Beginning of Life Cell Testing
| Project ID | 5906917d-2f8d-415f-a150-c730585adaab |
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Proton exchange membrane electrolysis benchmarking: Identifying and removing sources of variation in test stations, hardware, and membrane electrode assembly fabrication. To reach cost targets that accelerate the widespread deployment of renewable hydrogen production by electrolysis, research and development efforts must be rapid, efficient, and highly collaborative. To facilitate efforts, theH2NEW consortium has developed a benchmarking protocol as the basis for accurate comparison of PEM electrolyzer research results. Herein, three U.S. National Laboratories harmonize and validate this protocol to establish minimum requirements for test stations, cell hardware, cell test procedure, and the fabrication of a baseline material set, while maintaining maximum agreement of test results. The baseline membrane electrode assembly (MEA) features significantly lower loadings than commercially available and is referred to as the “Future Generation MEA (FuGeMEA)”.It consists of commercially available materials and is used as a baseline material set for research and development across the consortium. Using this material set, a phased harmonization approach is applied to isolate and address sources of variation associated with the test stations, cell hardware, and FuGeMEA fabrication procedure. Troubleshooting experiments are conducted within each phase, yielding a set of Lessons Learned (LL) that we present and discuss. In the final phase, the participating laboratories separately fabricate theFuGeMEA, assemble the cell, and conduct the harmonized test protocol to obtain cell performance results with a maximum standard deviation of 18mVat4Acm 2.This work thus establishes the FuGeMEA performance benchmark and test protocol as a baseline system for broad use in test equipment validation and comparison of performance results across the research community.
National Renewable Energy Laboratory: Makenzie Parimuha, James L. Young*, Guido Bender, Tobias Schuler Los Alamos National Laboratory: Abdurrahman Yilmaz, Sergio Diaz-Abad, Siddharth Komini Babu Lawrence Berkeley National Laboratory: Jason Keonhag Lee, Ramchandra Gawas