Informatics-Driven Selection of Polymers for Fuel-Cell Applications

Modern fuel cell technologies use Nafion as the material of choice for proton exchange membrane (PEM) and binding (ionomer), used to assemble catalyst layers anode cathode. These applications demand high conductivity well other requirements. For example, PEM is expected block electrons, oxygen, hydrogen from penetrating diffusing while anode/cathode ionomer should allow hydrogen/oxygen move easily, so that they can reach nanoparticles. Given some well-known limits Nafion, such low glass-transition temperature, community in midst an active search replacements. In this work, we present informatics-based scheme large polymer chemical spaces, which includes establishing a list properties needed targeted applications, developing predictive machine-learning models these properties, defining space, using developed screen space. Using scheme, have identified 60 new candidates PEM, ionomer, cathode hope will be advanced next step, i.e., validating designs through synthesis testing. The proposed informatics generic, select polymers multiple future.