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sustainable catalyst platforms. This PhD project, Data-enhanced Quantum Chemistry for Predictive Catalyst Design, aims to Develop computational approaches for the discovery of sustainable catalysts based on low
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shifts (technology adoption and peat replacement) represent major changes to mushroom production. There is a need to evaluate the competitiveness, sustainability and resilience of high-tech, low-peat
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greenhouse gas emissions whilst reducing pressure on water quality and biodiversity associated with livestock farming. Cascading use of grass can deliver low-emission feed, food, energy, material and
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deliver a compact, low-power, wearable iNIRS platform for multi-biomarker sensing, with a clinical demonstration planned in neonatal intensive care units. This PhD will develop the light engine