Ultra-low loading Pt electrocatalysts based on carbon support alloys for oxygen reduction in hydrogen fuel cells and their lifetime prediction

阴极上的氧还原反应（ORR）是燃料电池的核心电化学过程。四电子转移ORR是有利的，它涉及O=O键的裂解和OH*或OOH*物质的形成。反应动力学趋于缓慢，通常需要高过电位，这显著影响能量转换效率。四电子转移ORR的基准电催化剂绝大多数依赖于贵金属材料，因为它们具有优异的催化活性，即20~ 40%铂（Pt）在燃料电池阴极的碳材料上。然而，Pt材料的高成本和耐久性问题阻碍了它们的大规模应用。此外，目前对ORR催化剂的评价需要进行长期稳定性试验和材料稳定性分析，这占用了大量的精力和时间。开发合适的电催化剂和燃料电池寿命预测程序对于进一步降低设备成本具有重要意义。本项目旨在开发低成本和可持续的材料框架，项目分为三个阶段：第一阶段材料制备：采用自下而上的策略，通过湿化学和固态退火相结合的工艺制备改性碳材料。单碳前体的混合物，包括单宁酸、葡萄糖、马铃薯淀粉和聚乙二醇（这些前体具有丰富的氧官能团，最初会形成交联产物和氧官能团结构）。不同的过渡金属盐（Co, Fe， Ni等）和Pt前驱体的减少量将涉及。在还原气氛下退火后，在多孔碳载体上形成合金团簇。此外，非金属原子将参与进一步优化电子导电性和合金与碳载体之间的相互作用，如氮或磷进入框架。材料的均匀性、物相和结构可以系统地调整。广泛的材料表征技术将被采用，如扫描（透射）电子显微镜，x射线衍射和BET表面积评估。阶段2)电化学评价和燃料电池制造。ORR的性能将在三电极配置下进行测试。工作电极将通过将电催化剂混合物涂覆在旋转圆盘电极（RDE，玻碳盘）或旋转环盘电极（RRDE，带Au/Pt环的玻碳盘）上来制备。将评价所制备的电催化剂的动力学行为和稳定性，并与商业Pt/C材料进行比较。电化学阻抗谱将用于了解固有电阻。燃料电池的制造和测试将通过与Bramble能源有限公司和DB集团的合作进行。该学生将与SJ和GH的团队合作，了解电催化剂的机理，并根据电化学性能的初步评估开发合适的机器学习算法来预测电催化剂的寿命。原位光谱和层析成像研究，如化学学院的原位电化学拉曼光谱，将进一步指导新材料的开发。

The oxygen reduction reaction (ORR) on the cathode is a core electrochemical process in fuel cells. A four-electron transfer ORR is favourable, which involves the cleavage of O=O bonds and the formation of OH* or OOH* species. The reaction kinetics tend to be sluggish, and normally require high overpotentials which significantly affect the energy conversion efficiency. The benchmark electrocatalysts for four-electron transfer ORR overwhelmingly rely on noble metal materials owing to their excellent catalytic activities, i.e. 20~40 % platinum (Pt) on carbon materials for cathodes in fuel cells. However, the high cost and durability issues of Pt materials hinder their large-scale application. In addition, the current evaluation of ORR catalysts needs the long-term stability test and materials stability analysis, which occupy a large amount of the effort and time. Developing suitable programme for lifetime prediction of the electrocatalysts and fuel cells are important for further reducing the device cost.This project aims at developing low-cost and sustainable materials, frameworks and the project is divided into three stages:Stage 1) Materials preparation: The bottom-up strategy will be used to prepare the modified carbon materials via combined wet chemistry and solid-state annealing processes. The mixture of a single-carbon precursor, including tannic acid, glucose, potato starch and polyethylene glycol (these precursors have rich oxygen functional groups and will form cross-linking products and oxygen functionalised structure initially. Different transition metal salts (Co, Fe, Ni, etc.) and reduced amount of the Pt precursor will be involved. After annealing under a reductive atmosphere, the alloy clusters will be formed on the porous carbon supports. Furthermore, non-metal atoms will be involved to further optimise the electronic conductivity and the interaction among alloys and carbon supports, such as the nitrogen or phosphorus into the frameworks. The uniformity, phases and structures of the materials can be adjusted systematically. A broad range of materials characterisation techniques will be adopted, such as scanning (transmission) electron microscopy, X-ray diffraction and BET surface area evaluation.Stage 2) Electrochemical evaluation and fuel cells fabrication The ORR performance will be tested in a three-electrode configuration. The working electrode will be prepared by coating electrocatalyst mixtures onto a rotating disk electrode (RDE, glassy carbon disk) or a rotating ring disk electrode (RRDE, glassy carbon disk with Au/Pt ring). Kinetic behaviours and the stability of as-prepared electrocatalysts will be evaluated and compared with the commercial Pt/C materials. Electrochemical impedance spectroscopy will be used to understand the inherent resistance. The fuel cell fabrication and testing will be conducted via the collaboration with Bramble Energy ltd. and DB's group.Stage 3) Mechanism study and lifetime estimation The student will work with SJ and GH's group to understand the mechanism of electrocatalysts and develop suitable machine learning algorithms to predict the lifetime of the electrocatalysts according to the initial evaluation of the electrochemical performance. In-situ spectroscopic and tomography study, such as in-situ electrochemical Raman spectroscopy from the School of Chemistry will be used further guide the development of new materials.