Grain boundary segregation prediction with a dual-solute model

Abstract

Solute segregation along grain boundaries (GBs) profoundly affects their thermodynamic and kinetic behaviors in polycrystalline materials. Recently, the spectral approach has emerged as a powerful tool to predict GB segregation. However, previous GB segregation predictions using this method relied heavily on single-solute segregation energy spectrum without solute-solute interactions, which were often incorporated through a fitting parameter. In this work, we developed a dual-solute model whose segregation energy spectrum intrinsically incorporates solute-solute interactions. It was first validated for GB segregation prediction in the Al-Mg system and then extended to several other distinct binary alloy systems. The dual-solute model shows significant improvement over the single-solute model and can accurately predict the real segregation states obtained by hybrid Molecular Dynamics/Monte Carlo simulations within a broad temperature range with different solute concentrations before forming secondary phases. This dual-solute model provides an effective method for accurately predicting GB segregation in nanocrystalline metals.