Abstract
Water is a driving factor in the degradation process of biodegradable polymers. However, water diffusion is typically not incorporated in the kinetic models of biodegradation such as kinetic Monte Carlo (kMC), because water diffusion events occur at a much shorter time scale than the hydrolysis reactions. As such, there is a need to improve the computational efficiency of water diffusion in the kMC models of diffusion processes in biodegra-dation. In this work, a new dimensionality reduction scheme for kMC diffusion models is developed to signifi-cantly reduce the computation time, where a two-dimensional kMC diffusion model for porous microstructures is reduced to one-dimensional ones. The dimensionality reduction is accomplished by calibrating the model pa-rameters with multi-objective Bayesian optimization. The reduced-order diffusion model shows a 675-fold faster computation compared to the original two-dimensional model.
NSTL
Elsevier