion coeﬃcientand σ0 is a free parameter [71]. The red lines in Fig. 6.1a are the equation
6.1 shifted upward and downward to select properly reconstructed events
between them. A clear boundary at around 2.2 ms of the drift time is due tothe cathode electrode which defines the deepest of the TPC sensitive volume.
S1 Area Fraction Top is already introduced in section 5.6 and it can also
be a measure of the deepness of events. Therefore it has a strong correlation
with the time diﬀerence between S1 and S2 (drift time). Fig. 6.1b shows
events (again data from activation line study in section 6.4) in S1 AFT vsdrift time parameter space. There is a clear correlation between S1 AFT anddrift time, and events between the red lines are selected.
20000

1.0

17500

104

12500

103

10000
102

7500
5000

101

2500
00

500

1000 1500 2000
Drift Time [ s]

2500

3000

104

0.8
S1 Area Fraction Top

S2 Width [ns]

15000

100

0.6

103

0.4

102

0.2

101

0.0 0

(a) S2 width cut

5001000 1500 2000
Drift Time [ s]

2500

3000

100

(b) S1 Area Fraction Top (AFT) cut

Figure 6.1: (a) S2 Width and (b) S1 Area Fraction Top (AFT) cut are
fundamental cuts related to the detection principle of TPC. Events between
red lines are selected by these cuts.

986 Electron lifetime from TPC data

6.2

Electron lifetime from 83mKr

As already mentioned in section 2.7.1, 83m Kr is a monoenergetic ER calibration source which is useful for the characterization of many detector
parameters including electron lifetime, and calibration data is taken every
two weeks or so. Sequential emission of 32.2 and 9.4 keV conversion electrons is a distinct feature of this isotope and it is distinguishable. Fig. 6.2
shows an example waveform of a 83m Kr event with two S1s. However, since
9.4 keV emission happens after 32.2 keV with a half-life of t1/2 = 154.4 ns,
a large fraction of 83m Kr events has overlapped S1s. To select events withseparate S1s, the cut required S1 time diﬀerence to be between 400 and 2000
ns. Using dedicated selection criteria for 83m Kr we can select 83m Kr double
S1 events as shown in Fig. 6.3.
S1
S2

S1

S2
41.6 keV
7331.38 PE

32.2 keV
350.99 PE
9.4 keV110.16 PE

Figure 6.2: Example waveform of 83m Kr events. Top plot shows waveform of
entire event (S1 and S2). Bottom plot shows zoomed waveform for both S1and S2. It is clear that there are two S1s which corresponds to 32.3 and 9.4
keV electron emission respectively.
In addition, a fiducial volume cut was applied (definition of the coordinate
system in Appendix B) to select events only inside r < 60 cm and drift time
200 < td < 2100 µs. This cut is expected to remove events near the edge of
the TPC where there are more contaminations from the wall and the detector
is not well understood (e.g. stronger field non-uniformity). Although fiducial
volume for physics searches is determined by many factors of analysis, we use
fiducial volume naively defined here which has approximately 4 t mass (design
fiducial volume). This fiducial volume is used for other sources as well. Since996 Electron lifetime from TPC data

300
250
Second cS2 [PE]

102

200
150
101

100
50
0

0

100

200
300
First cS1 [PE]

400

500

100

Figure 6.3: 83m Kr double S1 population. Double S1 is a distinct feature of
83m
Kr decay. First cS1 and second cS1 are cS1s from 32.2 keV and subsequent 9.4 keV respectively, where cS1 is S1 size corrected with 3D position
dependence of light collection eﬃciency (see Appendix B).
we use S2s to calculate electron lifetime, S2 horizontal (xy) correction isapplied to correct the position-dependent S2 yield (see Appendix B).
Fig. 6.4a shows an example of selected 83m Kr events in drift time vs S2 size(S2 bottom) space. Data is from August 24th, 2021. S2 bottom is the S2 area
seen by the bottom PMTs and it was selected because S2s observed by the
top PMTs have stronger position dependence (see Appendix B). XENON1T
also adopted this method. One thing to note is that S2 size can be considered
as a sum of two S2s because almost all S2s from 32.2 and 9.4 keV decay merge
together due to wider width compared to S1s. The black points are medianS2 size in each 100 µs bin slice of drift time. S2 size decreases as drift time
gets longer. By fitting with an exponential function
)
(
t
,
(6.2)
f (t) = S20 exp −τeelectron lifetime τe was obtained to be 14.6 ± 0.7 ms for this dataset.
One factor that could cause systematics is the electric field. Electrons
generated by a recoil recombine with nearby xenon ions more frequently
when the electric field is low, which results in electric field dependence of
charge yield. Because of this, if there is a field non-uniformity inside the
TPC (especially inside the fiducial volume), it could result in the wrong
estimation of electron lifetime. The finite element method was used to nu100

6 Electron lifetime from TPC data
merically calculate the static electric field map inside the TPC (Fig. 6.5a).
The field dependence of charge yield in 83m Kr decay is calculated using apython framework called nestpy provided by NEST [36] (Fig. 6.5b). Using
this information, in principle, we can compensate for the possible eﬀect offield non-uniformity. Fig. 6.4b is the electron lifetime fitting using S2 bottom
with a field correction using the same data set (τe = 13.4 ± 0.4 ms).
Although the field correction sounds reasonable, there are some caveats.
The first one is that we are not sure how valid the electric field simulation
is because the electric field could be distorted by an accumulated charge on
the PTFE reflector wall for instance. Another issue is about the reliabilityof the NEST model. The NEST model is an empirical model based on many
noble liquid experiments but most of those experiments were conducted undermuch stronger electric fields (≥ O(100) V/cm) and the charge yield at 23
V/cm (XENONnT) is just an extrapolation from them. Since it is hard tomodel those systematic eﬀects, they are not considered in this study.
4000
3500
3000

3000

2500

2500

2000
1500

2000
1500

1000

1000

500

500

0

0

500

1000 1500
Drift time [ s]2000

EL: 13401 +- 369 s

3500

S2b [PE]

S2b [PE]

4000

EL: 14627 +- 705 s

0

2500

0

500

1000 1500
Drift time [ s]

2000

2500

(a) 83m Kr electron lifetime w/o field cor- (b) 83m Kr electron lifetime w/ field correction.
rection.

Figure 6.4: Example of electron lifetime calculation. Figure (a) shows theelectron lifetime calculation with S2 bottom (S2b) without field correction
and Figure (b) shows the same calculation but with field correction. Black
points are median of each bin slice and red lines are fitting functions. Black
points in between 200 to 2100 µs were used for fitting. Both are calculated
from data taken in August 24th, 2021.

101

6 Electron lifetime from TPC data

1.15

83mKr
222Rn

Relative charge yield Q/Q0

1.10

1.05

1.00

0.95

0.90

20

(a) Electric field inside the sensitive volume.

22

24
26
Electric field [V/cm]

2830(b) Relative charge yield.

Figure 6.5: Figure (a) shows the electric field distribution inside the TPC
sensitive volume. Figure (b) shows the field dependence of charge yield Q
from NEST framework. Q0 is charge yield at 23 V/cm, which is typical fieldin the TPC. 222 Rn has stronger field dependence than 83m Kr.

6.3

Electron lifetime from Radon alpha decays

222

Rn is an isotope in the 238 U chain and emanated from every detectormaterials. Since 222 Rn is the biggest source of background for the XENONnT
experiment, a great deal of eﬀort was put into mitigating it. However, we
still have enough activity in the detector to investigate electron lifetime frommonoenergetic alpha rays of 222 Rn and its daughter 218 Po. The biggest advantage of this source is that it is always in the detector and the electron
lifetime can be calculated at any time.
As mentioned in section 5.6, radon alphas have outstandingly large S1s
because alpha’s high energy and big stopping power create big and localizedenergy deposition, and a large fraction of ionized electrons recombines withparents or nearby xenon ions. Fig. 6.6a is a region of interest for radonalpha events which have very large S1s. Fig. 6.6b shows the removal of highenergy γ ray events which have larger S2 compared to alphas. Both cuts are
just coarse selections. After that, S2 Width cut (see Fig. 6.1a) and S1 Area
Fraction Top cut (6.1b) were applied in the same manner.
After these selections, we plotted the remaining events in S1 Area vs drift
time space (Fig. 6.7a). Main population is a combined band of 222 Rn and1026 Electron lifetime from TPC data

107

4.5

3.0
102

2.5

105
Accepted

103

3.5

S2 Area (PE)log10 S1 Width [ns]

102

106

4.0

104

101

101

103

2.0

101

1.5
1.0

102

104

Rejected

5.0

1

2

3
4
log10 S1 [PE]

5

6

100

102
101

50000

(a) ROI 1

100000150000S1 Area (PE)

200000100

100(b) ROI 2

Figure 6.6: (a) TPC events in S1 width (50% area range) vs S1 area. Large
S1 events inside the red box are selected since this is a characteristic of alphaS1s. (b) Red line removes high energy gamma candidates which has relatively
larger S2s but smaller S1s. Selection in Fig. 6.6a is already applied to makethis figure.

1e6120000

2.5

101

101

60000

1.5
1.0
0.5

40000
0.0

Number of entries

80000

Drift time [ns]2.0
Number of entries

S1 Area [PE]100000

0.5

1.0
1.5
Drift time [ns]

2.0

2.5

100
1e6

(a) Before S1 correction

0.0

40000

60000
80000
100000
Corrected S1 Area [PE]120000100(b) After S1 correction

Figure 6.7: (a) Radon events in S1 Area vs drift time space. Main bands
is from 222 Rn and 218 Po and faint band above is from 214 Po. Red points
are medians of 222 Rn and 218 Po band and black dashed line is a fitting line
used to correct S1 drift time dependence. (b) Radon events in drift time vscorrected S1 area. Correction is based on the black dashed line in Fig. 6.7a.
The band is more straight that in Fig. 6.7a.

103

6 Electron lifetime from TPC data
218

Po, and a faint band above the main band is from 214 Po. The black dashedline in Fig. 6.7a is the fitting line of the band median (red points) and thisline was used to correct the drift time dependence of S1 area. The fitting
function isa −x (
a −x )− 1− 1
f (x) = a0 e a2 1 − e a2 + a3 ,(6.3)
where a0 , a1 , a2 and a3 are fitting parameters. Fig. 6.7b shows the drift
time vs “corrected” S1, which has much less drift time dependence. After“correcting” S1s, radon alpha population is plotted in “corrected” S1 Areavs r2 parameter space which is shown in Fig. 6.8. It is clear that the twobands from 222 Rn and 218 Po (and also 214 Po) are separated with each otherand they can be selected easily. Population around r2 = 4400 cm2 is α eventsfrom 210 Po which tend to stay on the PTFE wall.

Po214

Po218

Rn222

Figure 6.8: Radon alpha events in “corrected” S1 vs r2 space. Red lines canbe used to separate 222 Rn and 218 Po events. Population around r2 = 4400
cm2 is 210 Po which tends to stay on the PTFE wall.
After selecting the radon alpha events and applying fiducial volume cut(same as in 83m Kr case), the population was fitted with an exponential function in a parameter space of S2 area vs drift time space. Fig. 6.9a is an
example of fitting using 222 Rn. The eﬀect of electric field (see Fig. 6.5b) isalso considered (Fig. 6.9b). The discrepancies between data and the fitting
are moderated (though not perfect).

104

6 Electron lifetime from TPC data

EL: 13732 +- 1772 s

12000

12000

10000

10000

8000
6000

8000
6000

4000

4000

2000

2000

0

0

500

1000 1500
Drift time [ s]EL: 12079 +- 1004 s

14000

S2b [PE]

S2b [PE]

14000

0

2000

0

500

1000 1500
Drift time [ s]2000(a) Electron lifetime from 222 Rn w/o field (b) Electron lifetime from 222 Rn w/ fieldcorrection
correction

Figure 6.9: (a) Electron lifetime calculation using 222 Rn alphas. Blue points
are radon events and black points are medians of the band. Black solid line
is a fitting function, which gave τe = 13.7±1.8 ms. (b) Electron lifetime with
222
Rn taking into account the field correction (τe = 12.1 ± 1.0 ms). Both arecalculated using data in August 17th, 2021.

105

6 Electron lifetime from TPC data

6.4

Electron lifetime from xenon activated lines

Any monoenergetic sources with a reasonable amount of statistics canbe used for the electron lifetime calculation. For example, when TPC iscalibrated with neutron sources such as AmBe, xenon atoms in TPC can get
activated to be 129m Xe (half-life: 8.9 d) and 131m Xe (half-life: 11.8 d) [72].
They de-excite with γ emission of 236 and 164 keV respectively and those γrays can be used for the electron lifetime calculation. However, 129m Xe and131m
Xe are only available for a week or two after neutron calibration, so it is
not useful to characterize a long-term trend of the electron lifetime.
Fig. 6.10 shows the activation lines of 129m Xe and 131m Xe in cS1 (S1 corrected with position-dependent light collection eﬃciency map) vs cS2 (S2corrected with xy position-dependent S2 size map and electron lifetime) parameter space using data from May 30th to June 6th, 2021. To constructcS2, the electron lifetime obtained from 83m Kr was used. The two populations for 129m Xe and 131m Xe were fitted with 2D elliptical Gaussian andselected events within 3σ, which is shown in black lines. After correcting theelectric field dependence of charge yield, those populations were fitted withan exponential function in the same manner. Obtained values are shown in
Fig. 6.11 in section 6.5 along with lifetimes from other sources.

100000cS2 [PE]

80000
101

60000
40000
20000
0
1000

1500

2000
cS1 [PE]

2500

3000

100

Figure 6.10: Activated xenon events were clearly visible in cS1 vs cS2 parameter space. Events inside the black elliptical lines were selected for thefollowing analysis.

106

6 Electron lifetime from TPC data

6.5

Time evolution

Fig. 6.11 shows the electron lifetime evolution from TPC data (83m Kr(black), 222 Rn (red), 218 Po (green), 129m Xe (magenta), 131m Xe (orange)).
These electron lifetimes are calculated using S2 bottom and the electric fieldcorrection is also taken into account. The purity monitor measurement isalso plotted with an uncertainty band. To construct the band, we first calculated median of every 100 lifetime measurements and assigned uncertainty
interval calculated using the method shown in section 5.4.
The electron lifetime increased since the beginning of May and reached
the plateau by the end of the same month. At the end of June, the radon
distillation system was reconnected to the global system, extracting only fromthe gas phase of the cryostat this time. Unfortunately, we observed a drop in
the electron lifetime and we decided to flow xenon from the radon distillation
outlet through hot getters in the gas purification system before returning to
the cryostat. Thanks to the online measurement of the purity monitor, wewere able to make a quick decision before spoiling the electron lifetime to thesub-milliseconds level. This is a good example of the fourth bullet in section
3.6. The electron lifetime started to improve again and reached a plateau atτe = 13.5 ± 0.2 ms from 83m Kr. The plateau value was higher compared toJune 2021 probably because the gas-phase circulation speed increased by the
integration of the radon distillation system (20 → 29 slpm).
We see discrepancies of the electron lifetimes obtained from radon alphas
and 83m Kr (e.g. τe = 11.2 ± 0.2 and 13.5 ± 0.2 ms at plateau respectively).
Such a problem was already reported by XENON1T, e.g. τe = 660 µs (83m Kr)
and 590 µs (222 Rn) [33]. A possible explanation could be that the electricfield map used for this study is not accurate enough. Since the charge yieldof radon alphas has stronger field dependence compared to 83m Kr (see Fig.
6.5b), a bias on lifetimes from radon alphas could be stronger. Actually,an exponential fit for radon alphas is not perfect even after field correction(see Fig. 6.9b). This is one of the reasons why we tend to believe that theelectron lifetime from 83m Kr is closer to the real electron lifetime than radonalphas. As mentioned in section 3.6, the purity monitor could have given
another insight into the problem of lifetime discrepancies. However, since
the purity monitor has relatively large uncertainties in the measurement ofhigh electron lifetime, it was hard to argue further with purity monitor data.
From the point of view of a science data analysis, we need a timedependent electron lifetime trend to correct the z dependence of S2 signals.
The question is whether we should use electron lifetime from radon alphas
or 83m Kr. Again 83m Kr would be a better choice because we are mostlyinterested in low energy events and 83m Kr is closer both in energy and par107

108

0 2021-05-11 2021-05-25 2021-06-08 2021-06-22 2021-07-06 2021-07-20 2021-08-03 2021-08-17 2021-08-31

5000

10000

15000

20000

25000

Purity monitor
83mKr
222Rn
218Po
129mXe131mXeFigure 6.11: Electron lifetime evolution from various sources (83m Kr (black), 222 Rn (red), 218 Po (green), 129m Xe(magenta) and 131m Xe (orange)). Field correction is applied. Purity monitor uncertainty band is shown in blue.

Electron lifetime [ s]30000

6 Electron lifetime from TPC data

6 Electron lifetime from TPC data
ticle type. XENON1T also used 83m Kr for science data analyses. Moreover,thanks to a much longer electron lifetime compared to the maximum drift
time of TPC (2.2 ms), even if we use radon alpha lifetimes, the diﬀerence issmall. Corrected S2s can get biased only by 1.6% (6.5% in XENON1T) on
average with the choice of lifetime sources, while energy resolution of liquid
xenon TPC is typically worse than 10% in the low energy region that we aremainly interested in.
As a conclusion of this section, we achieved τe = 13.5±0.2 ms at maximum
using TPC 83m Kr, and the trend of electron lifetime was consistent with thatof the purity monitor which had been used throughout commissioning. This
electron lifetime is equivalent to about 0.02 ppb of oxygen concentration.
Also, it is important to note that the St707 filter had been used from April(see Fig. 5.8) to August 2021 without reactivation. This result guarantees
that the frequency of the St707 reactivation is at least less than once per fourmonths, which is acceptable from the operational point of view.

109

6 Electron lifetime from TPC data

6.6

Comparison of the achievement with pastand future experiments

The XENONnT electron lifetime reached τe = 13.5 ± 0.2 ms at maximum
calculated from 83m Kr data. This is the first time that such high purity isachieved in a liquid xenon detector and it is even more impressive considering
the amount of liquid xenon (8.6 t). For comparison, in the Science Run 1(SR1) of XENON1T (3.2 t of xenon), we were able to reach only about 0.66
ms of electron lifetime. The survival probability of drift electron from thecathode is 85% for XENONnT while it was 35% in XENON1T.
It is also useful to see what happened if we had used conventional gasphase purification only. The dashed lines in Fig. 5.5 and Fig. 5.8 are an
expected electron lifetime evolution with gas purification only. The assumption is that the liquid phase gas purification (L/GXePUR) speed is 60 slpm
and the outgassing rate is 0.09 mg/d obtained in section 5.1. We can seethat the achieved electron lifetime (13.5 ms) was more than 30 times higher
than what we would achieve with a conventional gas purification system only(τe ≈ 0.4 ms). Although the gas purification system can handle more flow
rate, since the gas purification system needed to take care of the gas flowfrom the radon distillation system as well under the current configuration,
the flow rate in this assumption (60 slpm) was a realistic maximum at the
point of thesis writing. Therefore, by this achievement, the sensitivity of the
XENONnT detector to 50 GeV/c2 WIMPs improves by a factor of three (seeFig. 3.3) compared to gas purification only scenario.
Finally, let us compare the achieved electron lifetime with future large
liquid xenon experiments. nEXO is a projected neutrinoless double-beta
decay search experiment in 136 Xe. They utilize a similar TPC techniqueand oﬃcially state that they need 10 ms of electron lifetime to maximize
their energy resolution and acquire the best performance of the detector [73].
Achievable electron lifetime is determined by outgassing rate and purification
speed, but it is diﬃcult to predict it because of the unknown outgassing rate.
However, if we assume that the outgassing is a surface phenomenon and thesurface area of a detector is ∝ (volume)2/3 , we can estimate the achievable
electron lifetime. The electron lifetime reaches a plateau when purificationand outgassing speed equilibrate. This can be translated to dN/dt = 0 in
equation 4.1. As electron lifetime τe is proportional to M/N , we can derive
τe ∝

M
M
fL
= ΛτL = ϵL .
NΛϵLThe gas purification term is neglected because it is subdominant.
110

(6.4)

6 Electron lifetime from TPC datanEXO plans to use 5.1 t of liquid xenon [73]. Thus if they used the same
purification procedure as we did here (amount of filter, flow speed, etc.),
the outgassing rate of nEXO would be (5.1/8.6)2/3 and the corresponding
electron lifetime would be 13.5 (XENONnTvalue) × (8.6/5.1)2/3 = 19.1 ms
which is far beyond their goal. Another good example is the DARWIN experiment [74]. DARWIN is a next-generation dark matter search experimentthat plans to utilize about 50 t of liquid xenon. Since DARWIN will use theliquid xenon TPC technique as well, the minimum required electron lifetime
can be estimated by the maximum drift time in the TPC. By assuming thatthe drift length of TPC is 260 cm and the drift velocity of electrons is 1.5mm/µs, the maximum drift time in the TPC would be 1.7 ms. Under thesame assumption of outgassing rate as above, the outgassing rate would be(50/8.6)2/3 times higher than XENONnT and the expected electron lifetime
would be 13.5 (XENONnTvalue) × (8.6/50)2/3 = 4.2 ms. This is about 2.5
times longer than the maximum drift time of the TPC. From the fact that
St707 did not show any sign of saturation for > 4 months, the lifetime of
the filter would be scaled to > 4/(50/8.6)2/3 = 1.2 months. In XENONnT,the filter switch operation can be done within half a day, thus even if thefilter switch happens every month, the dead time would be relatively small.
It seems that this technique is promising for future large liquid xenon experiments. One caveat of this estimation is that the outgassing budget isassumed to simply scale as ∝ (volume)2/3 which might be incorrect. To beable to discuss the performance of St707, especially the lifetime of the filter
eﬃciency, under diﬀerent outgassing scenarios, the measurements of filter
capacity such as the one proposed in section 5.5 would be useful. Also, it isimportant to note that we can still increase the amount of St707 thanks to
the low radon emanation rate.

111

Chapter 7
Conclusion
Many cosmological observations suggest the existence of dark matter. The
XENONnT experiment aims to detect WIMP dark matter with the worldleading sensitivity of 1.4 × 10−48 cm2 scattering cross section for 50 GeV/c2
WIMPs. The XENONnT detector utilizes a liquid xenon dual phase time
projection chamber (TPC) technique and requires a low concentration ofelectronegative impurities in order to reduce the loss of drift electrons. Less
attenuation of electrons makes signal resolution better and results in stronger
discrimination of background. The amount of electronegative impurities isquantified by a parameter called electron lifetime τe , which represents theattenuation time of drift electrons and the goal was set to be τe = 3 ms
to achieve the required discrimination power, 99.9%, and as a result, theprojected sensitivity of XENONnT. However, since the XENONnT detector
keeps an unprecedentedly large amount of liquid xenon, we would achieve
only about τe = 400 µs of the electron lifetime with the conventional gas
purification system. Therefore, we needed to develop an eﬃcient purification
technique.
Unlike the existing purification systems, the new purification method circulates xenon in the liquid phase. Taking advantage of ≈ 500 times larger
density of a liquid compared to gas, we expected higher purification speedwith small flow rates. One of the challenges of this development was to findfilter materials that can remove electronegative impurities eﬀectively and do
not have a large 222 Rn emanation rate because the purification techniquewith the same concept, circulation/purification in the liquid phase, utilizes
impurity removal filters with a huge 222 Rn emanation rate. Beta-decay of222
Rn progeny, 214 Pb, is the biggest source of background to a dark mattersearch and thus should be avoided as much as possible.
Tests were performed using about 2 t of liquid xenon to understand thefunctionality of liquid filter candidates. During the tests, liquid xenon was112

7 Conclusion
flown into the filter and monitored the evolution of electron lifetime by a
dedicated device called a purity monitor. Two filter materials were shown
to be useful for the new purification technique after a few tests at the commissioning. The first one is alumina pellets coated by copper called Q5.
This material has been used for liquid argon experiments for a similar purpose, and large filtering eﬃciency and capacity were demonstrated by thetests. However, the only problem was its high 222 Rn emanation rate (O(100)mBq/kg) and thus it was not suitable for use in science data taking. The
second filter candidate is a non-evaporable getter material called St707. It
is often used in vacuum or gas systems to remove impurity molecules but
we tried to use it under the liquid xenon environment. The advantage ofthis filter was its very low 222 Rn emanation rate (0.24 ± 0.03 mBq per 3 kg
filter unit), and the disadvantages were lower filtering eﬃciency and capacity
per unit mass compared to Q5. Both filters can be regenerated/reactivatedunder dedicated procedures.
Considering the advantages and disadvantages of the two filter candidates,
we proposed to use those two filters in order. First, we use a large amount of
the Q5 filter (475 g) to clean the bulk of the initial non-purified liquid xenon.
Thanks to the excellent eﬃciency and capacity of the Q5 filter, it is expected
to reach O(1) ms of electron lifetime without saturating Q5. After reachingsuch high purity, we switch to St707 (3.0 kg). Although the eﬃciency andcapacity are not as high as Q5, since St707 deals only with small outgassingthat constantly emanated in the liquid, we expect several months of a lifetime
before getting degraded. When the filter is switched to St707, there is a lotof 222 Rn from Q5 in the system but thanks to 3.8 days of half-life, it will be
negligible after a month.
Using this strategy, we started to purify 8.6 t of xenon in the cryostat
with the XENONnT TPC. The electron lifetime reached τe = 5 ms after
one week of Q5 operation. After switching to St707, we successfully kept
the electron lifetime in milliseconds order and we did not see any sign ofeﬃciency loss (electron lifetime decrease) after four months of operation.
The eﬃciency of the St707 filter in XENONnT was estimated to be ϵL =0.560+0.075−0.056 . Maximum achieved electron lifetime was τe = 13.5 ± 0.2 ms(equivalent to about 0.02 ppb of oxygen concentration) calculated from 83m Kr
data. This was the first time that such high purity was achieved in a liquid
xenon detector and it is even more impressive considering the amount ofxenon we have. It was also shown that the radon rate from the St707 filter
was negligible, which meant that this technique was compatible with science
data taking of a dark matter search.
Table 7.1 summarizes the main achievements of this work along withtarget and XENON1T Science Run 1 (SR1) values. Target values are the1137 Conclusion
Table 7.1: Main achievements of this work.
Electron lifetime [ms]222
Rn rate [µBq/kg]

Target Achieved XENON1T SR1
3
13.5
0.66
1.0
1.7
13

required electron lifetime and radon rate in order to reach the projected
sensitivity of 1.4 × 10−48 cm2 (50 GeV/c2 WIMPs) with 20 t y exposure. The
achieved electron lifetime, τe = 13.5 ms, is far beyond the target value (τe = 3ms). Thanks to the negligible 222 Rn emanation rate of St707 and novel 222 Rn
distillation system (gas-only mode), as well as other material screening, the222
Rn rate, 1.7 µBq/kg, is the lowest ever achieved in liquid xenon detectors,
but it is still above the target (1.0 µBq/kg). 222 Rn distillation in liquid mode
would reduce 222 Rn by another factor of two and the goal would be met.
The purification technique developed in this thesis enables the search fordark matter with a sensitivity of 1.4 × 10−48 cm2 for 50 GeV/c2 WIMPs (theprojected sensitivity) thanks to the high purity and low radon emanation of
the filter. This makes it possible for XENONnT to explore large uninvestigated WIMP parameter space. For comparison, without this technique, thesensitivity would be three times worse than the projection due to a worse
electron lifetime and discrimination power. Moreover, since the liquid xenon
TPC technique is attracting more attention not only for dark matter but also
for other rare event searches, there are future projects of large liquid xenon
TPC such as nEXO and DARWIN. The technique developed in this thesis
seems to be promising for the liquid xenon purification of those experiments.

114

Appendix
A

Purity Monitor

Here details of the purity monitor are summarized although some of theinformation is already described in [59] (in Japanese).

A.1

Structure

Fig. A.1a shows the structure of the purity monitor with some descriptions. Here, more details of each part are described. First, let’s see electrodes
from bottom to top which are important for creating an electric field inside
the purity monitor. The bottommost electrode is a cathode which is ϕ50mm and h = 5 mm stainless steel disk. We have ϕ12 mm gold photocathode,which was made with vacuum deposition, at the center of the cathode. On
the cathode, there is a ring (outer: ϕ50 mm, inner:ϕ38 mm, h: 5 mm) topush the electric field inwards. The next one is a cathode grid (CG). Gridis made by etching from 0.1 mm thickness stainless steel (SUS) plate (Fig.
A.2). It has a hexagonal shape with a line width of 0.1 mm and the distance
between parallel lines is 2 mm. The thin grid is sandwiched with two SUS
rings (outer: ϕ50 mm, inner: ϕ38 mm, h: 5 mm) and attached to the ringby spot welding. There are slits in those rings so that optical fibers can beinserted toward the gold photocathode.
The next electrodes are called field shaping rings (outer: ϕ50 mm, inner:ϕ38mm, h: 10 mm) and there are 16 of them. Then there is an anode grid (AG)which has the same grid geometry as CG. It is also attached to a ring (outer:
ϕ50 mm, inner:ϕ38 mm, h: 5mm) by spot welding but not sandwiched as
CG. There is no slit as well. Finally, there is an anode at the top. The
geometry is the same as the cathode. All of these electrodes are made fromSUS.
To separate electrodes from each other, there are PEEK spacers as shownin Fig. A.1a. Two larger spacers are located around the middle and top of thepurity monitor. Those spacers almost touch with the purity monitor vessel
115

Appendix(a) Purity monitor structure.

(b) Purity monitor vessel.

Figure A.1: Purity monitor structure. (a) Purity monitor with descriptionsof each parts. (b) Purity monitor vessel closed.

116

Appendix

Figure A.2: Purity monitor grid.
wall and prevent it from leaning, especially when it is installed horizontallyas in Fig. 3.12. With those spacers, the distance between electrodes is fixed
to be 17 mm (Cathode-CG), 204 mm (CG-AG), 9 mm (AG-Anode). The
distance between shaping rings is 2mm. To create the electric field inside,
CG, shaping rings, and AG are connected with 17 chip resistors with 300 MΩ(SM5D 300MF) resistance. Thanks to constant voltage drops at resistors,
each electrode has its own voltage with constant intervals.
Kapton cables are attached to the cathode, CG, AG, and anode to apply
voltage. Since charge signals go through cathode and anode cables, coaxial
cables were selected for them. After attaching cables, the purity monitor
is enclosed in the ICF114 vessel (l = 400 mm) shown in Fig. A.1b. It has
feedthroughs for cables (4 SHVs) and optical fiber (not shown in the picture
because it was taken before inserting the fiber).
In real operations, we typically apply a 100 V/cm electric field in themain drift region. The applied voltages to each electrode are summarized inTable A.1. The electric field simulation with finite element method software,
COMSOL, indicates the 100% grid transparency with these configurations.

117

Appendix
Table A.1: Applied voltages to each electrode in 100 V/cm operation
Electrode
CathodeCathode grid
Anode grid
Anode

A.2

Voltage [V]
-50
0
2040
2540

OpticsDrift electrons are emitted from the gold photocathode by UV light fromthe L7685 xenon flash lamp manufactured by Hamamatsu Photonics (see Fig.
A.3). It can generate a pulsed light with a maximum intensity of 1 J/pulse(using an external 2 µF capacitor) and 60 Hz frequency. The width of thepulse is 2.9 µs FWHM when flashed with 1 J/pulse. The light is introduced
in a solarization-resistant optical fiber with a core diameter of 600 µm. The
solarization-resistant fiber withstands the damage from UV light better thanstandard quartz fibers and keeps the transmittance under UV conditions.
The lengths of fibers were 1 m (from the lamp to the outer vacuum vessel)and 70 cm (from the outer to the inner vessel). Optical feedthroughs with thesame core diameter are used to introduce light through vessels. We did notuse solarization-resistant fiber feedthroughs but standard quartz ones because
the length is short compared to the total length of the optical path. In real
operation, the lamp is turned on/oﬀ through a DC 24 V relay controlled bya slow control. In addition, external TTL signals with 10 Hz were supplied
to trigger the flash lamp timing which is synchronized with DAQ (see next
section).

A.3

Electronics and DAQ

Fig. A.4 is a main circuit for the purity monitor. To supply high voltages(HV) to electrodes, namely cathode, cathode grid, anode grid, and anode,
there are filters in between the HV module and the electrodes. The charges
from cathode and anode electrodes are read by AMPTEK A250 chargesensitive pre-amplifiers independently. Before the outputs of the chargesensitive amplifiers goes to FADC (CAEN DT5724), there are buﬀer amplifiers made with LM7171 so that the signals can be read using the digitizers
with 50 Ω input impedance. There are 470 pF coupling capacitors to cut DC
components and pass only pulsed charge signals.
DAQ algorithm is designed as follows:
1. FADC always takes data using a trigger synchronized with the lamp
118

Appendix

Figure A.3: Xenon flash lamp. The black one is the main part of the xenon
flash lamp system, which is composed of an L7685 xenon flash lamp, E6647
trigger socket, and E6611 cooling jacket. We also have a C6096 lamp powersystem and E7289-02 (2 µF) discharging capacitor. DC 24V switching power
supplies power to the C6096. Although it is not shown in this picture, there
is a relay between the DC 24 V switching power supply and AC power line
to control the on/oﬀ of the lamp.
trigger. Every 10 s, it creates a file with waveforms taken in the last
10 s. Since the lamp trigger is 10 Hz, each file contains 100 waveforms.
When the lamp is oﬀ (relay is oﬀ), the file only contains baseline waveforms, but when the lamp is on, it contains signal waveforms.
2. Whenever FADC creates a file, a check program looks into it and judges
whether there are signal waveforms. If it detects a file with signals, it
combines subsequent files until the file contains baseline only.
3. Whenever the check program creates a combined file with signal waveforms, a lifetime-computation program calculates the electron lifetime
from those waveforms after taking the average of them.
Obtained electron lifetime values are put into slow control database.

119Appendix

Figure A.4: Purity monitor circuit. It is mainly composed of HV filters andamplifiers.

B

Signal corrections in TPC analyses

When particles interact with xenon atoms, their deposit energies are converted to photons and free electrons. Unfortunately, observed number ofphotons and electrons (S1s and S2s) are interaction-position dependent due
to the detector response non-uniformity. Here we see those position dependent eﬀects as well as the methods to correct them. Electron lifetime isused to correct z (drift time) dependence of the S2 signal size, but we do
not discuss here because it is already discussed in the main text (see section
3.1.2).

Figure B.5: TPC coordinate system.
120

Appendix
The coordinate system of the XENONnT TPC is shown in Fig. B.5. The
origin (x = y = z = 0) is defined as the center of the gate electrode. The
vertical axis (z) points to the top of the TPC. It means that all z-coordinates
for events in the liquid xenon are negative.

B.1

S1 position dependence correction

0

1.5

20

1.4

40

1.3

60

1.2

80

1.1

100

1.0

120

0.9

140

0.8

Relative Yieldz [cm]

S1 photons are generated anywhere inside the sensitive volume of thedetector. However, since there is a liquid surface, S1s photons generated
near the top of the TPC are more likely to get reflected by the surface andtend to travel longer, which results in smaller S1s. On the other hand, S1s
photons generated near the bottom of the TPC can be detected directly by
the bottom PMT array, which results in larger S1s. Such a geometrical eﬀectof detector response can be calibrated with 83m Kr monoenergetic lines (41.5
keV). Fig. B.6 shows a relative light yield map of √S1s. Although the map
is 3D (x, y and z), it is projected to z − r (r = x2 + y 2 ) space for theconvenience of visualization. This map is used to create corrected S1s (cS1s)
from raw (observed) S1s to compensate for position-dependent light yield.

0

10

20

30 40
r [cm]

50

60

Figure B.6: S1 light yield map obtained from monoenergetic 83m Kr S1s.
Although the real map is 3D, it is projected to 2D for convenience.

121Appendix

B.2

S2 position dependence correction

S2s are generated at the anode, therefore, we only have to consider x andy position dependence, unlike S1s. Again the light yield maps are made byobserving 83m Kr monoenergetic S2s at diﬀerent positions. To disentangle z
and x − y dependence of S2s, electron-lifetime-corrected S2s were used before
making them. Fig. B.7a and Fig. B.7b are such maps made with the top or
bottom PMT arrays only. Diagonal lines correspond to support wires which
are running perpendicular to main anode wires to prevent possible sagging,and there is non-uniformity around these wires. In general, the light yieldtends to be larger at the center and the non-uniformity is larger for theS2 map by top PMT arrays (Fig. B.8). Therefore we often use corrected
S2 bottom (cS2b) for analyses (e.g. XENON1T) which is S2s seen by thebottom PMT array and corrected with the bottom S2 map.

(a) S2 map by top PMTs.

(b) S2 map by bottom PMTs.

Figure B.7: S2 light yield map. (a) S2 light yield map seen by top PMT
array. (b) S2 light yield map seen by bottom PMT array.

122

Appendix

700

S2 topS2 bottom

600

A.U.

500
400
300
200
100
0
0.6

0.8

1.0
1.2
Relative yield

1.4

1.6

Figure B.8: Distribution of S2 yield for top and bottom PMT array. S2 map
made with bottom PMTs is more uniform than top.

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