Sodium-ion Batteries
Developing accurate physics-based models for a promising low-cost alternative to lithium-ion technology.
Sodium-ion batteries are a promising, low-cost alternative to lithium-ion technology, but the complex mechanisms governing sodium-ion transport and storage are not fully captured by existing simulation tools.
This work package presents research on sodium-ion battery parameterisation and physics-based electrochemical modelling, with a focus on developing continuum-scale models of how sodium moves through and is stored within battery electrodes.
The work captures the distinctive storage behaviour of key electrode materials such as hard carbon and layered oxides, while integrating experimentally derived parameters into validated predictive frameworks.
By providing methodologies, experimentally derived parameterisation datasets, and modelling resources, the platform supports reproducible research and advances the development of accurate electrochemical models for sodium-ion batteries, benefiting researchers, engineers, and students.
Li-metal, Solid-state & Anode-free
Multi-scale models for lithium-metal interfaces, solid-state electrolytes and next-generation cell architectures.
Develop multi-scale models for mechanistic understanding of lithium metal anode and electrolyte interface. Integrate electrochemical and mechanical models to capture SEI evolution, lithium transport, dendrite formation, and interfacial degradation.
Advance these approaches to solid-state electrolyte systems using physics-based modelling to improve safety, performance, and cycle life.
Multi-scale interface and dendrite modelling
Phase-Change Materials
Next-generation mathematical models for electrode materials undergoing major structural and chemical changes.
Work package 8 is developing and validating new mathematical models for lithium-ion battery electrode materials that undergo significant structural and/or chemical changes during operation.
These materials, including lithium iron phosphate (LFP), lithium manganese iron phosphate (LMFP) and silicon, each present unique modelling challenges that cannot be met by the ubiquitous Doyle-Fuller-Newman (DFN) model.
By combining physics-based modelling with experimental validation, the team is developing next-generation models that capture the underlying physical processes more faithfully than conventional approaches.
These models improve our understanding of phase-changing electrode materials and provide a stronger foundation for the design and development of future battery technologies.
