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

建立一个充足、持久、无排放和环境友好的能源体系是全球能源议程的首要任务。在这些全球努力中，材料设计和电化学在提供替代能源解决方案方面发挥着核心作用。可再生氢，特别是电解生产的氢，是能源系统高效脱碳最有前途的方法之一。它还代表着一种安全、可持续的能源。RECIFE项目旨在通过结合材料建模、机器学习和先进的设计和表征概念，开发和构建一类基于非贵金属过渡金属（TM）和聚合物衍生陶瓷的新型水分解电极材料。两家法国研究所和一家德国研究所之间的合作，各自具有互补的专业知识，应该会导致电极超过传统产品的催化活性和耐用性，并使开发强大的下一代OER电解催化剂成为可能。特别注意的是纳米复合材料的设计，特别为计划的应用开发，它由易接近的，纳米级的，非贵重的，活跃的过渡金属颗粒组成，分散在陶瓷基体中。这些纳米复合材料必须具有催化活性、特定表面以及适当的导电性和耐化学性，这是析氧反应（OER）所需要的。计划中的RECIFE项目首次结合了(1)“第一原理”模型的准确性(2)利用计算机数据作为人工智能预测材料性能的来源(3)基于“深度学习”原理对合成电极材料的结构性能进行实验表征，(4)以机器学习和“第一原理”模型为支持的实验合成，(5)适应制造方法，使电极的规模扩大。包含建模的工作包有望在原子水平上提供对陶瓷材料结构的重要见解，以及对裸纳米复合材料和水合纳米复合材料电极上发生的OER机制和电化学过程的微观见解。该项目的实验部分侧重于开发最佳过渡金属修饰的陶瓷纳米复合电极的合成、优化和设计方案。

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.