Grooved Electrodes for High Power Density Fuel Cells
Bibliographic record
Abstract
Proton exchange membrane fuel cells (PEMFCs) are a promising alternative to internal combustion engines, owing to their intrinsic power density, decoupled energy storage and generation, and relatively short refueling time. However, challenges related to cost, performance, and durability continue to prevent wide adoption of PEMFCs. 1 Development of alternative electrode structures, which can enable smaller and less expensive PEMFCs with higher power and lower precious metal content, provides a promising path to overcome these challenges. 2 Here, we report grooved electrodes, where the transport pathways of H + and O 2 were partitioned. Specifically, H + are transported through electrode ridges with optimized ionomer content, and O 2 is transported through the grooves that separate the electrode ridges. The grooved electrodes made with commercial electrode materials enhanced the performance up to 50%, and the enhancement becomes greater after accelerated durability tests. We verify via electrochemical impedance analyses, limiting current measurements, and multiphysics modeling that the enhancement is due to improved H + and O 2 transport. The work also demonstrates that the electrodes can be further improved by optimizing the electrode geometry, proven via machine learning investigations. These results inform next generation electrode designs for enhanced PEMFC performance and durability. Acknowledgement: This work was supported by the Hydrogen and Fuel Cell Technologies Office (HFTO), Office of Energy Efficiency and Renewable Energy, US Department of Energy (DOE) through the Million Mile Fuel Cell Truck (M2FCT) consortia, technology managers G. Kleen and D. Papageorgopoulos. Financial support for this work from the Laboratory Directed Research and Development (LDRD) program at Los Alamos National Laboratory (LANL) is gratefully acknowledged (Projects 2020200DR and 20210915PRD2). ChungHyuk Lee acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC). References: D. A. Cullen et al., Nat. Energy , 6 , 462–474 (2021). K. Jiao et al., Nature , 595 , 361–369 (2021).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".