cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:27-8f
title: Porous functionalized polymers enable generating and transporting hyperpolarized mixtures of metabolites

description: Hyperpolarization by dissolution dynamic nuclear polarization (dDNP) has enabled promising applications in spectroscopy and imaging, but remains poorly widespread due to experimental complexity. Broad democratization of dDNP would require remote preparation and distribution of hyperpolarized samples from dedicated facilities. We describe here new hyperpolarizing polymers (HYPOPs) that can generate radical- and contaminant-free hyperpolarized samples within minutes with lifetimes exceeding hours in the solid state. HYPOPs feature tunable macroporous porosity, with porous volumes up to 80% and concentration of nitroxide radicals grafted in the bulk matrix up to 285 μmol g-1. Analytes can be efficiently impregnated as aqueous/alcoholic solutions and hyperpolarized up to P(13C) =25% within 8 min, through the combination of 1H spin diffusion and 1H →13C cross polarization. Solutions of 13C-analytes of biological interest hyperpolarized in HYPOPs display a very long solid-state 13C relaxation times of 5.7 h at 3.8 K, thus prefiguring transportation over long distances.
DOI: 10.24435/materialscloud:f2-b1
title: Reinvestigating the surface and bulk electronic properties of Cd3As2

description: This record contains the experimental results of our reinvestigation of the bulk and surface electronic properties of Cd3As2, a well-known material proposed to realize the 3D Dirac semimetal phase. By using polarization-based matrix element effects in photoemission, we reveal multiple bands crossing the Fermi level, characterized by different orbital character. Those states exhibit also largely different effective masses, and by combining alkali metal deposition and photon energy dependent ARPES, we report that the linearly dispersing band, which was previously interpreted as a bulk Dirac particle, is indeed a 2D surface Dirac state.
DOI: 10.24435/materialscloud:bd-t3
title: Reinvestigating the surface and bulk electronic properties of Cd3As2

description: This record contains the experimental results of our reinvestigation of the bulk and surface electronic properties of Cd3As2, a well-known material proposed to realize the 3D Dirac semimetal phase. By using polarization-based matrix element effects in photoemission, we reveal multiple bands crossing the Fermi level, characterized by different orbital character. Those states exhibit also largely different effective masses, and by combining alkali metal deposition and photon energy dependent ARPES, we report that the linearly dispersing band, which was previously interpreted as a bulk Dirac particle, is indeed a 2D surface Dirac state.
DOI: 10.24435/materialscloud:r8-tj
title: First principles correction scheme for linear-response time-dependent density functional theory calculations of core electronic states

description: Linear-response time-dependent density functional theory (LR-TDDFT) for core level spectroscopy using standard local functionals suffers from self-interaction error and a lack of orbital relaxation upon creation of the core hole. As a result, LR-TDDFT calculated X-ray absorption near edge structure (XANES) spectra need to be shifted along the energy axis to match experimental data. We propose a correction scheme based on many body perturbation theory to calculate the shift from first principles. The ionization potential of the core donor state is first computed and then substituted for the corresponding Kohn--Sham orbital energy, thus emulating Koopmans' condition. Both self-interaction error and orbital relaxation are taken into account. The method exploits the localized nature of core states for efficiency and integrates seamlessly in our previous implementation of core level LR-TDDFT, yielding corrected spectra in a single calculation. We benchmark the correction scheme on molecules at the K- and L-edges as well as for core binding energies and report accuracies comparable to higher order methods. We also demonstrate applicability in large and extended systems and discuss efficient approximations.
DOI: 10.24435/materialscloud:5v-j5
title: First principles correction scheme for linear-response time-dependent density functional theory calculations of core electronic states

description: Linear-response time-dependent density functional theory (LR-TDDFT) for core level spectroscopy using standard local functionals suffers from self-interaction error and a lack of orbital relaxation upon creation of the core hole. As a result, LR-TDDFT calculated X-ray absorption near edge structure (XANES) spectra need to be shifted along the energy axis to match experimental data. We propose a correction scheme based on many body perturbation theory to calculate the shift from first principles. The ionization potential of the core donor state is first computed and then substituted for the corresponding Kohn--Sham orbital energy, thus emulating Koopmans' condition. Both self-interaction error and orbital relaxation are taken into account. The method exploits the localized nature of core states for efficiency and integrates seamlessly in our previous implementation of core level LR-TDDFT, yielding corrected spectra in a single calculation. We benchmark the correction scheme on molecules at the K- and L-edges as well as for core binding energies and report accuracies comparable to higher order methods. We also demonstrate applicability in large and extended systems and discuss efficient approximations.
DOI: 10.24435/materialscloud:v8-rn
title: On‐surface synthesis and characterization of triply fused porphyrin–graphene nanoribbon hybrids

description: On‐surface synthesis offers a versatile approach to prepare novel carbon‐based nanostructures that cannot be obtained by conventional solution chemistry. Graphene nanoribbons (GNRs) have potential for a variety of applications. A key issue for their application in molecular electronics is in the fine‐tuning of their electronic properties through structural modifications, such as heteroatom doping or the incorporation of non‐benzenoid rings.
In this record we provide data to support our recent publication that reports the covalent fusion of grapnene nanoribbons (GNRs) and porphyrins (Pors). We demonstrated selective on‐surface synthesis of a Por–GNR hybrid, which consists of two Pors connected by a short GNR segment. The atomically precise structure of the Por–GNR hybrid has been characterized by bond‐resolved scanning tunneling microscopy and noncontact atomic force microscopy. The electronic properties have been investigated by scanning tunneling spectroscopy, in combination with DFT calculations, which reveals a low electronic gap of 0.4 eV
DOI: 10.24435/materialscloud:pt-ew
title: On‐surface synthesis and characterization of triply fused porphyrin–graphene nanoribbon hybrids

description: On‐surface synthesis offers a versatile approach to prepare novel carbon‐based nanostructures that cannot be obtained by conventional solution chemistry. Graphene nanoribbons (GNRs) have potential for a variety of applications. A key issue for their application in molecular electronics is in the fine‐tuning of their electronic properties through structural modifications, such as heteroatom doping or the incorporation of non‐benzenoid rings.
In this record we provide data to support our recent publication that reports the covalent fusion of grapnene nanoribbons (GNRs) and porphyrins (Pors). We demonstrated selective on‐surface synthesis of a Por–GNR hybrid, which consists of two Pors connected by a short GNR segment. The atomically precise structure of the Por–GNR hybrid has been characterized by bond‐resolved scanning tunneling microscopy and noncontact atomic force microscopy. The electronic properties have been investigated by scanning tunneling spectroscopy, in combination with DFT calculations, which reveals a low electronic gap of 0.4 eV
DOI: 10.24435/materialscloud:eh-vd
title: Towards predictive many-body calculations of phonon-limited carrier mobilities in semiconductors

description: We probe the accuracy limit of ab initio calculations of carrier mobilities in semiconductors, within the framework of the Boltzmann transport equation. By focusing on the paradigmatic case of silicon, we show
that fully predictive calculations of electron and hole mobilities require many-body quasiparticle corrections to band structures and electron-phonon matrix elements, the inclusion of spin-orbit coupling, and an extremely fine sampling of inelastic scattering processes in momentum space. By considering all these factors we obtain excellent agreement with experiment, and we identify the band effective masses as the most critical parameters to achieve predictive accuracy. Our findings set a blueprint for future calculations of carrier mobilities, and pave the way to engineering transport properties in semiconductors by design.
DOI: 10.24435/materialscloud:yk-6n
title: Towards predictive many-body calculations of phonon-limited carrier mobilities in semiconductors

description: We probe the accuracy limit of ab initio calculations of carrier mobilities in semiconductors, within the framework of the Boltzmann transport equation. By focusing on the paradigmatic case of silicon, we show
that fully predictive calculations of electron and hole mobilities require many-body quasiparticle corrections to band structures and electron-phonon matrix elements, the inclusion of spin-orbit coupling, and an extremely fine sampling of inelastic scattering processes in momentum space. By considering all these factors we obtain excellent agreement with experiment, and we identify the band effective masses as the most critical parameters to achieve predictive accuracy. Our findings set a blueprint for future calculations of carrier mobilities, and pave the way to engineering transport properties in semiconductors by design.
DOI: 10.24435/materialscloud:tf-kf
title: EPW: Electron-phonon coupling, transport and superconducting properties using maximally localized Wannier functions

description: The EPW (Electron-Phonon coupling using Wannier functions) software is a Fortran90 code that uses density-functional perturbation theory and maximally localized Wannier functions for computing
electron-phonon couplings and related properties in solids accurately and efficiently. The EPW v4 program can be used to compute electron and phonon self-energies, linewidths, electron-phonon scattering
rates, electron-phonon coupling strengths, transport spectral functions, electronic velocities, resistivity, anisotropic superconducting gaps and spectral functions within the Migdal-Eliashberg theory. The
code now supports spin-orbit coupling, time-reversal symmetry in non-centrosymmetric crystals, polar materials, and k and q-point parallelization. Considerable effort was dedicated to optimization and
parallelization, achieving almost a ten times speedup with respect to previous releases. A computer test farm was implemented to ensure stability and portability of the code on the most popular compilers
and architectures. Since April 2016, version 4 of the EPW code is fully integrated in and distributed with the Quantum ESPRESSO package, and can be downloaded through at https://gitlab.com/QEF/q-e
DOI: 10.24435/materialscloud:vb-yp
title: EPW: Electron-phonon coupling, transport and superconducting properties using maximally localized Wannier functions

description: The EPW (Electron-Phonon coupling using Wannier functions) software is a Fortran90 code that uses density-functional perturbation theory and maximally localized Wannier functions for computing
electron-phonon couplings and related properties in solids accurately and efficiently. The EPW v4 program can be used to compute electron and phonon self-energies, linewidths, electron-phonon scattering
rates, electron-phonon coupling strengths, transport spectral functions, electronic velocities, resistivity, anisotropic superconducting gaps and spectral functions within the Migdal-Eliashberg theory. The
code now supports spin-orbit coupling, time-reversal symmetry in non-centrosymmetric crystals, polar materials, and k and q-point parallelization. Considerable effort was dedicated to optimization and
parallelization, achieving almost a ten times speedup with respect to previous releases. A computer test farm was implemented to ensure stability and portability of the code on the most popular compilers
and architectures. Since April 2016, version 4 of the EPW code is fully integrated in and distributed with the Quantum ESPRESSO package, and can be downloaded through at https://gitlab.com/QEF/q-e
DOI: 10.24435/materialscloud:z9-24
title: Machine learning for metallurgy: a neural network potential for Al-Cu-Mg

description: High-strength metal alloys achieve their performance via careful control of precipitates and solutes. The nucleation, growth, and kinetics of precipitation, and the resulting mechanical properties, are inherently atomic-scale phenomena, particularly during early-stage nucleation and growth. Atomistic modeling using interatomic potentials is a desirable tool for understanding the detailed phenomena involved in precipitation and strengthening, which requires length and time scales far larger than those accessible by first-principles methods. Current interatomic potentials for alloys are not, however, sufficiently accurate for such studies. Here, a family of neural-network potentials (NNPs) for the Al-Cu-Mg system is presented as the first example of a machine-learning potential that can achieve near-first-principles accuracy for many different metallurgically-important aspects of this alloy. High fidelity predictions of intermetallic compounds, elastic constants, dilute solid-solution energetics, precipitate/matrix interfaces, generalized stacking fault energies, and surfaces for slip in matrix and precipitates, antisite defect energies, and other quantities, are shown.  The NNP shows some significant transferability to defects and properties outside the structures used to develop the NNP but also shows some errors, highlighting that the use of any interatomic potential requires careful validation in application to specific metallurgical problems of interest.
DOI: 10.24435/materialscloud:ea-y9
title: Machine learning for metallurgy: neural network potentials for Al-Cu-Mg and Al-Cu-Mg-Zn

description: Most metallurgical properties, e.g., dislocation propagation, precipitate formation, can only be fully understood atomistically but most phenomena and quantities of interest cannot be measured experimentally.  Accurate simulation methods are essential but first-principles density functional theory (DFT) is prohibitively expensive while empirical interatomic potentials are rarely sufficiently accurate for alloys.  Machine learning (ML) is emerging as an approach to create computationally-efficient atomistic potentials achieving near-DFT accuracy.  Building on recent work on binary Al-Cu and ternary Al-Mg-Si, here a family of neural network potentials (NNPs) for Al alloys of Al-Cu-Mg and Al-Cu-Mg-Zn is developed and assessed using the Behler-Parinello formulation.  Training of the potentials uses a robust set of metallurgically-relevant structures including intermetallic phases, stacking faults, solute/solute and solute/stacking fault interactions, solute clusters, and matrix/precipitate interfaces.  The accuracy of these NNPs is then demonstrated across a comprehensive set of properties derived from the training set structures and, moreover, many important structures not represented in the training set such as the generalized stacking fault energy (GSFE) surface of the critical S-phase precipitate in Al-Mg-Cu, and antisite and vacancy formation energies for Al-Cu-Mg intermetallics.  The broader Al-Cu-Mg-Zn NNPs also have high accuracy for subtle properties such as Cu substitutional energies in the $\eta'$ and T phases and formation energies of small Al-Zn-Mg clusters.  Together with earlier results, this work shows how increasingly complex multicomponent alloy potentials can be systematically developed by expanding a training database, leading to a comprehensive set of potentials for a broad alloy family, demonstrated here for the technological Al-2xxx, Al-5xxx, and Al-7xxx Al alloys.
DOI: 10.24435/materialscloud:y0-j5
title: Machine learning for metallurgy: neural network potentials for Al-Cu-Mg and Al-Cu-Mg-Zn

description: Most metallurgical properties, e.g., dislocation propagation, precipitate formation, can only be fully understood atomistically but most phenomena and quantities of interest cannot be measured experimentally.  Accurate simulation methods are essential but first-principles density functional theory (DFT) is prohibitively expensive while empirical interatomic potentials are rarely sufficiently accurate for alloys.  Machine learning (ML) is emerging as an approach to create computationally-efficient atomistic potentials achieving near-DFT accuracy.  Building on recent work on binary Al-Cu and ternary Al-Mg-Si, here a family of neural network potentials (NNPs) for Al alloys of Al-Cu-Mg and Al-Cu-Mg-Zn is developed and assessed using the Behler-Parinello formulation.  Training of the potentials uses a robust set of metallurgically-relevant structures including intermetallic phases, stacking faults, solute/solute and solute/stacking fault interactions, solute clusters, and matrix/precipitate interfaces.  The accuracy of these NNPs is then demonstrated across a comprehensive set of properties derived from the training set structures and, moreover, many important structures not represented in the training set such as the generalized stacking fault energy (GSFE) surface of the critical S-phase precipitate in Al-Mg-Cu, and antisite and vacancy formation energies for Al-Cu-Mg intermetallics.  The broader Al-Cu-Mg-Zn NNPs also have high accuracy for subtle properties such as Cu substitutional energies in the $\eta'$ and T phases and formation energies of small Al-Zn-Mg clusters.  Together with earlier results, this work shows how increasingly complex multicomponent alloy potentials can be systematically developed by expanding a training database, leading to a comprehensive set of potentials for a broad alloy family, demonstrated here for the technological Al-2xxx, Al-5xxx, and Al-7xxx Al alloys.
DOI: 10.24435/materialscloud:3r-86
title: Emergence of nontrivial low-energy Dirac fermions in antiferromagnetic EuCd2As2

description: When magnetism meets topology, colorful novel states can be created in materials. The realization of magnetic topological Dirac materials remains a major issue in topological physics studies. In this work, it is ascertained that the topologically nontrivial ground state of EuCd2As2 is a good candidate for different types of magnetic topological state: magnetic topological Dirac semimetal, axion insulator, antiferromagnetic TCI, and higher order topological insulator. This documents include all the raw data in the reference Advanced Materials 32, 1907565 (2020). This files contains all the raw data that published in the related paper. Fig.1.zip includes dat format transport measurement results which can be open by Origin. Fig.2.zip contains ibw format ARPES spectra which can be opened by IGOR. Fig.3.zip contains figures of the calculated FS, band structure. The dat format files can be open by IGOR. Fig.4.zip contains both ARPES spectra and STS data. sxm format file can be opened by SXM software which is commonly used for STM/STS data. The h5 format file can be opened by IGOR. H5 format is also commonly used for high dimensional data in ARPES experiments. Fig.5 is mainly the calculated band structure of the related fig.5. The itx format can be opened by IGOR. All the ibw format files are duplicated in the txt file with same name. The SXM file is also duplicated in txt file with same name.
DOI: 10.24435/materialscloud:f0-x6
title: Emergence of nontrivial low-energy Dirac fermions in antiferromagnetic EuCd2As2

description: When magnetism meets topology, colorful novel states can be created in materials. The realization of magnetic topological Dirac materials remains a major issue in topological physics studies. In this work, it is ascertained that the topologically nontrivial ground state of EuCd2As2 is a good candidate for different types of magnetic topological state: magnetic topological Dirac semimetal, axion insulator, antiferromagnetic TCI, and higher order topological insulator. This documents include all the raw data in the reference Advanced Materials 32, 1907565 (2020). This files contains all the raw data that published in the related paper. Fig.1.zip includes dat format transport measurement results which can be open by Origin. Fig.2.zip contains ibw format ARPES spectra which can be opened by IGOR. Fig.3.zip contains figures of the calculated FS, band structure. The dat format files can be open by IGOR. Fig.4.zip contains both ARPES spectra and STS data. sxm format file can be opened by SXM software which is commonly used for STM/STS data. The h5 format file can be opened by IGOR. H5 format is also commonly used for high dimensional data in ARPES experiments. Fig.5 is mainly the calculated band structure of the related fig.5. The itx format can be opened by IGOR. All the ibw format files are duplicated in the txt file with same name. The SXM file is also duplicated in txt file with same name.
DOI: 10.24435/materialscloud:gb-wz
title: Massive Dirac fermion behavior in a low bandgap graphene nanoribbon near a topological phase boundary

description: Graphene nanoribbons (GNRs) have attracted much interest due to their largely modifiable electronic properties. Manifestation of these properties requires atomically precise GNRs which can be achieved through a bottom–up synthesis approach. This has recently been applied to the synthesis of width‐modulated GNRs hosting topological electronic quantum phases, with valence electronic properties that are well captured by the Su–Schrieffer–Heeger (SSH) model describing a 1D chain of interacting dimers. In this record we provide data to support our recent publication where we demonstrate that ultralow bandgap GNRs with charge carriers behaving as massive Dirac fermions can be realized when their valence electrons represent an SSH chain close to the topological phase boundary, i.e., when the intra‐ and interdimer coupling become approximately equal. Such a system has been achieved via on‐surface synthesis based on readily available pyrene‐based precursors and the resulting GNRs are characterized by scanning probe methods. The pyrene‐based GNRs (pGNRs) can be processed under ambient conditions and incorporated as the active material in a field effect transistor. A quasi‐metallic transport behavior is observed at room temperature, whereas at low temperature, the pGNRs behave as quantum dots showing single‐electron tunneling and Coulomb blockade. This study may enable the realization of devices based on carbon nanomaterials with exotic quantum properties.