材料シミュレーションによる蓄電池材料の探索

中山 将伸; Randy JALEM; 木村 真夕実; 春日 敏宏

doi:10.1380/jsssj.36.527

特集：マテリアルズ・インフォマティクス—表面科学のビッグ・データの構築—

材料シミュレーションによる蓄電池材料の探索

中山将伸, Randy JALEM, 木村真夕実, 春日敏宏

著者情報

キーワード: density functional theory, force field method, secondary battery, machine learning, high-throughput

ジャーナルフリー

2015 年 36 巻 10 号 p. 527-532

DOI https://doi.org/10.1380/jsssj.36.527

詳細

抄録

Materials exploration for the functional materials are always essential, but this process is often time and cost demanding and uncertain. Recently, intensive efforts are made to develop “high-throughput computational materials exploration” in order to discover effectively the best materials with targeted properties. Present review article introduces the concept and several examples on the development of high-throughput computations, in particular for battery materials.

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