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Informatics-Driven Selection of Polymers for Fuel-Cell Applications

Huan TranKuan-Hsuan ShenShivank ShuklaHa-Kyung KwonRampi Ramprasad
Dec 2022
摘要
Modern fuel cell technologies use Nafion as the material of choice for theproton exchange membrane (PEM) and as the binding material (ionomer), used toassemble the catalyst layers of the anode and cathode. These applicationsdemand high proton conductivity as well as other requirements. For example, PEMis expected to block electrons, oxygen, and hydrogen from penetrating anddiffusing while the anode/cathode ionomer should allow hydrogen/oxygen to moveeasily, so that they can reach the catalyst nanoparticles. Given some of thewell-known limits of Nafion, such as low glass-transition temperature, thecommunity is in the midst of an active search for Nafion replacements. In thiswork, we present an informatics-based scheme to search large polymer chemicalspaces, which includes establishing a list of properties needed for thetargeted applications, developing predictive machine-learning models for theseproperties, defining a search space, and using the developed models to screenthe search space. Using the scheme, we have identified 60 new polymercandidates for PEM, anode ionomer, and cathode ionomer that we hope will beadvanced to the next step, i.e., validating the designs through synthesis andtesting. The proposed informatics scheme is generic, and can be used to selectpolymers for multiple applications in the future.
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