Stochastic statistical theory of nucleation and evolution of nano-sized precipitates in alloys with application to precipitation of copper in iron

TL;DR

This paper introduces a stochastic statistical approach (SSA) for modeling nano-sized precipitate formation in alloys, demonstrating good agreement with Monte Carlo simulations and enabling analysis of microstructural evolution under different conditions.

Contribution

The paper develops a computationally efficient SSA method for alloy precipitation kinetics, incorporating a new parameter estimation based on thermodynamic principles.

Findings

SSA results agree well with kinetic Monte Carlo simulations

The approach effectively models microstructure evolution under varying temperature and concentration

The method provides a practical tool for studying alloy precipitation processes

Abstract

The consistent and computationally efficient stochastic statistical approach (SSA) is suggested to study kinetics of nucleation and evolution of nano-sized precipitates in alloys. An important parameter of the theory is the size of locally equilibrated regions at the nucleation stage which is estimated using the "maximum thermodynamic gain" principle suggested. For several realistic models of iron-copper alloys studied, the results of the SSA-based simulations of precipitation kinetics agree well with the kinetic Monte Carlo simulation results for all main characteristics of microstructure. The approach developed is also used to study kinetics of nucleation and changes in microstructural evolution under variations of temperature or concentration.