A three dimensional kinetic Monte Carlo defect-free crystal dissolution model for biological systems, with application to uncertainty analysis and robust optimization. (January 2022) - Chaffart, Donovan; Ricardez-Sandoval, Luis A.
Highlights: A 3D kinetic Monte Carlo (kMC) model is developed to simulate crystal dissolution. The novel kMC model is applied to simulate CaCO3 dissolution within the human body. Polynomial chaos expansions used to propagate uncertainty through the kMC model. Low-order models developed to predict PCE coefficients for various crystal designs. Low-order models used to perform robust optimization on crystal dissolution process. Abstract: The objective of this study was to construct a novel kinetic Monte Carlo (kMC) model to predict the complete dissolution of nanoscale crystals. The developed framework was designed to predict the dissolution of a wide variety of crystalline minerals, regardless of their composition and crystal structure. The proposed framework was used to explore ways of enhancing crystal dissolution processes by assessing the variability from environmental uncertainties and by performing robust optimization to improve the dissolution performance. The approach was used to simulate calcium carbonate dissolution within the human gastrointestinal system. Polynomial chaos expansions (PCEs) were used to propagate the parametric uncertainty through the kMC model. Robust optimization was subsequently performed to determine the crystal design parameters that achieve target dissolution specifications using low-order PCE coefficient models. The results showcased the applicability of the kMC crystal dissolution model and the need to account for dissolution uncertainty within key biological applications.