Simulating Thermodynamic Stabilization in Nanocrystalline Binary Alloys Using a Novel Cellular Automaton Model

Abstract

Predictive models for grain growth of nanocrystalline binary alloys are designed to select appropriate solutes and assess thermodynamic stabilization in nanoscale alloy systems. The available models incorporate concepts of free energy, solute segregation, size-misfit elastic strain energy, grain boundary energy and phase field framework. Besides the above factors, the present work proposes a novel cellular automaton model by considering normal grain boundary (GB) diffusion, triple junction GB kinetics and grain misorientation. The experimental data for two kinds of binary alloy system were used to validate the reasonability of the proposed model. For nanocrystalline Fe-4% Zr alloy with large atomic size mismatch and negative mixing enthalpy, compared with the available models, the proposed model shows a better fit to the experimental results for grain size as a function of annealing temperatures. For another binary alloy system with small atomic size mismatch and positive mixing enthalpy, the proposed model also captures well the measurements for grain size of nanocrystalline W-20% Ti alloy. The comparisons reveal that the proposed model has a wide application in addressing the thermal stabilization of nanocrystalline grain size.