Bridging Models at Different Scales To Design New Generation Fuel Cells for Electrified Mobility (BLESSED)
Bridging Models at Different Scales To Design New Generation Fuel Cells for Electrified Mobility (BLESSED)
批准号:
EP/X032264/1
负责人:
Rune Lindstedt
金额:
$50.7万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
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英文摘要
To achieve the goals of the European Green Deal on climate neutrality, a 90% reduction in transport emissions is needed by 2050. The automotive industry urgently needs to accelerate the introduction of alternative powertrains for electrified vehicles. Hydrogenpowered Proton Exchange Membrane Fuel Cells (PEMFCs) are carbon-free power devices that meet these goals in both mobile and stationary applications. BLESSED aims at revolutionising the design process of next generation PEMFCs, to improve efficiency, durability and affordability for widespread use, with direct implications in clean energy and sustainable industry/mobility. BLESSED will train 15 Doctoral Candidates (DCs) to solve Multi-Scale (MS) engineering challenges, from the electrons up to the device level, through a unique combination of multi-disciplinary computational methods with Machine Learning (ML) to bridge each length scale's highly accurate model to adjacent scales. Then, a top-down length scale approach will be followed to optimise PEMFC and its components. To this end, the 15 DCs will synergistically develop a unique MS computational framework for the all-scale PEMFC analysis/design, assisted by ML tools. This will allow the simultaneous consideration of complex physico-chemical phenomena occurring at all length scales, such as catalytically-assisted chemical reactions, contact of rough surfaces, mechanical/chemicaldegradation of membranes, fluid flows in porous media etc., at affordable computational cost. The proposed ID-network brings together world-class academic expertise on numerical modelling and simulation in electrochemistry, reacting flows, fluid mechanics, materials, optimisation methods and ML, with industrial developers. With a strong focus on industrial applications, BLESSED will develop methodologies and tools to exceed state-of-the-art in PEMFCs by minimising the Platinum group metal content and corrosion while maximising mass transport and electrical conductivity.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位:
新型手性NAD(P)H Models合成及生化模拟
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批准号:20472090
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项目类别:面上项目
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资助金额:23.0万元
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批准年份:2004
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负责人:王乃兴
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依托单位: