Imaging Heterogeneous Electrocatalyst Stability and Decoupling Degradation Mechanisms in Operating Hydrogen Fuel Cells
Bibliographic record
Abstract
The proliferation of hydrogen fuel cell systems is hindered by a degradation of the platinum catalyst. Here, we provide a device-level assessment of the catalyst degradation phenomena and its coupling to nanoscale hydration gradients, using advanced operando X-ray scattering tomography tailored for device-scale imaging. Gradients formed inside the fuel cell produce a heterogeneous degradation of the catalyst nanostructure, which can be linked to the flow field design and water distribution in the cell. Striking differences in catalyst degradation are observed between operating fuel cell devices and the liquid cell routinely used for catalyst stability studies, highlighting the crucial impact of the complex operating environment on the catalyst degradation phenomena. This degradation knowledge gap accentuates the necessity of multimodal, in situ characterization of real devices when assessing the performance and durability of electrocatalysts and, more generally, electrochemically active phases used in energy conversion and storage technologies.
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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".