Art

J-GLOBAL ID：202002210996839999   Reference number：20A0489552

Machine Learning for Catalysis Informatics: Recent Applications and Prospects

触媒情報学のための機械学習:最近の応用と展望【JST・京大機械翻訳】

Author (10)： Toyao Takashi (Institute for Catalysis, Hokkaido University, Japan) ,  Toyao Takashi (Elements Strategy Initiative for Catalysts and Batteries, Kyoto University, Japan) ,  Maeno Zen (Institute for Catalysis, Hokkaido University, Japan) ,  Takakusagi Satoru (Institute for Catalysis, Hokkaido University, Japan) ,  Kamachi Takashi (Elements Strategy Initiative for Catalysts and Batteries, Kyoto University, Japan) ,  Kamachi Takashi (Department of Life, Environment and Materials Science, Fukuoka Institute of Technology, Japan) ,  Takigawa Ichigaku (RIKEN, Center for Advanced Intelligence Project, Tokyo, Japan) ,  Takigawa Ichigaku (Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Hokkaido, Japan) ,  Shimizu Ken-ichi (Institute for Catalysis, Hokkaido University, Japan) ,  Shimizu Ken-ichi (Elements Strategy Initiative for Catalysts and Batteries, Kyoto University, Japan)
Material： ACS Catalysis
Volume： 10  Issue： 3  Page： 2260-2297  Publication year： 2020 
JST Material Number： W5035A  ISSN： 2155-5435  Document type： Article
Article type： 文献レビュー  Country of issue： United States (USA)  Language： ENGLISH (EN)

Abstract/Point： The discovery and development ...

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Thesaurus term： *Machine Learning ,  catalytic activity ,  chemical substance ,  ecology (science) ,  *Information Science ,  Structure-Activity Relationship ,  *catalyst ,  Data Mining ,  time dependence ,  characterization ,  community (group) ,  complexity ,  *cultural science
Semi thesaurus term： ハイスループット ,  触媒作用 ,  パラダイムシフト , 【Automatic Indexing@JST】

Author keywords (5)： machine learning ,  catalysis informatics ,  high-throughput experiments/computations ,  data mining ,  structure-activity relationships

JST classification (2)： Other catalysts  (CB06123Z) ,  Nobel metal catalysts  (CB06122I)

Terms in the title (5)： 触媒 ,  情報学 ,  機械学習 ,  応用 ,  展望