Editorial: Machine Learning in Materials Science

被引:0
|
作者
Merz, Kenneth M. [1 ]
Choong, Yee Siew [2 ]
Cournia, Zoe [3 ]
Isayev, Olexandr [4 ]
Soares, Thereza A. [5 ]
Wei, Guo-Wei [6 ]
Zhu, Feng [7 ]
机构
[1] Michigan State Univ, Dept Chem, Lansing, MI 48824 USA
[2] Univ Sains Malaysia, Inst Res Mol Med INFORMM, Minden 11800, Penang, Malaysia
[3] Biomed Res Fdn, Acad Athens, Athens 11527, Greece
[4] Carnegie Mellon Univ, Mellon Coll Sci, Dept Chem, Pittsburgh, PA 15213 USA
[5] Univ Sao Paulo, Dept Quim, Fac Filosofia Ciencias & Letras Ribeirao Preto, BR-14049 Ribeirao Preto, SP, Brazil
[6] Michigan State Univ, Dept Math, Lansing, MI 48824 USA
[7] Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Peoples R China
关键词
D O I
10.1021/acs.jcim.4c00727
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
引用
收藏
页码:3959 / 3960
页数:2
相关论文
共 50 条
  • [31] DScribe: Library of descriptors for machine learning in materials science
    Himanen, Lauri
    Jager, Marc O. J.
    Morooka, Eiaki, V
    Canova, Filippo Federici
    Ranawat, Yashasvi S.
    Gao, David Z.
    Rinke, Patrick
    Foster, Adam S.
    [J]. COMPUTER PHYSICS COMMUNICATIONS, 2020, 247
  • [32] Encoding the atomic structure for machine learning in materials science
    Li, Shunning
    Liu, Yuanji
    Chen, Dong
    Jiang, Yi
    Nie, Zhiwei
    Pan, Feng
    [J]. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE, 2022, 12 (01)
  • [33] Interpretable and Explainable Machine Learning for Materials Science and Chemistry
    Oviedo, Felipe
    Ferres, Juan Lavista
    Buonassisi, Tonio
    Butler, Keith T.
    [J]. ACCOUNTS OF MATERIALS RESEARCH, 2022, 3 (06): : 597 - 607
  • [34] Functional Output Regression for Machine Learning in Materials Science
    Iwayama, Megumi
    Wu, Stephen
    Liu, Chang
    Yoshida, Ryo
    [J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2022, 62 (20) : 4837 - 4851
  • [35] Machine learning and data science in soft materials engineering
    Ferguson, Andrew L.
    [J]. JOURNAL OF PHYSICS-CONDENSED MATTER, 2018, 30 (04)
  • [36] Big-Data Science in Porous Materials: Materials Genomics and Machine Learning
    Jablonka, Kevin Maik
    Ongari, Daniele
    Moosavi, Seyed Mohamad
    Smit, Berend
    [J]. CHEMICAL REVIEWS, 2020, 120 (16) : 8066 - 8129
  • [37] MACHINE LEARNING IN MATERIALS SCIENCE: RECENT PROGRESS AND EMERGING APPLICATIONS
    Mueller, Tim
    Kusne, Aaron Gilad
    Ramprasad, Rampi
    [J]. REVIEWS IN COMPUTATIONAL CHEMISTRY, VOL 29, 2016, 29 : 186 - 273
  • [38] Virtual Issue on Machine-Learning Discoveries in Materials Science
    Oliynyk, Anton O.
    Buriak, Jillian M.
    [J]. CHEMISTRY OF MATERIALS, 2019, 31 (20) : 8243 - 8247
  • [39] Identifying domains of applicability of machine learning models for materials science
    Christopher Sutton
    Mario Boley
    Luca M. Ghiringhelli
    Matthias Rupp
    Jilles Vreeken
    Matthias Scheffler
    [J]. Nature Communications, 11
  • [40] A strategy to apply machine learning to small datasets in materials science
    Zhang, Ying
    Ling, Chen
    [J]. NPJ COMPUTATIONAL MATERIALS, 2018, 4