Kinetic Monte Carlo (KMC) simulation of sintering of nickel oxide-yttria stabilized zirconia composites: Model, parameter calibration and validation

Abstract

This study proposes a kinetic Monte Carlo (KMC) model for the sintering of two-phase composites using nickel oxide-yttria stabilized zirconia (NiO-YSZ) as a case study. An artificial neural network (ANN) assisted method is used to calibrate the KMC model parameters by comparing the simulated microstructures and the real microstructure reconstructed by focused ion beam scanning electron microscopy (FIB-SEM). It is demonstrated that the ANN calibrated KMC model can predict quantitatively the microstructure evolution of NiO-YSZ composite. The microstructural parameters such as volume fraction, specific surface area, and triple-phase boundary length density of sintered NiO-YSZ are well predicted within acceptable errors. The proposed framework can be adapted for the simulation of the microstructure evolution of any other composite electrodes for solid oxide fuel cells and other composites fabricated by sintering.

Keywords

• Sintering
• Solid oxide fuel cell
• Kinetic Monte Carlo
• Artificial neural network
• Microstructure
• Composites