High-Throughput Discovery of Novel Cubic Crystal Materials Using Deep Generative Neural Networks.

Zhao, Yong; Al-Fahdi, Mohammed; Hu, Ming; Siriwardane, Edirisuriya M D; Song, Yuqi; Nasiri, Alireza; Hu, Jianjun

Zhao, Yong; Al-Fahdi, Mohammed; Hu, Ming; Siriwardane, Edirisuriya M D; Song, Yuqi; Nasiri, Alireza; Hu, Jianjun.

Afiliação

Zhao Y; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.
Al-Fahdi M; Department of Mechanical Engineering, University of South Carolina, Columbia, SC, 29201, USA.
Hu M; Department of Mechanical Engineering, University of South Carolina, Columbia, SC, 29201, USA.
Siriwardane EMD; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.
Song Y; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.
Nasiri A; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.
Hu J; Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29201, USA.

Adv Sci (Weinh) ; 8(20): e2100566, 2021 10.

Article em En | MEDLINE | ID: mdl-34351707

Palavras-chave

crystal structure generation; cubic crystals; deep neural networks; generative adversarial networks

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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