Stainless Steel Felt as a Combined OER Electrocatalyst/Porous Transport Layer for Investigating Anion-Exchange Membranes in Water Electrolysis
Bibliographic record
Abstract
Anion-exchange membrane water electrolysis (AEMWE) is a promising technology for low-cost, high-efficiency, green hydrogen production. The stability of the AEM is a critical issue but difficult to delineate in situ from degradation of the catalyst layer (CL). Moreover, the porous transport layer (PTL) can contribute electrocatalytically. Herein, we demonstrate that stainless steel (SS) felt, in the absence of an anode CL, is highly active toward the oxygen evolution reaction (OER) (1 A cm –2 at 1.74 V cell ) and serves as a combined OER electrocatalyst and PTL, thus simplifying the study of AEMs in water electrolyzers. We further show that Ni felt exhibits much lower OER activity than SS felt, which suggests that in situ studies of OER electrocatalysts and CL compositions should be performed with Ni felt, not SS felt, to reduce OER contributions from the PTL. Lastly, we found that the substrate for depositing the cathode CL, AEM, or PTL strongly influences the rate of H 2 crossover.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".