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，就必须在正在发生的反应的基础科学上进行大量投资。这项提议的目的是确定详细的原子机理，包括PEM燃料电池阴极氧还原反应的自由能垒。重点放在机理和速率如何依赖于合金成分、表面和主体区域之间的分布以及溶剂。通过预测二元和三元催化剂将如何提高选择性、速率和寿命来检验计算结果。此外，加州理工学院材料和工艺模拟中心的PI威廉·A·戈达德三世鲍里斯·梅里诺夫建议确定催化剂降解的机理及其与合金成分的关系。其结果是得到一个足够准确的计算模型，对指导实验和工程应用都是有用的。在此之前，还没有一种实用的方法来将如此广泛的反应现象仅基于第一原理进行耦合。这一新方法将根据基本原理预测工程模型的数据，允许通过计算设计新系统，然后针对实验进行测试。为了能够进行这种模型测试，已经安排了与Argonne National Labs和Ford Science Labs的合作，对预测最有希望的合金进行实验。这个模型应该有助于开发准确的工程模型，从理论和模拟中获得信息，但进行调整以结合实验结果。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的合金能够达到当前改进燃料电池的目标。改进的催化剂(更高效、寿命更长)的开发应该会加快高效燃料电池的开发，这些燃料电池在商业上是可行的，用于运输、能源生产和储存，并由此产生环境影响。在更广泛的意义上，除了对燃料电池阴极用改进的合金催化剂的开发做出重大贡献外，包括通过ReaxFF反应动力学的QM在内的计算工具的成功耦合到催化剂/载体系统的模拟将适用于催化剂、材料和能源方面的其他问题。

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.