Article abstract


Nature Materials 5, 641 - 646 (2006)
doi:10.1038/nmat1691

Subject Categories: Metals and alloys | Characterisation and analytical techniques | Computation, modelling and theory

Predicting crystal structure by merging data mining with quantum mechanics

Christopher C. Fischer1, Kevin J. Tibbetts1, Dane Morgan2 and Gerbrand Ceder1


Modern methods of quantum mechanics have proved to be effective tools to understand and even predict materials properties. An essential element of the materials design process, relevant to both new materials and the optimization of existing ones, is knowing which crystal structures will form in an alloy system. Crystal structure can only be predicted effectively with quantum mechanics if an algorithm to direct the search through the large space of possible structures is found. We present a new approach to the prediction of structure that rigorously mines correlations embodied within experimental data and uses them to direct quantum mechanical techniques efficiently towards the stable crystal structure of materials.

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  1. Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
  2. Department of Materials Science and Engineering, University of Wisconsin, Madison, Wisconsin 53706, USA

Correspondence to: Gerbrand Ceder1 e-mail: gceder@mit.edu


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