Oxygen Reduction Reaction Catalyzed by Carbon-Supported Platinum Few-Atom Clusters: Significant Enhancement by Doping of Atomic Cobalt
Bibliographic record
Abstract
Oxygen reduction reaction (ORR) plays an important role in dictating the performance of various electrochemical energy technologies. As platinum nanoparticles have served as the catalysts of choice towards ORR, minimizing the cost of the catalysts by diminishing the platinum nanoparticle size has become a critical route to advancing the technological development. Herein, first-principle calculations show that carbon-supported Pt 9 clusters represent the threshold domain size, and the ORR activity can be significantly improved by doping of adjacent cobalt atoms. This is confirmed experimentally, where platinum and cobalt are dispersed in nitrogen-doped carbon nanowires in varied forms, single atoms, few-atom clusters, and nanoparticles, depending on the initial feeds. The sample consisting primarily of Pt 2~7 clusters doped with atomic Co species exhibits the best mass activity among the series, with a current density of 4.16 A mg Pt − 1 at +0.85 V vs. RHE that is almost 50 times higher than that of commercial Pt/C.
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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".