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Field
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, it is crucial to evaluate whether increasing broadleaf stands effectively enhances biodiversity and how these effects vary with landscape context. Additionally, the interaction of forest composition
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catalytic metals. These clusters will be deposited with high control over size and composition using cluster beam deposition on morphologically engineered TiO2 nanotubes. The most efficient catalysts will be
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biodiversity and how these effects vary with landscape context. Additionally, the interaction of forest composition at stand and landscape scales in shaping species communities is not well understood. Advances
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-metallic clusters that combine plasmonic and catalytic metals These clusters will be deposited with high control over size and composition using cluster beam deposition on morphologically engineered TiO2
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fail to reach those most in need. To develop equitable and effective policy tools, further research is needed on the contexts, compositions, and mechanisms of retrofits, as well as a deeper understanding
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on the contexts, compositions, and mechanisms of retrofits, as well as a deeper understanding of the barriers preventing vulnerable communities from taking action. This PhD project proposes “grassroots retrofitting
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manufacturing (year 1) - Advanced Composites manufacturing using energy absorbing fibres and nanomaterials (year 1) - Analytical/mathematical modelling and FEA modelling of hyper-velocity impact test of
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the potential to accelerate materials design and optimization. By leveraging large datasets and complex algorithms, ML models can uncover intricate relationships between composition, processing parameters, and
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management platform that connects institutes to facilitate a rapid and efficient exchange among experimental and computational groups Devising an approach in invertible predictive modeling that links
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models considering networks of patches and their species and interactions composition to predict spatial and temporal community structure across restoration gradients, aimed at developing a predictive