Nucleation is the least understood stage of crystallization of undercooled liquids. A wealth of knowledge on the phenomenon was obtained from experiments on colloidal suspensions and from Brownian dynamics simulations, including the presence of amorphous precursor mediated two-step nucleation, lifting-off of heterogeneously nucleated crystals from curved surfaces, and non-monotonous dependence of nucleation rate on shear flow. Crystalline aggregation in colloids is usually considered a fair approximation of freezing in simple liquids, although the respective time and length scales and the dynamics are obviously very different. It is of high importance to learn how far the results obtained for colloids apply to simple fluids like metallic melts, especially that nucleation in metallic melts is inaccessible for in situ experiments, thus a molecular scale theoretical approach tested against molecular dynamics (MD) simulation is required. While models for diffusion controlled colloidal crystal aggregation are present for some time, molecular scale treatment of crystallization in simple liquids requires hydrodynamic density relaxation. During the planned research, we employ a recently developed molecular scale model of ours, which is based on combining fluctuating non-linear hydrodynamics with a molecular scale phase-field model (the Phase-Field Crystal theory) for investigating whether the phenomena observed in the case of nucleation in colloids indeed exist on the molecular scale. The results will be compared to MD simulations.
For background information see papers at: http://www.phasefield.hu
The applicant should win a PhD scholarship or MTA Young Researcher scholarship. The successful applicant will work as part of our small team, with our CPU and/or high-end GPU clusters. We offer increased salary and the possibility of presenting his/her work at international meetings and conferences.
The planned work will be supported by an NKFIH "Frontline" Research Excellence Project of title "Modeling crystal morphology at various length scales: From atomic scale to biological systems".
Required knowledge: statistical physics of phase transitions, ability to develop codes, experience in programming of GPUs and GPU clusters. Experience in MD simulations is preferable.
English and Hungarian language