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Optimizing a 3D microfluidic IVD model to study cell responses to wear particles, refining culture conditions, and analysing cytotoxic and inflammatory mechanisms. Optimizing a 3D microfluidic IVD
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inorganic AEMWEs by integrating the perovskite electrolyte with perovskite electrodes from cell fabrication to cell configuration optimization and to single cell performance. Significance The project has
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alternative to lithium-ion battery. The PhD research will address challenges in proton battery research and improve energy density, fast charging and discharging capability, stability and low
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development, tissue regeneration, and stem cell maintenance. Unregulated activation can lead to various illnesses, including immunological dysregulation, infections, and the development and advancement
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mechanisms involved in the leaching of copper concentrate by glycine solutions. • Optimize process parameters such as temperature, pH, glycine concentration, and particle size to maximize copper
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to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic
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of magnetocaloric materials for hydrogen liquefaction. This cutting-edge research aims to enhance the efficiency of hydrogen liquefaction processes, a crucial step in the future of clean energy. This opportunity is
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through objective assessment of disease activity and selection of the most optimal medical therapy. Predictors of response to the current arsenal of treatment are paramount to achieve endoscopic and
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Research Hub for Carbon Utilisation and Recycling, which is established in 2023 with one of the aims is to develop technologies to transform carbon dioxide emissions from our energy and manufacturing sectors