Exploring the configurational space of amorphous graphene with machine-learned atomic energies
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- Zakariya El-Machachi
- Department of Chemistry, Inorganic Chemistry Laboratory, University of Oxford, Oxford OX1 3QR, UK
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- Mark Wilson
- Department of Chemistry, Physical and Theoretical Chemistry Laboratory, University of Oxford, Oxford OX1 3QZ, UK
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- Volker L. Deringer
- Department of Chemistry, Inorganic Chemistry Laboratory, University of Oxford, Oxford OX1 3QR, UK
書誌事項
- 公開日
- 2022
- 権利情報
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- http://creativecommons.org/licenses/by/3.0/
- DOI
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- 10.1039/d2sc04326b
- 公開者
- Royal Society of Chemistry (RSC)
この論文をさがす
説明
<jats:p>Machine-learning models for atomic energies can be used to drive Monte-Carlo structural exploration, and also to obtain new insight into disordered structures – as demonstrated here for amorphous graphene.</jats:p>
収録刊行物
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- Chemical Science
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Chemical Science 13 (46), 13720-13731, 2022
Royal Society of Chemistry (RSC)