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| 1 | The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design显示文摘The Joint Automated Repository for Various Integrated Simulations(JARVIS)is an integrated infrastructure to accelerate materials discovery and design using density functional theory(DFT),classical force-fields(FF),and machine learning(ML)techniques.JARVIS is motivated by the Materials Genome Initiative(MGI)principles of developing open-access databases and tools to reduce the cost and development time of materials discovery,optimization,and deployment. | Kamal Choudhary Kevin F.Garrity Andrew C.E.Reid Brian DeCost Adam J.Biacchi Angela R.Hight Walker Zachary Trautt Jason Hattrick-Simpers A.Gilad Kusne Andrea Centrone Albert Davydov Jie Jiang Ruth Pachter Gowoon Cheon Evan Reed Ankit Agrawal Xiaofeng Qian Vinit Sharma Houlong Zhuang Sergei V.Kalinin Bobby G.Sumpter Ghanshyam Pilania Pinar Acar Subhasish Mandal Kristjan Haule David Vanderbilt Karin Rabe Francesca Tavazza | 2020 | npj Computational Materials2020，，1： | 10 |
| 2 | High-throughput density functional perturbation theory and machine learning predictions of infrared,piezoelectric,and dielectric responses显示文摘Many technological applications depend on the response of materials to electric fields,but available databases of such responses are limited.Here,we explore the infrared,piezoelectric,and dielectric properties of inorganic materials by combining highthroughput density functional perturbation theory and machine learning approaches.We computeΓ-point phonons,infrared intensities,Born-effective charges,piezoelectric,and dielectric tensors for 5015 non-metallic materials in the JARVIS-DFT database.We find 3230 and 1943 materials with at least one far and mid-infrared mode,respectively. | Kamal Choudhary Kevin F.Garrity Vinit Sharma Adam J.Biacchi Angela R.Hight Walker Francesca Tavazza | 2020 | npj Computational Materials2020，，1： | 7 |
| 3 | Computational search for magnetic and non-magnetic 2D topological materials using unified spin-orbit spillage screening显示文摘Two-dimensional topological materials(2D TMs)have a variety of properties that make them attractive for applications including spintronics and quantum computation.However,there are only a few such experimentally known materials.To help discover new 2D TMs,we develop a unified and computationally inexpensive approach to identify magnetic and non-magnetic 2D TMs,including gapped and semi-metallic topological classifications,in a high-throughput way using density functional theory-based spin–orbit spillage,Wannier-interpolation,and related techniques. | Kamal Choudhary Kevin F.Garrity Jie Jiang Ruth Pachter Francesca Tavazza | 2020 | npj Computational Materials2020，，1： | 4 |
| 4 | Prediction of Weyl semimetal and antiferromagnetic topological insulator phases in Bi_(2)MnSe_(4)显示文摘Three-dimensional materials with strong spin–orbit coupling and magnetic interactions represent an opportunity to realize a variety of rare and potentially useful topological phases with broken time-reversal symmetry.In this work,we use first principles calculations to show that the recently synthesized material Bi_(2)MnSe_(4) displays a combination of spin–orbit-induced band inversion,also observed in non-magnetic topological insulator Bi2PbSe4,with magnetic interactions,leading to several topological phases.In bulk form,the ferromagnetic phase of Bi_(2)MnSe_(4) has symmetry protected band crossings at the Fermi level,leading to either a nodal line or Weyl semimetal,depending on the direction of the spins.Due to the combination of time reversal symmetry plus a partial translation,the ground state layered antiferromagnetic phase is instead an antiferromagnetic topological insulator.The surface of this phase intrinsically breaks time-reversal symmetry,allowing the observation of the half-integer quantum anomalous Hall effect.Furthermore,we show that in thin film form,for sufficiently thick slabs,Bi_(2)MnSe_(4) becomes a Chern insulator with a band gap of up to 58 meV.This combination of properties in a stoichiometric magnetic material makes Bi_(2)MnSe_(4) an excellent candidate for displaying robust topological behavior. | Sugata Chowdhury Kevin F.Garrity Francesca Tavazza | 2019 | npj Computational Materials2019，，1： | 0 |
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