A deep equivariant neural network approach for efficient hybrid density functional calculations.

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Title: A deep equivariant neural network approach for efficient hybrid density functional calculations.
Authors: Tang Z; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China., Li H; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China.; Institute for Advanced Study, Tsinghua University, 100084, Beijing, China., Lin P; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, 100190, Beijing, China.; Songshan Lake Materials Laboratory, 523808, Dongguan, Guangdong, China.; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, 230026, Hefei, Anhui, China., Gong X; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China.; School of Physics, Peking University, 100871, Beijing, China., Jin G; Key Laboratory of Quantum Information, University of Science and Technology of China, 230026, Hefei, Anhui, China., He L; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, 230026, Hefei, Anhui, China.; Key Laboratory of Quantum Information, University of Science and Technology of China, 230026, Hefei, Anhui, China., Jiang H; College of Chemistry and Molecular Engineering, Peking University, 100871, Beijing, China., Ren X; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, 100190, Beijing, China. renxg@iphy.ac.cn.; Songshan Lake Materials Laboratory, 523808, Dongguan, Guangdong, China. renxg@iphy.ac.cn., Duan W; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China. duanw@tsinghua.edu.cn.; Institute for Advanced Study, Tsinghua University, 100084, Beijing, China. duanw@tsinghua.edu.cn.; Frontier Science Center for Quantum Information, Beijing, China. duanw@tsinghua.edu.cn., Xu Y; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China. yongxu@mail.tsinghua.edu.cn.; Frontier Science Center for Quantum Information, Beijing, China. yongxu@mail.tsinghua.edu.cn.; RIKEN Center for Emergent Matter Science (CEMS), Wako, Saitama, 351-0198, Japan. yongxu@mail.tsinghua.edu.cn.
Source: Nature communications [Nat Commun] 2024 Oct 11; Vol. 15 (1), pp. 8815. Date of Electronic Publication: 2024 Oct 11.
Publication Type: Journal Article
Journal Info: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE; PubMed not MEDLINE
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  Data: A deep equivariant neural network approach for efficient hybrid density functional calculations.
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  Data: <searchLink fieldCode="AU" term="%22Tang+Z%22">Tang Z</searchLink>; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Li+H%22">Li H</searchLink>; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China.; Institute for Advanced Study, Tsinghua University, 100084, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Lin+P%22">Lin P</searchLink>; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, 100190, Beijing, China.; Songshan Lake Materials Laboratory, 523808, Dongguan, Guangdong, China.; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, 230026, Hefei, Anhui, China.<br /><searchLink fieldCode="AU" term="%22Gong+X%22">Gong X</searchLink>; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China.; School of Physics, Peking University, 100871, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Jin+G%22">Jin G</searchLink>; Key Laboratory of Quantum Information, University of Science and Technology of China, 230026, Hefei, Anhui, China.<br /><searchLink fieldCode="AU" term="%22He+L%22">He L</searchLink>; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, 230026, Hefei, Anhui, China.; Key Laboratory of Quantum Information, University of Science and Technology of China, 230026, Hefei, Anhui, China.<br /><searchLink fieldCode="AU" term="%22Jiang+H%22">Jiang H</searchLink>; College of Chemistry and Molecular Engineering, Peking University, 100871, Beijing, China.<br /><searchLink fieldCode="AU" term="%22Ren+X%22">Ren X</searchLink>; Beijing National Laboratory for Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, 100190, Beijing, China. renxg@iphy.ac.cn.; Songshan Lake Materials Laboratory, 523808, Dongguan, Guangdong, China. renxg@iphy.ac.cn.<br /><searchLink fieldCode="AU" term="%22Duan+W%22">Duan W</searchLink>; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China. duanw@tsinghua.edu.cn.; Institute for Advanced Study, Tsinghua University, 100084, Beijing, China. duanw@tsinghua.edu.cn.; Frontier Science Center for Quantum Information, Beijing, China. duanw@tsinghua.edu.cn.<br /><searchLink fieldCode="AU" term="%22Xu+Y%22">Xu Y</searchLink>; State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, 100084, Beijing, China. yongxu@mail.tsinghua.edu.cn.; Frontier Science Center for Quantum Information, Beijing, China. yongxu@mail.tsinghua.edu.cn.; RIKEN Center for Emergent Matter Science (CEMS), Wako, Saitama, 351-0198, Japan. yongxu@mail.tsinghua.edu.cn.
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  Data: <searchLink fieldCode="JN" term="%22101528555%22">Nature communications</searchLink> [Nat Commun] 2024 Oct 11; Vol. 15 (1), pp. 8815. <i>Date of Electronic Publication: </i>2024 Oct 11.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Pub%2E+Group%22">Nature Pub. Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101528555 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2041-1723 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220411723%22">20411723 </searchLink><i>NLM ISO Abbreviation: </i>Nat Commun <i>Subsets: </i>MEDLINE; PubMed not MEDLINE
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        Value: 10.1038/s41467-024-53028-4
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              Text: 2024 Oct 11
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