Engineering the synergistic effect of carbon dots‐stabilized atomic and subnanometric ruthenium as highly efficient electrocatalysts for robust hydrogen evolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Currently, the most efficient electrocatalyst for the hydrogen evolution reaction (HER) in water dissociation is Pt‐based catalyst. Unfortunately, the high cost and less than perfect efficiency hinder wide‐range industrial/technological applications. Here, by controlling the treatment temperature of tris (2,2‐bipyridine) ruthenium dichloride hexahydrate, synthesis of compounds with novel ruthenium single/dual atoms (Ru S/DAs) mixed with Ru nanoclusters (Ru S/DAs + Ru NCs) and supported by carbon dots is demonstrated. These compounds are shown to be highly efficient and competitive catalysts for hydrogen evolution. Ru S/DAs + Ru NCs exhibit very high activity, with overpotentials of 15 and 40 mV at a current density of 10 mA/cm 2 in 1.0 mol/L KOH and 0.5 mol/L H 2 SO 4 , respectively. Furthermore, the composites are found to possess outstanding stability and rapid HER kinetics. X ray absorption fine structure analysis, supported by density functional theory calculations, shows charge rearrangement in single‐atomic Ru, and the Ru dual sites promote active hydrogen adsorption and recombination. Ru S/DAs and Ru NCs demonstrate high electroactivity due to the electroactive Ru 4d orbitals. The introduction of Ru NCs activates the carbon support, providing a high electronic conductivity to transfer electrons from Ru NCs to Ru S/DAs, and facilitates water dissociation for the HER process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it