About the project
Proton-exchange Membrane (PEM) hydrogen fuel cells are an emerging technology for environmentally sustainable transport and other carbon-neutral energy applications. A crucial component of these devices are the metallic catalyst nanoparticles which allow the chemical reactions to take place at fast rates.
The aim of this PhD is to use cutting-edge quantum (DFT, DFTB) and classical (machine learnt force fields) atomistic simulations of nanoparticles of relevant size, composition and support, to develop advanced models to optimise the rate determining steps of the operation of hydrogen fuel cells. You will use new developments in the ONETEP linear-scaling DFT code to include the environment of solvent, electrolyte and constant potential which will allow to do simulations under electrochemical conditions.
This will allow to simulate the adsorption and reactions on the supported catalyst nanoparticle under different degrees of oxidation and applied voltage, the charge of the electrode and the nature of the electrolyte double layer that is formed under different conditions, with atomic resolution.
The ultimate goal of this research strand is to build a digital twin of a hydrogen fuel cell. While the focus of this PhD project will be on fuel cells the developed models will be transferable to other electrochemical systems such as electrolysers.
This is a ICASE PhD studentship that involves collaboration with our industrial partner Johnson Matthey, who will provide guidance towards the most relevant models and materials to simulate, and periods of placement at their premises.
