Data-mining-driven quantum mechanics for the prediction of structure

被引：42

作者：

Ceder, G.

Morgan, D.

Fischer, C.

Tibbetts, K.

Curtarolo, S.

机构：

来源：

MRS BULLETIN | 2006年 / 31卷 / 12期

基金：

美国国家科学基金会;

关键词：

ab initio; crystal structure; simulation;

D O I：

10.1557/mrs2006.224

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The prediction of crystal structure is a key outstanding problem in materials science and one that is fundamental to computational materials design. We argue that by combining the predictive accuracy of quantum mechanics with data mining tools to extract knowledge from a large body of historical experimental or computational results, this problem can be successfully addressed.

引用

收藏

页码：981 / 985

页数：5

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