Stochastic Simulations of Motion of Solute Molecules during the Process of Crystallization Yields the Rate Constants for the Processes of Crystallization

Theoretical and computational understanding of crystallization processes can significantly replace the trial-and-error methods in place for crystallization at different pharmaceutical, chemical and fertilizer industries. However, the self-assembly of molecules during the process of crystallization spans multiple timescales which makes full computational modeling of crystallization process difficult. Recently, with the help of molecular simulations, it was shown that dynamics of solvation shell determines the crystal structure and growth rates. However, more appropriate computational approach is required for calculation of rate constants for nucleation and growth of crystals. In this study, stochastic simulations of glutamic acid molecules were performed. The molecular features of glutamic acid were approximated using the already established models to retain its molecular feature while reducing the computational time. Such approximation allows simulating higher number of glutamic acid molecules in a simulation box for longer times. Findings of this study yield in rate constants for glutamic acid crystallization which reasonably agree with experimental observations. The approach also shows potential to be applied to other crystallization systems.