FIB‐SEM and ToF‐SIMS Analysis of High‐Temperature PEM Fuel Cell Electrodes
Bibliographic record
Abstract
Abstract The phosphoric acid (PA) distribution in the electrodes is a crucial factor for the performance of high‐temperature polymer electrolyte fuel cells (HT‐PEM FCs). Therefore, understanding and optimizing the electrolyte distribution is vital to maximizing power output and achieving low degradation. Although challenging, tracking the PA in nanometer‐sized pores is essential because most active sites in the commonly used carbon black‐supported catalysts are located in pores below 1 µm. For this study, a cell is operated at 200 mA cm−2 for 5 days. After this break‐in period, the cathode is separated from the membrane electrode assembly and subsequently investigated by cryogenic focused ion beam scanning electron microscopy (cryo FIB‐SEM) coupled with energy‐dispersive X‐ray spectroscopy (EDX) and time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS). PA is located on the surface and in the bulk of the cathode catalyst layer. In addition, the PA distribution can be successfully linked to the gas diffusion electrode morphology and the binder distribution. The PA preferably invades nanometer‐sized pores and is uniformly distributed in the catalyst layer.
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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 | 0.001 | 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) | 0.004 | 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".