Fitting database entries for a modified embedded atom method potential for interstitial oxygen in titanium

Abstract

Modeling oxygen interstitials in titanium requires a new empirical potential. We optimize potential parameters using a fitting database of first-principle oxygen interstitial energies and forces. A new database optimization algorithm based on Bayesian sampling is applied to obtain an optimal potential for a specific testing set of density functional data. A parallel genetic algorithm minimizes the sum of logistic function evaluations of the testing set predictions. We test the transferability of the potential model against oxygen interstitials in HCP titanium, transition barriers between oxygen interstitial sites, oxygen in the titanium prismatic stacking fault. The potential is applicable to oxygen interaction with the titanium screw dislocation, and predicts that the interactions between oxygen and the dislocation core is weak and short-ranged.