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Structure and stability prediction of compounds with evolutionary algorithms.
Revard, Benjamin C; Tipton, William W; Hennig, Richard G.
Afiliación
  • Revard BC; Department of Materials Science and Engineering, Cornell University, Ithaca, 14853, New York, USA.
Top Curr Chem ; 345: 181-222, 2014.
Article en En | MEDLINE | ID: mdl-24515753
Crystal structure prediction is a long-standing challenge in the physical sciences. In recent years, much practical success has been had by framing it as a global optimization problem, leveraging the existence of increasingly robust and accurate free energy calculations. This optimization problem has often been solved using evolutionary algorithms (EAs). However, many choices are possible when designing an EA for structure prediction, and innovation in the field is ongoing. We review the current state of evolutionary algorithms for crystal structure and composition prediction and discuss the details of methodological and algorithmic choices. Finally, we review the application of these algorithms to many systems of practical and fundamental scientific interest.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Evolución Biológica / Compuestos Inorgánicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Top Curr Chem Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos / Evolución Biológica / Compuestos Inorgánicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Top Curr Chem Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos