Use machine learning to find energy materials

被引：92

作者：

De Luna, Phil ^{[1
]}

Wei, Jennifer ^{[2
]}

Bengio, Yoshua ^{[3
]}

Aspuru-Guzik, Alan ^{[2
]}

Sargent, Edward ^{[4
]}

机构：

[1] Univ Toronto, Dept Mat Sci & Engn, Toronto, ON, Canada

[2] Harvard Univ, Dept Chem & Chem Biol, Cambridge, MA 02138 USA

[3] Univ Montreal, Dept Comp Sci & Operat Res, MILA, Montreal, PQ, Canada

[4] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON, Canada

来源：

NATURE | 2017年 / 552卷 / 7683期

关键词：

DESIGN;

D O I：

10.1038/d41586-017-07820-6

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Artificial intelligence can speed up research into new photovoltaic, battery and carbon-capture materials, argue Edward Sargent, Alán Aspuru-Guzikand colleagues.

引用

页码：23 / 25

页数：3

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