Collaborative Research: Mesoscale Analysis of Transport and Degradation in Electrochemical Systems

随着社会向更多的可再生能源生产和电动运输方式过渡，用于能量转换和储存的电化学系统将发挥越来越大的作用。为了使这些系统经济，耐久性是关键驱动因素；需要数学模型来帮助确定影响系统耐久性的关键因素。准确地说，描述过程必须接近分子水平，并具有良好的时间分辨率。然而，电化学装置的物理尺寸可能很大，寿命可能会延长数年。通过这项研究，预测这些系统的长期行为是通过开发新的方法和建模技术来完成的，这些方法和建模技术跨越了时间和空间尺度。本项目以质子交换膜(PEM)燃料电池的研究为例，考察了阴极的性能。阴极是燃料电池的关键部件，它会导致电池性能随着时间的推移而下降。本项目将开发的建模工具将允许研究电极中的化学反应和物理材料变化以及如何减轻它们的影响。这一合作研究项目还有助于在多学科研究环境中对研究生和本科生进行教育和培训。计算模型和数据将通过开源的拓扑结构提供给科学界，从而促进科学的快速发展。这项工作的主要目标是开发方法来跨越不同的时间和长度尺度，以便能够基于详细的物理模型对电化学能量系统的长期退化行为进行高效的计算模拟。这项工作建立在已经收集的新数据的基础上，这些数据显示了质子交换膜燃料电池中电极在老化后微结构的演变，作为电化学能源系统的典范。发展了介观模拟方法来模拟电化学反应，耦合物质和电荷输运以及两相流动。将建立一个广义时空尺度-桥梁框架，以便能够有效地模拟中尺度基础，并与退化的微观结构数据保持一致。这一框架有可能改变这些能源系统的设计和运营方式。这项研究通过开发新的方法和规模桥接建模技术来预测电化学能源系统的长期行为，广泛地针对这一挑战。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

As society transitions towards greater renewable energy production and electric modes of transportation, electrochemical systems for energy conversion and storage are poised to play an ever-greater role. In order for these systems to be economical, durability is the key driver; and mathematical models are needed to help determine the key factors that impact system durability. To be accurate, processes must be described close to the molecular level and with fine temporal resolution. Yet, the electrochemical devices can be physically large and have lifetimes that may extend for years. Through this research, predicting the long-term behavior of these systems is accomplished by developing novel methodologies and modeling techniques that bridge the temporal and spatial scales. This project uses as an example, the study of a proton exchange membrane (PEM) fuel cell and looks at the performance of the cathode. The cathode is a key component of the fuel cell that contributes to its degradation in performance over time. The modeling tools that will be developed in this project will allow the study of both the chemical reactions and physical material changes in the electrode and how to mitigate their impacts. This collaborative research project also contributes to the education and training of both graduate and undergraduate students within a multidisciplinary research environment. The computational models and data will be made available to the scientific community through an open-source topology, thus promoting rapid progress of science.The principal objective of this work is to develop methodologies to bridge disparate time and length scales to allow computationally efficient simulations of the long-term degradation behavior of electrochemical energy systems based on detailed physical models. The work builds upon new data that have been collected showing the evolution of microstructure in electrodes subject to ageing in proton exchange membrane fuel cells as an exemplar electrochemical energy system. Mesoscale modeling approaches are developed to simulate electrochemical reaction coupled species and charge transport and two-phase flow. A generalized spatio-temporal scale-bridging framework will be created to allow efficient simulation of the mesoscale underpinnings and to align with the microstructural data of the degradation. This framework has the potential to transform the way that these energy systems are designed and operated. The research broadly targets this challenge by developing novel methodologies and scale-bridging modeling techniques to predict long-term behavior of electrochemical energy systemsThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.