Durable Mn-based PGM-Free Catalysts for Polymer Electrolyte Membrane Fuel Cells

Recipient Giner, Inc (PI: Xu, Hui)

Subs Prof. Gang Wu (University at Buffalo, the State University of New York), Prof. Guofeng Wang (University of Pittsburgh), Dr. Anusorn Kongkanand (General Motors Company)

Abstract Polymer electrolyte membrane fuel cell (PEMFC) is a technology to generate electricity through efficient electrochemical conversion of hydrogen and oxygen into environmentally benign water. Hence, it is of great economic and societal benefits to apply PEMFC in automotive transportation. The objective of this proposed project is to develop low- cost, high-performance, and durable electrocatalysts, which currently is a major challenge in advancing PEMFC technology. This proposed project aims to develop and evaluate novel manganese based, nitrogen-derived, PGM-free electrocatalysts (denoted as Mn-N-C) to fully address the membrane electrolyte assemblies (MEA)’s ionomer degradation issue resulting from iron. Four thrusts will be pursed in this proposed project. First, advanced first-principles computation methods will be employed to accelerate the rational catalyst design and synthesis. Second, an effective hydro-gel method will be used to maximize atomic Mn active sites embedded in carbon matrix. Next, state-of-the art methods in fuel cell companies will be used to fabricate MEAs containing the Mn-N-C catalysts. Finally, industry standards will be rigorously followed to evaluate fuel cell performance and durability of the Mn-N-C catalysts. With successful completion of the project, it is expected that the following outcomes will be achieved. (1) A set of MEAs containing the Mn-N-C catalysts and with active area large than 50 cm2 for independent testing, (2) testing results demonstrating that the MEAs of Mn-N-C catalysts have mass activity of 0.044 A/cm2 at 0.9 VIR-free and H2/air performance of 0.50 V at 1.0 A/cm2; (3) fundamental understanding of the composition-structure-property relation of the PGM-free Mn- N-C catalysts, and (4) computational data, measurement data, and publications deposited into the database of ElectroCat Consortium.