Method and Advantages of Genetic Algorithms in Parameterization of Interatomic Potentials: Metal-Oxides

TL;DR

This paper presents a genetic algorithm-based method for parameterizing interatomic potentials in metal oxides, demonstrating its ability to optimize multiple phases simultaneously and predict properties accurately.

Contribution

It introduces a novel evolutionary computing approach for interatomic potential parameterization that improves optimization efficiency and accuracy for complex materials.

Findings

Successfully optimized force fields for BaTiO3 phases

Predicted physical properties closely match experimental data

Method effectively handles multiple local minima in parameter space

Abstract

The method and the advantages of an evolutionary computing based approach using a steady state genetic algorithm (GA) for the parameterization of interatomic potentials for metal oxides within the shell model framework are developed and described. We show that the GA based methodology for the parameterization of interatomic force field functions is capable of (a) simultaneous optimization of the multiple phases or properties of a material in a single run, (b) facilitates the incremental re-optimization of the whole system as more data is available for either additional phases or material properties not included in previous runs, and (c) successful global optimization in the presence of multiple local minima in the parameter space. As an example, we apply the method towards simultaneous optimization of four distinct crystalline phases of Barium Titanate (BaTiO3 or BTO) using an ab initio density functional theory (DFT) based reference dataset. We find that the optimized force field function is capable of the prediction of the two phases not used in the optimization procedure, and that many derived physical properties such as the equilibrium lattice constants, unit cell volume, elastic properties, coefficient of thermal expansion, and average electronic polarization are in good agreement with the experimental results available from the literature.