  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.
