Applying computational chemistry to the study of proton exchange membranes/ Étude par modélisation moléculaire de membranes échangeuses de protons

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Polymer electrolyte membrane fuel cells (PEMFC's) are the primary system being developed for use in automotive applications. Nevertheless, some improvements have to be achieved to make fuel cells economically competitive with other alternative solutions, such as high performance diesel, or hybrid vehicles. In this proposal, a hierarchical series of computational chemistry methods is used to solve the high-temperature low-humidity performance problems of proton exchange membranes (PEM). The procedure is intended to capture the insight of molecular behaviour through the intimately link between data stemming from the different computation chemistry methods, and the experimental results. A molecular level understanding of the physical mechanisms controlling PEM performance should thus help advance their development and therefore improve the final efficiency of fuel cells. The purpose of this primary phase is to clarify the factors governing the scale of phase segregation and self-organization in Nafion®, the actual benchmark polymer for membranes used in PEMFC, by comparing the calculated mesoscale morphology to its experimentally determined structure. These features will provide the basis for an initial evaluation of the accuracy of the proposed methodology.  The next focus is to apply the methods developed during the Nafion® work to newly synthesized block copolymer PEMs currently being developed by GM.  The proposed calculations on these block copolymers are intended to complement and provide context to GM's existing and planned experimental program on these membranes. Guidance on improving membrane synthesis is also anticipated from such comparisons.  The final goal is a fully developed methodology that can predict changes in the stability of the structural phases of both random and block copolymer ionomers based on the chemical composition, length of the component blocks, and polydispersity. Leveraging of experimental results in an iterative process between computational theory and experiment is viewed as essential component for making substantial progress. This interchange is central to the current collaboration between Université de Sherbrooke and GM Canada Limited.