Machine-learning correction to density-functional crystal structure optimization

被引:0
|
作者
Robert Hussein
Jonathan Schmidt
Tomás Barros
Miguel A. L. Marques
Silvana Botti
机构
[1] Friedrich-Schiller-Universität Jena,Institut für Festkörpertheorie und
[2] European Theoretical Spectroscopy Facility,optik
[3] Martin-Luther-Universität Halle-Wittenberg,Institut für Physik
来源
MRS Bulletin | 2022年 / 47卷
关键词
Machine learning; Crystallographic structure; Predictive;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:765 / 771
页数:6
相关论文
共 50 条
  • [1] Machine learning the derivative discontinuity of density-functional theory
    Gedeon, Johannes
    Schmidt, Jonathan
    Hodgson, Matthew J. P.
    Wetherell, Jack
    Benavides-Riveros, Carlos L.
    Marques, Miguel A. L.
    MACHINE LEARNING-SCIENCE AND TECHNOLOGY, 2022, 3 (01):
  • [2] Machine-learning potentials for crystal defects
    Rodrigo Freitas
    Yifan Cao
    MRS Communications, 2022, 12 : 510 - 520
  • [3] A machine-learning framework for isogeometric topology optimization
    Xia, Zhaohui
    Zhang, Haobo
    Zhuang, Ziao
    Yu, Chen
    Yu, Jingui
    Gao, Liang
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2023, 66 (04)
  • [4] Machine-learning scoring functions for structure-based drug lead optimization
    Li, Hongjian
    Sze, Kam-Heung
    Lu, Gang
    Ballester, Pedro J.
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE, 2020, 10 (05)
  • [5] Machine-Learning in Simulation-Driven Optimization
    Tenne, Yoel
    2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM 2016), 2016, : 32 - 36
  • [6] Use of low-fidelity models with machine-learning error correction for well placement optimization
    Tang, Haoyu
    Durlofsky, Louis J.
    COMPUTATIONAL GEOSCIENCES, 2022, 26 (05) : 1189 - 1206
  • [7] Use of low-fidelity models with machine-learning error correction for well placement optimization
    Haoyu Tang
    Louis J. Durlofsky
    Computational Geosciences, 2022, 26 : 1189 - 1206
  • [8] Design Challenges on Machine-Learning Enabled Resource Optimization
    Karkazis, Panagiotis
    Uzunidis, Dimitris
    Trakadas, Panagiotis
    Leligou, Helen C. C.
    IT PROFESSIONAL, 2022, 24 (05) : 69 - 74
  • [9] Structure exploration of gallium based on machine-learning potential
    Yu, Yaochen
    Fan, Jiahui
    Lei, Yuefeng
    Niu, Haiyang
    JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY, 2025, 232 : 239 - 245
  • [10] MACHINE-LEARNING IN OPTIMIZATION OF EXPENSIVE BLACK-BOX FUNCTIONS
    Tenne, Yoel
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2017, 27 (01) : 105 - 118