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Rational design concepts of Engineered Ceramics with Integrated catalytically active metal sites for electrochemical Energy conversion

Rational design concepts of Engineered Ceramics with Integrated catalytically active metal sites for electrochemical Energy conversion
用于电化学能量转换的具有集成催化活性金属位点的工程陶瓷的合理设计理念
批准号:
490841897
负责人:
Dr. Günter Motz
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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英文摘要
Achieving a sufficient, permanent, emission-free and environmentally friendly energy system is a top priority for the global energy agenda. In these global efforts, material design and electrochemistry play a central role in offering alternative energy solutions. Renewable hydrogen, in particular, produced by electrolysis, is one of the most promising approaches for efficient decarbonization of the energy system. It also represents a safe and sustainable source of energy. The RECIFE project aims to develop and construct a new class of water-splitting electrode materials based on non-noble transition metals (TM) and polymer-derived ceramics by combining material modeling, machine learning and advanced design and characterization concepts. The collaboration between two French and one German institute, each with complementary expertise, should lead to electrodes that exceed the catalytic activity and durability of conventional products and enable the development of powerful next-generation OER electrolysis catalysts. Particular attention is paid to the design of the nanocomposites, specially developed for the planned application, which consist of accessible, nano-scale, non-noble, active transition metal particles that are dispersed in a ceramic matrix. These nanocomposites must have a catalytically active, specific surface as well as an appropriate electrical conductivity and chemical resistance, as required for the oxygen evolution reactions (OER). The planned RECIFE project combines for the first time (1) the accuracy of the "first principle" models (2) the use of computer data as a source for the prediction of material properties by artificial intelligence (3) an experimental characterization of the structural properties of the synthesized electrode materials based on the "deep learning" principle, (4) the experimental synthesis, supported by machine learning and "first-principle" models, and (5) the adaptation of the manufacturing methods to enable up-scaling of electrodes. The work packages that contain the modeling are expected to provide important insights into the structure of the ceramic materials at the atomic level, as well as a microscopic insight into the OER mechanisms and the electrochemical processes taking place on the bare and hydrated nanocomposite electrodes. The experimental part of the proposed project focuses on the development of protocols for the synthesis, optimization and design of optimal, transition metal-modified, ceramic nanocomposite electrodes.
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