机构:University of Cambridge,Cavendish Laboratory, Department of Physics
Valerio Vitale
Giovanni Pizzi
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机构:University of Cambridge,Cavendish Laboratory, Department of Physics
Giovanni Pizzi
Antimo Marrazzo
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机构:University of Cambridge,Cavendish Laboratory, Department of Physics
Antimo Marrazzo
Jonathan R. Yates
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机构:University of Cambridge,Cavendish Laboratory, Department of Physics
Jonathan R. Yates
Nicola Marzari
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机构:University of Cambridge,Cavendish Laboratory, Department of Physics
Nicola Marzari
Arash A. Mostofi
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机构:University of Cambridge,Cavendish Laboratory, Department of Physics
Arash A. Mostofi
机构:
[1] University of Cambridge,Cavendish Laboratory, Department of Physics
[2] Imperial College London,Departments of Materials and Physics, and the Thomas Young Centre for Theory and Simulation of Materials
[3] École Polytechnique Fédérale de Lausanne,Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL)
Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high-throughput (HT) computational materials design is an emergent field that promises to accelerate reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical space. We assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles calculations. Finally, we provide a downloadable virtual machine that can be used to reproduce the results of this paper, including all first-principles and atomistic simulations as well as the computational workflows.
机构:
AbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USAAbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USA
Pan, Jeffrey Y.
Chang-Yen, David
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AbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USAAbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USA
Chang-Yen, David
Blanchard, David P.
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AbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USAAbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USA
Blanchard, David P.
Lam, Wil
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AbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USAAbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USA
Lam, Wil
Searle, Philip A.
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AbbVie, Discovery Platform Technol DPS, APS, N Chicago, IL USAAbbVie, Integrated Sci & Technol iSAT Discovery, Specialized Res Chaot Syst SPaRCS, N Chicago, IL USA
机构:
Abbott Labs, Global Pharmaceut Res & Dev, Neurosci Res Dept R4PM, Abbott Pk, IL 60064 USAAbbott Labs, Global Pharmaceut Res & Dev, Neurosci Res Dept R4PM, Abbott Pk, IL 60064 USA