UC Santa Barbara

Crystal growth shapes must be optimized with respect to product functionality. Rapid in silico calculations of crystal habits, coupled with theoretical understanding of the physical processes that drive them, will enable intelligent navigation across the vast design space of growth conditions. This dissertation focuses on upgrading a multi-scale mechanistic modeling framework to realize such a design aid for systematic shape engineering.

First, underlying kinetic rate expressions for growth unit attachment and detachment are clarified, and the incorporation mechanism is considered. Second, a method for predicting the dominant growth regime operating on each face is introduced, which enables the effect of supersaturation on crystal shape to be accounted for. Third, the effect of solvent on crystal shape is investigated and a practical technique to account for it is detailed. Fourth, a model for the velocity of a step edge with non-centrosymmetric growth units is developed, which can account for complex instability phenomena unique to this general class of crystals. For each model development, predictions are tested against experimental crystal morphologies (or kinetic Monte Carlo simulations for the case of step velocities), to confirm accuracy. Finally, the strategy for overall model execution and automation is detailed.

These developments act to increase predictive accuracy and enable application of mechanistic models to a wider array of systems and growth conditions, while providing insight for rational crystal engineering.