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Unveiling the principle descriptor for predicting the electron inelastic mean free path based on a machine learning framework.
Liu, Xun; Hou, Zhufeng; Lu, Dabao; Da, Bo; Yoshikawa, Hideki; Tanuma, Shigeo; Sun, Yang; Ding, Zejun.
Affiliation
  • Liu X; Hefei National Laboratory for Physical Sciences at Microscale and Department of Physics, University of Science and Technology of China, Hefei, Anhui, People's Republic of China.
  • Hou Z; Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Ibaraki, Japan.
  • Lu D; Research Center for Advanced Measurement and Characterization, National Institute for Materials Science, Tsukuba, Ibaraki, Japan.
  • Da B; State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, China.
  • Yoshikawa H; Hefei National Laboratory for Physical Sciences at Microscale and Department of Physics, University of Science and Technology of China, Hefei, Anhui, People's Republic of China.
  • Tanuma S; Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Ibaraki, Japan.
  • Sun Y; Research Center for Advanced Measurement and Characterization, National Institute for Materials Science, Tsukuba, Ibaraki, Japan.
  • Ding Z; Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Ibaraki, Japan.
Sci Technol Adv Mater ; 20(1): 1090-1102, 2019.
Article de En | MEDLINE | ID: mdl-31807220
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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Sci Technol Adv Mater Année: 2019 Type de document: Article
Texte intégral
Ajouter à My VHL
Imprimer
XML
PubMed Links
Recherche sur Google

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Prognostic_studies / Risk_factors_studies Langue: En Journal: Sci Technol Adv Mater Année: 2019 Type de document: Article