ID | 59982 |
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Author |
Misawa, Masaaki
Graduate School of Natural Science and Technology, Okayama University
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Fukushima, Shogo
Department of Physics, Kumamoto University
Koura, Akihide
Department of Physics, Kumamoto University
Shimamura, Kohei
Department of Physics, Kumamoto University
Shimojo, Fuyuki
Department of Physics, Kumamoto University
Tiwari, Subodh
Collaboratory for Advanced Computing and Simulations, University of Southern California
Nomura, Ken-ichi
Collaboratory for Advanced Computing and Simulations, University of Southern California
Kalia, Rajiv K.
Collaboratory for Advanced Computing and Simulations, University of Southern California
Nakano, Aiichiro
Collaboratory for Advanced Computing and Simulations, University of Southern California
Vashishta, Priya
Collaboratory for Advanced Computing and Simulations, University of Southern California
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Abstract | The use of artificial neural network (ANN) potentials trained with first-principles calculations has emerged as a promising approach for molecular dynamics (MD) simulations encompassing large space and time scales while retaining first-principles accuracy. To date, however, the application of ANN-MD has been limited to near-equilibrium processes. Here we combine first-principles-trained ANN-MD with multiscale shock theory (MSST) to successfully describe far-from-equilibrium shock phenomena. Our ANN-MSST-MD approach describes shock-wave propagation in solids with first-principles accuracy but a 5000 times shorter computing time. Accordingly, ANN-MD-MSST was able to resolve fine, long-time elastic deformation at low shock speed, which was impossible with first-principles MD because of the high computational cost. This work thus lays a foundation of ANN-MD simulation to study a wide range of far-from-equilibrium processes.
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Note | This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Physical Chemistry Letters, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jpclett.0c00637.
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Published Date | 2020-05-22
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Publication Title |
Journal of Physical Chemistry Letters
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Volume | volume11
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Issue | issue11
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Publisher | American Chemical Society
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Start Page | 4536
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End Page | 4541
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ISSN | 1948-7185
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NCID | AA1260018X
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Content Type |
Journal Article
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language |
English
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OAI-PMH Set |
岡山大学
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File Version | author
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Related Url | isVersionOf https://doi.org/10.1021/acs.jpclett.0c00637
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Funder Name |
Japan Science and Technology Agency
Ministry of Education, Culture, Sports, Science and Technology
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助成番号 | JPMJCR18I2
20K14378
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