Lysgaard, Steen
Jennings, Paul C.
HummelshÃ¸j, Jens Strabo
Bligaard, Thomas
Vegge, Tejs
Machine Learning Accelerated Genetic Algorithms for Computational Materials Search
A machine learning model is used as a surrogate fitness evaluator in a genetic algorithm (GA) optimization of the atomic distribution of Pt-Au nanoparticles. The machine learning accelerated genetic algorithm (MLaGA) yields a 50-fold reduction of required energy calculations compared to a traditional GA.
Genetic algorithms;Nanoparticle Catalysts;Machine Learning;Gaussian process regression model;PtAu;Icosahedral Pt Au nanoparticles;Density Functional Theory;GPAW;Effective Medium Theory
2018-12-03
https://chemrxiv.org/articles/Machine_Learning_Accelerated_Genetic_Algorithms_for_Computational_Materials_Search/7411172

10.26434/chemrxiv.7411172.v1