Open AccessOptimization of shell model potential parameters of BaTiO3 by genetic algorithm
Author(s) -
Xiaoqin Hu,
Guofeng Xie
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.013401
Subject(s) - shell (structure) , key (lock) , computer science , shell model , genetic algorithm , sensitivity (control systems) , biological system , phase transition , optimization algorithm , task (project management) , algorithm , materials science , molecular dynamics , function (biology) , statistical physics , mathematical optimization , physics , thermodynamics , machine learning , computational chemistry , mathematics , chemistry , computer security , atomic physics , electronic engineering , evolutionary biology , engineering , composite material , biology , management , economics
Shell model potential is widely applied to molecular dynamics simulations of ionic crystal, and the parameters of shell model potential function are crucial to the simulation veracity. The parameters of shell model of multi-oxide are numerous, and the optimization is a challenging task. In this paper, the sensitivity analysis is applied to find the key parameters which affect structure and properties mostly in all the shell model potential parameters of BaTiO3. Whereafter, the genetic algorithm is applied to optimize the key parameters, and the insignificant parameters are kept constant in optimization. The results show that the structures, physical properties and phase transition of BaTiO3 simulated by the optimized potential agree well with the experimental data.