A thermodynamic and kinetic-based grain growth model for nanocrystalline materials: Parameter sensitivity analysis and model extension

Mark A. Tschopp, Efraín Hernández-Rivera, Mark A. Atwater, Kiran Solanki, Kris A. Darling

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Predicting grain growth in nanocrystalline materials requires modeling approaches that incorporate grain boundary thermodynamics and kinetics. In this work, the thermokinetic model of Chen et al. (2012) for grain growth was applied to experimental X-ray diffraction measurements from a binary nanocrystalline alloy in an effort (1) to understand the influence of thermodynamic, kinetic, and material parameters in the model; and (2) to extend the thermokinetic model by incorporating temperature dependence. The model performs well for the grain boundary saturated case in the binary nanocrystalline alloy, where it is assumed that solute segregates to the grain boundaries and thermodynamically/kinetically reduces the driving force for grain growth. In this work, a sensitivity analysis of parameters (Monte Carlo global sensitivity analysis) identifies the important thermodynamic/kinetic parameters and their correlation with one another for the present model. This model was then extended to include the change in these independent thermodynamic/kinetic parameters as a function of temperature and to model the effect of initial grain size distribution. This research shows that the thermodynamic and kinetic contributions can describe grain growth in nanocrystalline materials and this extended model can be parameterized for grain size evolution and stabilization with temperature for nanocrystalline systems.

Original languageEnglish (US)
Pages (from-to)250-265
Number of pages16
JournalComputational Materials Science
Volume131
DOIs
StatePublished - Apr 15 2017

Keywords

  • Grain growth
  • Kinetics
  • Nanocrystalline materials
  • Sensitivity analysis
  • Thermodynamics
  • Thermokinetic model

ASJC Scopus subject areas

  • Computer Science(all)
  • Chemistry(all)
  • Materials Science(all)
  • Mechanics of Materials
  • Physics and Astronomy(all)
  • Computational Mathematics

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