Collision Incidents of Single Tetrahexahedral Platinum Nanocrystals Recorded by a Carbon Nanoelectrode
Bibliographic record
Abstract
Abstract Recently, collision mode has been adopted to study the electrochemical or photoelectrochemical behavior of single particles touching and/or attaching on a biased ultramicroelectrode (UME). However, to correlate the reaction activity to the nanocrystal structure still remains challenging because of: (1) the uncontrolled structure and size of the single nanoparticle; (2) the uncertainty of one particle in each collision incident since the size of UME is much larger than that of the single nanoparticle. To these problems, we synthesized well‐defined convex tetrahexahedral platinum nanocrystals (THH Pt NC) with an average size of 30 nm and fabricated a carbon nanoelectrode through pyrolysis of butane. The current fluctuation caused by oxygen reduction reaction (ORR) during the single collision incident of THH Pt NC was detected by the carbon nanoelectrode. It is reasonable to use nanocrystals with well‐defined morphology and size in the collision experiments. However, the adoption of nanoelectrode will decrease the collision frequency and shorten the standing time of nanocrystals on the electrode surface. How to figure out the kinetics from the current fluctuations in the single collision incident still remains challenging.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".