A diagram of the transition of water (left) to ice (right) made by the ICE group.
A PhD thesis from the Professor Angelos Michaelides’ ICE group was awarded this year’s 2023 Institute of Physics Computational Physics Group Thesis Prize.
As a PhD student, Dr Michael Davies was a member of both the University of Cambridge and University College London. His thesis was titled Solving mysteries of ice formation with simulation and data-driven methods, applied molecular dynamics simulations and machine learning techniques to understand ice formation at the molecular level.
Michael wrote for the Institute of Physics: "At first glance, the formation of ice might seem a mundane everyday phenomenon but its impacts are vast, ranging from glaciers, to cryopreservation, to climate modelling. Its formation is perplexing: in its pure state water must be cooled to around -40 °C for ice to form and a foreign material is almost always required."
To understand how materials control ice formation, Michael used high-throughput computational simulations in combination with deep learning. The work uncovered a path to an elusive “cubic ice” polymorph and produced an AI model that beat experts from across the globe in an open head-to-head challenge despite 80 years of human endeavour.
Michael also investigated the formation of “amorphous ice”, which is believed to be the most common form of water in the universe. In collaboration with experiment, he discovered a new form of amorphous ice with the same density as liquid water. The discovery raises questions about the very nature of liquid water.
Michael currently works as a data scientist at Faculty, working at the forefront of applying AI to real life.