Interplay between thermal vacancy and short-range order in complex concentrated alloys

Abstract

This work investigates the interplay between thermal vacancy and short-range order (SRO) in complex concentrated alloys (CCAs) for the purposes of accurately predicting SRO evolution kinetics and elemental diffusivities. Taking equiatomic NiCoCr as the model alloy, high-throughput atomic calculations show that SRO shifts the distributions of both vacancy formation energy and migration barrier, with a trend of reducing equilibrium vacancy concentration and vacancy diffusivity. To incorporate the effect of SRO on diffusion kinetics, a comprehensive framework is developed by coupling a machine learning model trained by atomistic calculations that predicts thermodynamic and kinetic properties of vacancy, a lattice kinetic Monte Carlo (LKMC) model that evolves chemical ordering, and a thermodynamic theory that computes equilibrium vacancy concentration. Several recently proposed theoretical models are benchmarked against Grand Canonical Monte Carlo (GCMC) simulations to resolve the controversy in computing equilibrium vacancy concentration, which is needed for converting the LKMC simulation time to real time. Based on LKMC results, Time-Temperature-Ordering (TTO) diagrams are constructed to predict SRO development kinetics, highlighting the critical importance of capturing concurrent evolution of SRO and thermal vacancy concentration and diffusivity. Further, a new algorithm for quantifying dynamic vacancy trapping in the SRO state is developed to elucidate its impact on tracer-diffusion relative to jump frequency and correlation factor.