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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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levels of Cu, Mo, Ni & Sn. Direct comparisons will be made with experimentally identified phases from high throughput samples. Subsequent characterisation will be performed using a combination of scanning
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