Material discovery and modelling for solid-state hydrogen storage and fuel cell applications
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 mol...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2023
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| Online Access: | https://eprints.nottingham.ac.uk/73082/ |