Crystallisation is a fundamental process ubiquitous in nature and of high industrial importance. This phase transition from a liquid to a solid often occurs via nucleation and growth, but not always into the same crystalline form, a phenomenon known as polymorphism. The mechanism through which polymorphs are ‘selected’ is currently not understood. This project investigates the nucleation and polymorphism of the amino acid glycine with Molecular Dynamics simulation and in particular transition path sampling. Glycine is an ideal system due to its relative simplicity, and because it exhibits three unique crystal compositions at ambient conditions. Better understanding of the polymorph selection mechanism could lead to improved control of crystallization, which has important applications in Material Science and Medicine.


Investigating vibrational properties of PAHs using Artificial Neural Networks
Polycyclic Aromatic Hydrocarbons (PAHs) are molecules of great astronomical interests. In this project, we aim to predict anharmonic vibrational spectra for astronomical polycyclic aromatic hydrocarbons (PAHs) using artificial neural networks.