Systems engineering for energy production: optimizing catalysts, models and systems

催化剂是能源技术的重要组成部分，开发改进的催化剂可以通过提高关键反应的活性来显着改善燃料电池系统的性能。在这项工作中，我们寻求开发方法来优化催化剂使用详细的模型。这将是对目前做法的改进，目前的做法涉及试错实验。我们开发的模型是多尺度的，并考虑到在电子，分子和反应器尺度的影响。这使我们能够在预测催化剂性质对反应速率和选择性的影响时考虑所有相关现象。在这项工作中，我们开发的方法，通过进行明智的实验，以提高这些模型的预测能力。然后，我们使用模型描述的关系，以确定导致最佳反应行为的催化性能。找到最佳催化剂的特性后，我们确定了显示这些特性的多金属催化剂（合金）。我们还使用多尺度模型来优化反应器设计。

Catalysis is an important component of energy technologies, and the development of improved catalysts can dramatically improve the performance of fuel cell systems by increasing the activity of crucial reactions. In this work, we seek to develop methods to optimize catalysts using detailed models. This will be an improvement on current practice, which involves trial-and-error experimentation. The models we develop are multiscale, and take into account effects at the electronic, molecular and reactor scales. This enables us to account for all relevant phenomena in predicting the effect of catalyst properties on reaction rates and selectivity. In this work, we develop methods, by conducting judicious experiments, to improve the predictive power of these models. We then use the relationships described by the models to identify the catalytic properties that lead to the optimal reaction behavior. Having found the properties of the optimal catalyst, we then identify multimetallic catalysts (alloys) that display these properties. We also use the multiscale models to optimize reactor design.