Adaptive Genetic Algorithm Method for Crystal Structure Prediction
|Date/Time:||Thursday, 11 Apr 2013 - Thursday, 11 Apr 2013|
|Location:||PHYSICS Hall Room 5|
|Channel:||Condensed Matter Physics|
Ames Laboratory - US DOE and Department of Physics and Astronomy, Iowa State University, Ames, Iowa 50011, USA
We have developed a fast and efficient method for crystal structure prediction and materials discovery. Our method performs genetic algorithm (GA) searches using auxiliary classical potentials to screen the energies of candidate structures, and select only a few of them for more extensive first-principles evaluation. Parameters of the auxiliary potentials are adaptively adjusted to reproduce the first-principles results during the course of the GA search. Therefore, the adaptive GA method can combine the speed of empirical potential searches with the accuracy of first-principles calculations. The efficiency of the adaptive GA method allows a great increase in the size and complexity of systems that can be studied. The performance of adaptive GA is demonstrated by application to various metallic alloys systems.