Art

J-GLOBAL ID：201902254141076805   Reference number：19A1400611

Improved Thermoelectric Properties of Hot-Extruded Bi-Te-Se Bulk Materials with Cu Doping and Property Predictions via Machine Learning

機械学習によるCuドーピングと特性予測による熱間押出Bi-Te-Seバルク材料の改善された熱電特性【JST・京大機械翻訳】

Author (6)： Wang Zhi-Lei (Department of Mechanical and Aerospace Engineering, Tottori University, Koyama-minami 4-101, Tottori, 680-8552, Japan) ,  Wang Zhi-Lei (Department of Materials Science and Engineering, Nagoya University, Furou-cho, Chikusa-ku, Nagoya, 464-8601, Japan) ,  Yokoyama Yuuki (Department of Mechanical and Aerospace Engineering, Tottori University, Koyama-minami 4-101, Tottori, 680-8552, Japan) ,  Onda Tetsuhiko (Department of Mechanical and Aerospace Engineering, Tottori University, Koyama-minami 4-101, Tottori, 680-8552, Japan) ,  Adachi Yoshitaka (Department of Materials Science and Engineering, Nagoya University, Furou-cho, Chikusa-ku, Nagoya, 464-8601, Japan) ,  Chen Zhong-Chun (Department of Mechanical and Aerospace Engineering, Tottori University, Koyama-minami 4-101, Tottori, 680-8552, Japan)
Material： Advanced Electronic Materials
Volume： 5  Issue： 6  Page： e1900079  Publication year： 2019 
JST Material Number： W2482A  ISSN： 2199-160X  Document type： Article
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)

Abstract/Point： Cu-doped Bi₂Te<sub>...

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Thesaurus term： *doping ,  *forecast ,  thermal conductivity ,  *hot extrusion ,  thermoelectric material ,  *machine learning ,  micro structure ,  *copper ,  materials science ,  material design ,  carrier density ,  electrical resistivity
Semi thesaurus term： 材料特性 ,  データ駆動 ,  *熱電特性 , 【Automatic Indexing@JST】

Author keywords (5)： bismuth telluride ,  Cu doping ,  hot extrusion ,  machine learning ,  property predictions

JST classification (2)： Semiconductor thin films  (BK14040E) ,  Electronic structure of surfaces  (BM02080J)

Terms in the title (10)： 機械学習 ,  Cu ,  ドーピング ,  予測 ,  熱間押出 ,  Bi ,  Te ,  Se ,  バルク材料 ,  熱電特性