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

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键的断裂和OH*或OOH*物种的形成。反应动力学趋于迟缓，通常需要很高的过电位，这对能量转换效率有显著影响。用于四电子转移ORR的基准电催化剂大多依赖于贵金属材料，即燃料电池阴极用碳材料上20~40%的铂(PT)。然而，铂材料的高成本和耐久性问题阻碍了其大规模应用。另外，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，耗费大量的精力和时间。开发合适的电催化剂和燃料电池寿命预测程序对进一步降低器件成本具有重要意义。本项目旨在开发低成本和可持续发展的材料框架，该项目分为三个阶段：阶段1)材料准备：将采用自下而上的策略，通过湿化学和固态退火法相结合的方法制备改性碳材料。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含氧官能团，最初将形成交联物和含氧官能化结构。不同的过渡金属盐(钴、铁、镍等)并减少了铂前驱体的量。在还原气氛下热处理后，在多孔炭载体上会形成合金团簇。此外，还将涉及非金属原子，以进一步优化电子传导性和合金与碳载体之间的相互作用，如进入骨架的氮或磷。材料的均匀性、物相和结构均可进行系统的调节。将采用广泛的材料表征技术，如扫描(透射式)电子显微镜、X射线衍射和BET表面积评估。阶段2)电化学评估和燃料电池制造将在三电极配置中测试ORR性能。工作电极将通过将电催化剂混合物涂覆到旋转圆盘电极(RDE，玻璃碳盘)或旋转环盘电极(RRDE，带Au/Pt环的玻璃碳盘)上来制备。对所制备的电催化剂的动力学行为和稳定性进行了评价，并与商用的铂/碳材料进行了比较。电化学阻抗谱将被用来理解固有电阻。燃料电池的制造和测试将通过与Bramble Energy Ltd.的合作进行。3)机理研究和寿命估算学生将与SJ和GH的团队合作，了解电催化剂的机理，并根据对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.