Single Atom Ruthenium‐Doped CoP/CDs Nanosheets via Splicing of Carbon‐Dots for Robust Hydrogen Production
Bibliographic record
Abstract
Abstract Ultrathin two‐dimensional catalysts are attracting attention in the field of electrocatalytic hydrogen evolution. This work describe a composite material design in which CoP nanoparticles doped with Ru single‐atom sites supported on carbon dots (CDs) single‐layer nanosheets formed by splicing CDs (Ru 1 CoP/CDs). Small CD fragments bore abundant functional groups, analogous to pieces of a jigsaw puzzle, and could provide a high density of binding sites to immobilize Ru 1 CoP. The single‐particle‐thick nanosheets formed by splicing CDs acted as supports, which improved the conductivity of the electrocatalyst and the stability of the catalyst during operation. The Ru 1 CoP/CDs formed from doping atomic Ru dispersed on CoP showed very high efficiency for the hydrogen evolution reaction (HER) over a wide pH range. The catalyst prepared under optimized conditions displayed outstanding stability and activity: the overpotential for the HER at a current density of 10 mA cm −2 was as low as 51 and 49 mV under alkaline and acidic conditions, respectively. Density functional theory calculations showed that the substituted Ru single atoms lowered the proton‐coupled electron transfer energy barrier and promoted H−H bond formation, thereby enhancing catalytic performance for the HER. The findings open a new avenue for developing carbon‐based hybridization materials with integrated electrocatalytic performance for water splitting.
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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".