cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:jg-3f
title: A variational formulation of the Harris functional as correction to approximate Kohn-Sham density functional theory

description: Accurate descriptions of intermolecular interactions are of great importance in simulations of molecular liquids. We present an electronic structure method that combines the accuracy of the Harris functional approach with the computational efficiency of approximately linear-scaling density functional theory (DFT). The proposed method allows for simulations with accuracies close to the Kohn-Sham DFT reference. Embedded in the CP2K program package, the method is designed to enable ab initio molecular dynamics simulations of molecular solutions for system sizes of several thousands of atoms. As example of production applications we applied the method to molecular dynamics simulations in the isobaric-isothermal ensemble of the binary mixtures cyclohexane-methanol and toluene-methanol at different molar fractions of methanol. This record contains all CP2K input files necessary for the MD simulations, as well as 30ps trajectory files, and benchmark data of the energy correction.
DOI: 10.24435/materialscloud:86-bg
title: Testing Koopmans spectral functionals on the analytically-solvable Hooke's atom

description: Koopmans spectral functionals are a class of orbital-density-dependent functionals designed to accurately predict spectroscopic properties. They do so markedly better than their Kohn-Sham density-functional theory counterparts, as demonstrated in earlier works on benchmarks of molecules and bulk systems. This work is a complementary study where — instead of comparing against real, many-electron systems — we test Koopmans spectral functionals on Hooke's atom, a toy two-electron system that has an analytical solution. As these calculations clearly illustrate, Koopmans spectral functionals do an excellent job of describing Hooke's atom. This work also provides broader insight into the features and capabilities of Koopmans spectral functionals more generally.
This repository contains data associated with the article of the same name.
DOI: 10.24435/materialscloud:1v-hh
title: Testing Koopmans spectral functionals on the analytically-solvable Hooke's atom

description: Koopmans spectral functionals are a class of orbital-density-dependent functionals designed to accurately predict spectroscopic properties. They do so markedly better than their Kohn-Sham density-functional theory counterparts, as demonstrated in earlier works on benchmarks of molecules and bulk systems. This work is a complementary study where --- instead of comparing against real, many-electron systems --- we test Koopmans spectral functionals on Hooke's atom, a toy two-electron system that has analytical solutions for particular strengths of its harmonic confining potential. As these calculations clearly illustrate, Koopmans spectral functionals do an excellent job of describing Hooke's atom across a range of confining potential strengths. This work also provides broader insight into the features and capabilities of Koopmans spectral functionals more generally.
DOI: 10.24435/materialscloud:re-4m
title: Testing Koopmans spectral functionals on the analytically-solvable Hooke's atom

description: Koopmans spectral functionals are a class of orbital-density-dependent functionals designed to accurately predict spectroscopic properties. They do so markedly better than their Kohn-Sham density-functional theory counterparts, as demonstrated in earlier works on benchmarks of molecules and bulk systems. This work is a complementary study where --- instead of comparing against real, many-electron systems --- we test Koopmans spectral functionals on Hooke's atom, a toy two-electron system that has analytical solutions for particular strengths of its harmonic confining potential. As these calculations clearly illustrate, Koopmans spectral functionals do an excellent job of describing Hooke's atom across a range of confining potential strengths. This work also provides broader insight into the features and capabilities of Koopmans spectral functionals more generally.
DOI: 10.24435/materialscloud:gm-n0
title: Machine learning guided high-throughput search of non-oxide garnets

description: Garnets, known since the early stages of human civilization, have found important applications in modern technologies including magnetorestriction, spintronics, lithium batteries, etc. The overwhelming majority of experimentally known garnets are oxides, while explorations (experimental or theoretical) for the rest of the chemical space have been limited in scope.  A key issue is that the garnet structure has a large primitive unit cell, requiring an enormous amount of computational resources. To perform a comprehensive search of the complete chemical space for new garnets, we combine recent progress in graph neural networks with high-throughput calculations. We apply the machine learning model to identify the potential (meta-)stable garnet systems before systematic density-functional calculations to validate the predictions. In this way, we discover more than 600 ternary garnets with distances to the convex hull below 100~meV/atom with a variety of physical and chemical properties. This includes sulfide, nitride and halide garnets. This record includes the results of 15742 vasp calculations of the ternary garnets investigated. All calculations were performed using the PBE functional.
DOI: 10.24435/materialscloud:wd-9p
title: Machine learning guided high-throughput search of non-oxide garnets

description: Garnets, known since the early stages of human civilization, have found important applications in modern technologies including magnetorestriction, spintronics, lithium batteries, etc. The overwhelming majority of experimentally known garnets are oxides, while explorations (experimental or theoretical) for the rest of the chemical space have been limited in scope.  A key issue is that the garnet structure has a large primitive unit cell, requiring an enormous amount of computational resources. To perform a comprehensive search of the complete chemical space for new garnets, we combine recent progress in graph neural networks with high-throughput calculations. We apply the machine learning model to identify the potential (meta-)stable garnet systems before systematic density-functional calculations to validate the predictions. In this way, we discover more than 600 ternary garnets with distances to the convex hull below 100~meV/atom with a variety of physical and chemical properties. This includes sulfide, nitride and halide garnets. This record includes the results of 15742 vasp calculations of the ternary garnets investigated. All calculations were performed using the PBE functional.
DOI: 10.24435/materialscloud:fy-86
title: Polaron hopping through piecewise-linear functionals

description: We use piecewise-linear functionals to study the polaron energy landscape and hopping rates in 𝜷-Ga₂O₃, which we adopt as an example of an anisotropic material hosting multiple polaronic states. We illustrate various functionals for polaron localization, including a hybrid functional and two types of semilocal functionals, and discuss how to ensure the piecewise linearity condition. Then, we determine the formation energies of stable polarons, and show that single-site and multi-site polaronic states can be found in close energetic competition. We calculate the hyperfine and superhyperfine parameters associated with each polaron, and discuss the comparison with experiment. Next, we perform nudged-elastic-band calculations to determine energy landscapes and hole transfer rates of all first-nearest-neighbor polaron hoppings. We show that when the piecewise linearity condition is ensured polaron properties are robust upon variation of the functional adopted, including formation energies, energy barriers, and charge transfer rates. This supports the use of semilocal functionals for calculating polaron transport properties.
DOI: 10.24435/materialscloud:64-3c
title: Tunable topological Dirac surface states and van Hove singularities in kagome metal GdV6Sn6

description: Transition-metal-based kagome materials at van Hove filling are a rich frontier for the investigation of novel topological electronic states and correlated phenomena. To date, in the idealized two-dimensional kagome lattice, topologically Dirac surface states (TDSSs) have not been unambiguously observed, and the manipulation of TDSSs and van Hove singularities (VHSs) remains largely unexplored. Here, we reveal TDSSs originating from a Z2 bulk topology and identify multiple VHSs near the Fermi level (EF) in magnetic kagome material GdV6Sn6. Using in situ surface potassium deposition, we successfully realize manipulation of the TDSSs and VHSs. The Dirac point of the TDSSs can be tuned from above to below EF, which reverses the chirality of the spin texture at the Fermi surface. These results establish GdV6Sn6 as a fascinating platform for studying the nontrivial topology, magnetism, and correlation effects native to kagome lattices. They also suggest potential application of spintronic devices based on kagome materials.
DOI: 10.24435/materialscloud:zj-0b
title: Polaron hopping through piecewise-linear functionals

description: We use piecewise-linear functionals to study the polaron energy landscape and hopping rates in 𝜷-Ga₂O₃, which we adopt as an example of an anisotropic material hosting multiple polaronic states. We illustrate various functionals for polaron localization, including a hybrid functional and two types of semilocal functionals, and discuss how to ensure the piecewise linearity condition. Then, we determine the formation energies of stable polarons, and show that single-site and multi-site polaronic states can be found in close energetic competition. We calculate the hyperfine and superhyperfine parameters associated with each polaron, and discuss the comparison with experiment. Next, we perform nudged-elastic-band calculations to determine energy landscapes and hole transfer rates of all first-nearest-neighbor polaron hoppings. We show that when the piecewise linearity condition is ensured polaron properties are robust upon variation of the functional adopted, including formation energies, energy barriers, and charge transfer rates. This supports the use of semilocal functionals for calculating polaron transport properties.
DOI: 10.24435/materialscloud:ca-c2
title: Tunable topological Dirac surface states and van Hove singularities in kagome metal GdV6Sn6

description: Transition-metal-based kagome materials at van Hove filling are a rich frontier for the investigation of novel topological electronic states and correlated phenomena. To date, in the idealized two-dimensional kagome lattice, topologically Dirac surface states (TDSSs) have not been unambiguously observed, and the manipulation of TDSSs and van Hove singularities (VHSs) remains largely unexplored. Here, we reveal TDSSs originating from a Z2 bulk topology and identify multiple VHSs near the Fermi level (EF) in magnetic kagome material GdV6Sn6. Using in situ surface potassium deposition, we successfully realize manipulation of the TDSSs and VHSs. The Dirac point of the TDSSs can be tuned from above to below EF, which reverses the chirality of the spin texture at the Fermi surface. These results establish GdV6Sn6 as a fascinating platform for studying the nontrivial topology, magnetism, and correlation effects native to kagome lattices. They also suggest potential application of spintronic devices based on kagome materials.
DOI: 10.24435/materialscloud:et-g4
title: Dataset of proximity induced superconductivity in a topological insulator

description: Interfacing a topological insulator (TI) with an s-wave superconductor (SC) is a promising material platform that offers the possibility to realize a topological superconductor through which Majorana-based topologically protected qubits can be engineered. In our computational study of the prototypical SC/TI interface between Nb and Bi₂Te₃, we identify the benefits and possible bottlenecks of this potential Majorana material platform. Bringing Nb in contact with the TI film induces charge doping from the SC to the TI, which shifts the Fermi level into the TI conduction band. For thick TI films, this results in band bending leading to the population of trivial TI quantum-well states at the interface. In the superconducting state, we uncover that the topological surface state experiences a sizable superconducting gap-opening at the SC/TI interface, which is furthermore robust against fluctuations of the Fermi energy. We also show that the trivial interface state is only marginally proximitized, potentially obstructing the realization of Majorana-based qubits in this material platform.
This dataset contains the data for the DFT-based calculations for interfaces between the s-wave superconductor Nb and the topological insulator Bi₂Te₃ which is discussed in the publication referenced below.
DOI: 10.24435/materialscloud:14-ah
title: Dataset of proximity induced superconductivity in a topological insulator

description: Interfacing a topological insulator (TI) with an s-wave superconductor (SC) is a promising material platform that offers the possibility to realize a topological superconductor through which Majorana-based topologically protected qubits can be engineered. In our computational study of the prototypical SC/TI interface between Nb and Bi₂Te₃, we identify the benefits and possible bottlenecks of this potential Majorana material platform. Bringing Nb in contact with the TI film induces charge doping from the SC to the TI, which shifts the Fermi level into the TI conduction band. For thick TI films, this results in band bending leading to the population of trivial TI quantum-well states at the interface. In the superconducting state, we uncover that the topological surface state experiences a sizable superconducting gap-opening at the SC/TI interface, which is furthermore robust against fluctuations of the Fermi energy. We also show that the trivial interface state is only marginally proximitized, potentially obstructing the realization of Majorana-based qubits in this material platform.
This dataset contains the data for the DFT-based calculations for interfaces between the s-wave superconductor Nb and the topological insulator Bi₂Te₃ which is discussed in the publication referenced below.
DOI: 10.24435/materialscloud:a9-4n
title: A machine learning model of chemical shifts for chemically and structurally diverse molecular solids

description: Nuclear magnetic resonance (NMR) chemical shifts are a direct probe of local atomic environments and can be used to determine the structure of solid materials. However, the substantial computational cost required to predict accurate chemical shifts is a key bottleneck for NMR crystallography. We recently introduced ShiftML, a machine-learning model of chemical shifts in molecular solids, trained on minimum-energy geometries of materials composed of C, H, N, O, and S that provides rapid chemical shift predictions with density functional theory (DFT) accuracy. Here, we extend the capabilities of ShiftML to predict chemical shifts for both finite temperature structures and more chemically diverse compounds, while retaining the same speed and accuracy. For a benchmark set of 13 molecular solids, we find a root-mean-squared error of 0.47 ppm with respect to experiment for 1H shift predictions (compared to 0.35 ppm for explicit DFT calculations), while reducing the computational cost by over four orders of magnitude.
DOI: 10.24435/materialscloud:sm-yz
title: A machine learning model of chemical shifts for chemically and structurally diverse molecular solids

description: Nuclear magnetic resonance (NMR) chemical shifts are a direct probe of local atomic environments and can be used to determine the structure of solid materials. However, the substantial computational cost required to predict accurate chemical shifts is a key bottleneck for NMR crystallography. We recently introduced ShiftML, a machine-learning model of chemical shifts in molecular solids, trained on minimum-energy geometries of materials composed of C, H, N, O, and S that provides rapid chemical shift predictions with density functional theory (DFT) accuracy. Here, we extend the capabilities of ShiftML to predict chemical shifts for both finite temperature structures and more chemically diverse compounds, while retaining the same speed and accuracy. For a benchmark set of 13 molecular solids, we find a root-mean-squared error of 0.47 ppm with respect to experiment for 1H shift predictions (compared to 0.35 ppm for explicit DFT calculations), while reducing the computational cost by over four orders of magnitude.
DOI: 10.24435/materialscloud:tb-mf
title: Single in-situ interface characterization composed of niobium and a selectively grown topological insulator nanoribbon

description: With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features.

This dataset contains the DFT and experimental raw data discussed in the associated publication.
DOI: 10.24435/materialscloud:gt-0r
title: Single in-situ interface characterization composed of niobium and a selectively grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

description: With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features.

This dataset contains the DFT and experimental raw data discussed in the associated publication.
DOI: 10.24435/materialscloud:p4-0v
title: Characterization of single in situ prepared interfaces composed of niobium and a selectively-grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

description: With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features.

This dataset contains the DFT and experimental raw data discussed in the associated publication.
DOI: 10.24435/materialscloud:aj-bh
title: Characterization of single in situ prepared interfaces composed of niobium and a selectively-grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

description: With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features.

This dataset contains the DFT and experimental raw data discussed in the associated publication.
DOI: 10.24435/materialscloud:xw-g5
title: Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

description: The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of Density Functional Theory (DFT). However, running large simulation cells with DFT is computationally demanding, while simulations of small cells are often plagued with non-physical effects that are a consequence of the system's finite size. Therefore, one is often forced to use empirical models that describe the physics of the material in terms of effective interaction terms, that are fitted using the results from DFT, to perform simulations that do not suffer from finite size effects. In this study we use a machine-learning (ML) potential trained on DFT, in combination with accelerated sampling techniques, to converge the thermodynamic properties of Barium Titanate (BTO) with first-principles accuracy and a full atomistic description. Our results indicate that the predicted Curie temperature depends strongly on the choice of DFT functional and system size, due to the presence of emergent long-range directional correlations in the local dipole fluctuations. Our findings demonstrate how the combination of ML models and traditional bottom-up modeling allow one to investigate emergent phenomena with the accuracy of first-principles calculations and the large size and time scales afforded by empirical models.