Probing Electrocatalytic Gas Evolution Reaction at Pt by Force Noise Measurements. Part 1. Hydrogen
Bibliographic record
Abstract
Electrocatalytic processes occurring at a heterogeneous interface are complex, and their understanding at the molecular level remains challenging. Atomic force microscopy (AFM) can detect force interactions down to the atomic level, but so far it has been mainly used to obtain in situ images of electrocatalysts. Here, for the first time, we employ AFM to investigate gas evolution at a platinum ultramicroelectrode (Pt UME) under electrochemical conditions using force noise measurements. We detect excess force noise when individual H 2 gas bubble nucleation, growth, and detachment events occur at the Pt UME. Based on our in situ AFM, electrochemical, and optical microscopy analyses, we conclude that larger size H 2 gas bubbles remain pinned to the UME surface while smaller H 2 gas bubbles are released until an overpotential of −0.8 V vs RHE. This study demonstrates the viability of in situ AFM in studying gas evolution under electrocatalytic conditions and contributes to a mechanistic understanding of the H 2 gas bubble detachments during the hydrogen evolution reaction (HER).
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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 | 0.001 |
| 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 | 0.001 | 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".