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OPERA - DEVELOPMENT OF OPERANDO TECHNIQUES AND MULTISCALE MODELLING TO FACE THE ZERO-EXCESS SOLID-STATE BATTERY CHALLENGE

OPERA - DEVELOPMENT OF OPERANDO TECHNIQUES AND MULTISCALE MODELLING TO FACE THE ZERO-EXCESS SOLID-STATE BATTERY CHALLENGE
OPERA - 开发操作技术和多尺度建模以应对零过剩固态电池挑战
批准号:
10078555
负责人:
金额:
$62.75万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
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英文摘要
Green, high-performing and safe batteries based on abundant materials are a key element in the transition to a carbon-neutral future. However, to accelerate their development, a deep understanding of the complex electro-chemo-mechanical processes within the battery is required, which is only accessible through advanced experimental and computational methods. Zero-excess solid-state batteries, where the anode is formed in situ, have emerged as a promising new generation of environmentally friendly batteries with high energy density, improved safety and higher cost-efficiency, but only after solutions for non-uniform anode formation were found. In OPERA, seven leading research institutions, two synchrotron radiation facilities, a small-medium sized enterprise and a large technological company, all from complementary research fields such as batteries, surface and material science, and multiscale modelling, propose a unique strategy to face the current challenges of this technology. OPERA relies on the development of novel operando experimental techniques at the ESRF, ALBA and DESY synchrotrons and at the lab-scale, providing complementary information on multiaxial stress fields, chemical composition, nucleation and growth kinetics, structural defect formation and degradation of well-defined model cells with a resolution down to the atomic scale. The new insights and collected multiparameter data will be incorporated into a novel multiscale modelling approach supported by machine learning algorithms. This will ultimately lead to a conceptual understanding of the in-situ anode formation and, based on this, innovative improvement approaches to enable this type of energy storage technology, which will be an important step towards increasing the global competitiveness, resilience and independence of the EU.
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海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: