Mechanisms and Rates for Improved Fuel Cell Cathode Catalysts and Supports from First Principles Based Methods

如果要在最终克服PEM燃料电池的技术和成本限制方面取得进展，就必须对所发生的反应的基础科学进行重大投资。本提案的目的是确定PEM燃料电池阴极上氧还原反应的详细原子机制，包括自由能垒。重点是机制和速率如何取决于合金成分，表面和大块区域之间的分布，以及溶剂。计算结果将通过预测二元和三元催化剂如何提高选择性、速率和寿命来检验。此外，来自加州理工学院材料与工艺模拟中心的pi William A. Goddard III Boris Merinov建议确定催化剂降解的机制以及它们如何依赖于合金成分。结果是得到一个足够精确的计算模型，可用于指导实验和工程应用。以前还没有一种实用的方法可以仅仅基于第一性原理来耦合如此广泛的反应现象。这种新颖的方法将从第一性原理预测工程模型的数据，允许新系统进行计算设计，然后进行实验测试。为了实现这种模型测试，已经与阿贡国家实验室和福特科学实验室安排了合作，对那些被预测最有前途的合金进行实验。该模型应有助于从理论和模拟中获得准确的工程模型的发展，但应调整以纳入实验结果。这种方法对于开发改进的材料和工艺至关重要，这些材料和工艺需要使新合金能够满足改进燃料电池的当前目标。改进的催化剂（效率更高、寿命更长）的发展将加速高效燃料电池的发展，这种燃料电池将在商业上可行，用于运输、能源生产和储存，从而对环境产生影响。从更广泛的意义上说，除了对燃料电池阴极的改进合金催化剂的发展做出重大贡献外，通过ReaxFF反应动力学将包括QM在内的计算工具成功地耦合到催化剂/支撑系统的模拟中，将适用于催化剂、材料和能源的其他问题。

If progress is to be made at ultimately overcoming the technical and cost limitations of PEM fuel cells, a significant investment in the fundamental science of the reactions taking place must be made. The objective for this proposal is to determine the detailed atomistic mechanism including free energy barriers for the oxygen reduction reaction at PEM fuel cell cathodes. The focus is on how the mechanism and rates depend on alloy composition, distribution between surface and bulk regions, and solvent. The computational results would be tested by predicting how binary and ternary catalysts would be expected to improve selectivity, rates, and lifetime. In addition, the PIs, William A. Goddard III Boris Merinov, both of the Materials and Process Simulation Center at California Institute of Technology, propose to determine mechanisms of catalyst degradation and how they depend on alloy composition. The result is to be a computational model sufficiently accurate to be useful in guiding both experiments and engineering applications. There has previously been no practical means to couple such a wide range of reactive phenomena based solely on first principles. This novel approach would predict data for engineering models from first principles, allowing new systems to be designed computationally and then tested against experiment. To enable this model testing, collaborations have been arranged with Argonne National Labs and with Ford Scientific Labs to carry out experiments on those alloys predicted to be most promising. This model should aid the development of accurate engineering models informed from the theory and simulations but adjusted to incorporate results from experiments. This approach will be essential to develop the improved materials and processes needed to enable new alloys to meet the current targets for improved fuel cells. The development of improved catalysts (more efficient, longer-lived) should accelerate development of efficient fuel cells that would be commercially viable for transportation, energy production and storage, with the resultant environmental impact. In the broader sense, in addition to contributing significantly to the development of improved alloy catalysts for fuel cell cathodes, the successful coupling of computational tools including QM through ReaxFF reactive dynamics to simulation of the catalyst/support system would apply to other problems in catalysts, materials, and energy.