Abstract:
This thesis uses the kinetic Monte Carlo (KMC) algorithm to examine the
growth morphology and structure of nanocrystals. Crystal growth in a
supersaturated gas of atoms and in an undercooled binary melt is investigated.
First, in the gas phase, the interplay of the deposition and surface
diffusion rates is studied. Then, the KMC algorithm is refined by including
solidification events and finally, by adding diffusion in the surrounding
liquid.
A new algorithm is developed for modelling solidification from an undercooled melt.
This algorithm combines the KMC method, which models
the change in shape of the crystal during growth, with a macroscopic continuum
method that tracks the diffusion of material through solution towards
the crystal. For small length and time scales, this approach provides
simple, effective front tracking with fully resolved atomistic detail of the
crystal-melt interface. Anisotropy is included in the model as a surface
diffusion process and the growth rate of the crystal is found to increase
monotonically with increase in the surface anisotropy value. The method
allows for the study of multiple crystal nuclei and Ostwald ripening. This
method will aid researchers to explain why certain crystal shapes form
under particular conditions during growth, and may enable nanotechnologists
to design techniques for growing nanocrystals with specific shapes
for a variety of applications, from catalysis to the medicine field and electronics
industry. This will lead to a better understanding of the atomistic
process of crystal growth at the nanoscale.
