In Situ Liquid Cell TEM Study of Morphological Evolution and Degradation of Pt–Fe Nanocatalysts During Potential Cycling
Bibliographic record
Abstract
Nanocatalyst degradation is a serious limiting factor for the commercialization of proton exchange membrane fuel cells. Although the degradation has been extensively studied in the past through various ex situ electrochemical methods, employing an in situ technique can greatly improve our understanding of the mechanisms involved during the electrochemical cycling. In this work, we have employed an in situ liquid cell inside a TEM for a simultaneous investigation of the structural evolution and electrochemical response of Pt–Fe nanocatalysts. We demonstrate that the coarsening processes of these nanocatalyst particles, including the nucleation and growth, are not uniform, both in space and in time scale. The growth rate is found to be both site- and potential-dependent. Furthermore, these particles were found to exhibit considerably different behaviors when attached to an electrode as opposed to when isolated in the electrolyte. With Pt–Fe nanoalloy system as a candidate material, this work demonstrates that the in situ structural characterization of nanocatalysts under electrochemical bias and inside the native electrolyte environment provides much deeper insight into the catalyst degradation mechanisms as compared to the routine ex situ electrochemical studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".