PEM Electrolysis Benchmarking: Lessons Learned in Identifying and Removing Sources of Variation in Test Stations, Hardware, and MEA Fabrication
Bibliographic record
Abstract
This talk will overview work within the H2NEW Consortium to accelerate joint research efforts 1 . A performance benchmark and test protocol is established and validated as a baseline system to enable meaningful comparison of results across the research community. Three U.S. National Laboratories have harmonized and validated the equipment and procedures to confirm the 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. The detailed MEA fabrication procedures and protocol will be summarized 1 . A phased harmonization approach allowed for isolating and addressing sources of variation. I will summarize the troubleshooting experiments that have yielded a set of Lessons Learned to aid others in identifying equipment or protocol deviations and/or shortcomings that can compromise comparability and repeatability of test results. In the final phase, the participating laboratories separately fabricate the FuGeMEA and conduct the harmonized test protocol to obtain cell performance results with a maximum standard deviation of 18 mV at 4 A cm -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. 1 Proton exchange membrane electrolysis benchmarking: Identifying and removing sources of variation in test stations, hardware, and membrane electrode assembly fabrication. International Journal of Hydrogen Energy , Volume 114, 2025, Pages 486-496. https://doi.org/10.1016/j.ijhydene.2025.02.443
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.130 | 0.093 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.011 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".