Kevin F. Garrity
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View article: Spin-Orbital-Lattice Coupling and the Phonon Zeeman Effect in the Dirac Honeycomb Magnet CoTiO$_3$
Spin-Orbital-Lattice Coupling and the Phonon Zeeman Effect in the Dirac Honeycomb Magnet CoTiO$_3$ Open
The entanglement of electronic spin and orbital degrees of freedom is often the precursor to emergent behaviors in condensed matter systems. With considerable spin-orbit coupling strength, the cobalt atom on a honeycomb lattice offers a pl…
View article: JARVIS-Leaderboard: a large scale benchmark of materials design methods
JARVIS-Leaderboard: a large scale benchmark of materials design methods Open
View article: InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning
InterMat: Accelerating Band Offset Prediction in Semiconductor Interfaces with DFT and Deep Learning Open
We introduce a computational framework (InterMat) to predict band offsets of semiconductor interfaces using density functional theory (DFT) and graph neural networks (GNN). As a first step, we benchmark OptB88vdW generalized gradient appro…
View article: InterMat: accelerating band offset prediction in semiconductor interfaces with DFT and deep learning
InterMat: accelerating band offset prediction in semiconductor interfaces with DFT and deep learning Open
We introduce a computational framework (InterMat) to predict band offsets of semiconductor interfaces using density functional theory (DFT) and graph neural networks (GNN).
View article: Recent progress in the JARVIS infrastructure for next-generation data-driven materials design
Recent progress in the JARVIS infrastructure for next-generation data-driven materials design Open
The joint automated repository for various integrated simulations (JARVIS) infrastructure at the National Institute of Standards and Technology is a large-scale collection of curated datasets and tools with more than 80 000 materials and m…
View article: JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods
JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods Open
Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmar…
View article: Recent progress in the JARVIS infrastructure for next-generation data-driven materials design
Recent progress in the JARVIS infrastructure for next-generation data-driven materials design Open
The Joint Automated Repository for Various Integrated Simulations (JARVIS) infrastructure at the National Institute of Standards and Technology (NIST) is a large-scale collection of curated datasets and tools with more than 80000 materials…
View article: Fast and accurate prediction of material properties with three-body tight-binding model for the periodic table
Fast and accurate prediction of material properties with three-body tight-binding model for the periodic table Open
Parametrized tight-binding models fit to first-principles calculations can provide an efficient and accurate quantum mechanical method for predicting properties of molecules and solids. However, well-tested parameter sets are generally onl…
View article: Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning
Efficient computational design of two-dimensional van der Waals heterostructures: Band alignment, lattice mismatch, and machine learning Open
Here, we develop a computational database, website applications (web-apps), and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D) heterostructures. Using density functional theory (DFT) based latti…
View article: High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors
High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors Open
High-throughput density functional theory (DFT) calculations allow for a systematic search for conventional superconductors. With the recent interest in two-dimensional (2D) superconductors, we used a high-throughput workflow to screen ove…
View article: Ring-Exchange Interaction Effects on Magnons in Dirac Magnet CoTiO$_3$
Ring-Exchange Interaction Effects on Magnons in Dirac Magnet CoTiO$_3$ Open
The magnetic interactions that determine magnetic order and magnon energies typically involve only two spins. While rare, multi-spin interactions can also appear in quantum magnets and be the driving force in the ground state selection and…
View article: Designing high-TC superconductors with BCS-inspired screening, density functional theory, and deep-learning
Designing high-TC superconductors with BCS-inspired screening, density functional theory, and deep-learning Open
We develop a multi-step workflow for the discovery of conventional superconductors, starting with a Bardeen–Cooper–Schrieffer inspired pre-screening of 1736 materials with high Debye temperature and electronic density of states. Next, we p…
View article: High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors
High-Throughput DFT-Based Discovery of Next Generation Two-Dimensional (2D) Superconductors Open
High-throughput density functional theory (DFT) calculations allow for a systematic search for conventional superconductors. With the recent interest in two-dimensional (2D) superconductors, we used a high-throughput workflow to screen ove…
View article: On the Role of Defects in the Electronic Structure of MnBi$_{2-x}$Sb$_x$Te$_4$
On the Role of Defects in the Electronic Structure of MnBi$_{2-x}$Sb$_x$Te$_4$ Open
Elemental substitution is a proven method of Fermi level tuning in topological insulators, which is needed for device applications. Through static and time resolved photoemission, we show that in MnBi$_2$Te$_4$, elemental substitution of B…
View article: Designing High-Tc Superconductors with BCS-inspired Screening, Density Functional Theory and Deep-learning
Designing High-Tc Superconductors with BCS-inspired Screening, Density Functional Theory and Deep-learning Open
We develop a multi-step workflow for the discovery of conventional superconductors, starting with a Bardeen Cooper Schrieffer inspired pre-screening of 1736 materials with high Debye temperature and electronic density of states. Next, we p…
View article: Topological Phases of Mn$A_{2}$$X_{4}$ (A=Bi, Sb; X = Se, Te) under Magnetic Field
Topological Phases of Mn$A_{2}$$X_{4}$ (A=Bi, Sb; X = Se, Te) under Magnetic Field Open
The concept of electronic topology and the associated topological protection brings excellent opportunities for developing next-generation devices. Ideally, magnetic topological materials (MTM) should have their Dirac/Weyl points and/or as…
View article: Benchmark data comparison DFT vs TB3
Benchmark data comparison DFT vs TB3 Open
detailed data in support of https://github.com/usnistgov/ThreeBodyTB.jl/ https://arxiv.org/abs/2112.11585 Contains comparison of DFT and tight binding for elastic and band structure data, as well at atomization energies.
View article: defect, surface, and bulk POSCARs
defect, surface, and bulk POSCARs Open
POSCAR of defect crystal structures
View article: Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table
Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table Open
Parameterized tight-binding models fit to first principles calculations can provide an efficient and accurate quantum mechanical method for predicting properties of molecules and solids. However, well-tested parameter sets are generally on…
View article: Magnon-phonon hybridization in 2D antiferromagnet MnPSe <sub>3</sub>
Magnon-phonon hybridization in 2D antiferromagnet MnPSe <sub>3</sub> Open
Strong hybridization of two-magnon scattering with phonons is observed in 2D antiferromagnet MnPSe 3 .
View article: High-throughput search for magnetic topological materials using spin-orbit spillage, machine learning, and experiments
High-throughput search for magnetic topological materials using spin-orbit spillage, machine learning, and experiments Open
Magnetic topological insulators and semi-metals have a variety of properties that make them attractive for applications including spintronics and quantum computation. Here, we use systematic high-throughput density functional theory calcul…
View article: Database of Wannier tight-binding Hamiltonians using high-throughput density functional theory
Database of Wannier tight-binding Hamiltonians using high-throughput density functional theory Open
View article: Computational scanning tunneling microscope image database
Computational scanning tunneling microscope image database Open
We introduce the systematic database of scanning tunneling microscope (STM) images obtained using density functional theory (DFT) for two-dimensional (2D) materials, calculated using the Tersoff-Hamann method. It currently contains data fo…
View article: Magnon-phonon hybridization in quasi-2D antiferromagnet MnPSe$_3$
Magnon-phonon hybridization in quasi-2D antiferromagnet MnPSe$_3$ Open
Magnetic excitations in van der Waals (vdW) materials, especially in the two-dimensional (2D) limit, are an exciting research topic from both the fundamental and applied perspectives. Using temperature-dependent, magneto-Raman spectroscopy…
View article: Database of Wannier Tight-binding Hamiltonians using High-throughput\n Density Functional Theory
Database of Wannier Tight-binding Hamiltonians using High-throughput\n Density Functional Theory Open
We develop a computational workflow for high-throughput Wannierization of\ndensity functional theory (DFT) based electronic band structure calculations.\nWe apply this workflow to 1771 materials, and we create a database with the\nresultin…
View article: Data-driven discovery of 3D and 2D thermoelectric materials
Data-driven discovery of 3D and 2D thermoelectric materials Open
In this work, we first perform a systematic search for high-efficiency three-dimensional (3D) and two-dimensional (2D) thermoelectric materials by combining semiclassical transport techniques with density functional theory (DFT) calculatio…
View article: High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses
High-throughput density functional perturbation theory and machine learning predictions of infrared, piezoelectric, and dielectric responses Open
View article: Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning
Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning Open
We develop a computational database, web-apps, and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D)-heterostructures. Using density functional theory (DFT) based lattice-parameters and electronic …
View article: Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning
Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning Open
We develop a computational database, web-apps, and machine-learning (ML) models to accelerate the design and discovery of two-dimensional (2D)-heterostructures. Using density functional theory (DFT) based lattice-parameters and electronic …
View article: Effects of Octahedral Tilting on the Site of Substitution of Manganese in CaTiO <sub>3</sub>
Effects of Octahedral Tilting on the Site of Substitution of Manganese in CaTiO <sub>3</sub> Open