Material discovery and modelling for solid-state hydrogen storage and fuel cell applications - Wakerley, James Kenneth Malcolm (2023)
This thesis covers an attempt to construct a supervised machine learning model, for use in prediction of formation enthalpy values for novel metal hydride compositions. Further work, making use of static density functional theory calculations as well as ab initio and machine learning force field molecular dynamics simulations, to model oxygen transport in a La-Mg co-doped barium titanate system is also reported.