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

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.

Duke Authors

Cited Authors

  • Ceder, G; Morgan, D; Fischer, C; Tibbetts, K; Curtarolo, S

Published Date

  • 2006

Published In

Volume / Issue

  • 31 / 12

Start / End Page

  • 981 - 985

International Standard Serial Number (ISSN)

  • 0883-7694

Citation Source

  • SciVal