Achieving high performance and durability with ultra-low precious metal nanolayer on porous transport layer for PEMWE application
Bibliographic record
Abstract
Green hydrogen produced from polymer electrolyte membrane water electrolysis (PEMWE) provides a promising pathway to decarbonization. However, excessive dependence on Pt and Ir in the catalyst synthesis and anticorrosive coating on porous transport layers (PTL) drives the cost of PEMWE technology . As an alternative to the Pt-coated commercial PTL, sputtered multilayer and co-deposited TaPt coatings with low Pt loading were developed. Ex-situ electrochemical and physical characterizations (potentiostatic and galvanostatic polarization, scanning electron microscopy, interfacial contact resistance (ICR) testing, and x-ray photoelectron spectroscopy), and in-situ PEMWE cell testing was conducted to examine the PTL coating viability. Under the ex-situ PTL electrochemical stability analysis protocol developed in this work, the multilayered TaPt coating exhibited a higher simulated durability (96 h at 2.0 A cm −2 ) and lower ICR (1.9 mΩ cm 2 ) than the existing commercial Pt-coated PTL (15 h simulated durability and 2.1 mΩ cm 2 ). Low compressive stress and low extent of Galvanic coupling led to an improvement in the durability, conductivity, and in-situ performance of the TaPt multilayered PTL coating.
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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".