Entropy-driven microstructure evolution predicted with the steepest-entropy-ascent quantum thermodynamic framework

A Potts model and the Replica Exchange Wang-Landau algorithm are used to construct an energy landscape for a crystalline solid containing surfaces grain boundaries. The is applied equation of motion from steepest-entropy-ascent quantum thermodynamic (SEAQT) framework explore kinetics three distinct kinds microstructural evolution: polycrystalline sintering, precipitate coarsening, growth. steepest entropy ascent postulate predicts unique kinetic paths these non-equilibrium processes without needing any detailed information about underlying physical mechanisms processes. method also proposed associating path in state space set smoothly evolving descriptors. SEAQT-predicted agree well with available experimental ZrO2 Al3Li growth nanocrystalline Pd. computational cost associated calculating needed by approach comparable Monte Carlo simulation. However, subsequent calculations SEAQT quite modest save considerable resources obviating need averaging multiple runs.