Creating High‐entropy Single Atoms on Transition Disulfides through Substrate‐induced Redox Dynamics for Efficient Electrocatalytic Hydrogen Evolution
Bibliographic record
Abstract
Abstract The controllable anchoring of multiple metal single‐atoms (SAs) into a single support exhibits scientific and technological opportunities, while marrying the concentration‐complex multimetallic SAs and high‐entropy SAs (HESAs) into one SAC system remains a substantial challenge. Here, we present a substrate‐mediated SAs formation strategy to successfully fabricate a library of multimetallic SAs and HESAs on MoS 2 and MoSe 2 supports, which can precisely control the doping location of SAs. Specially, the contents of SAs can continuously increase until the accessible Mo atoms on TMDs carriers are completely replaced by SAs, thus allowing the of much higher metal contents. In‐depth mechanistic study shows that the well‐controlled synthesis of multimetallic SAs and HESAs is realized by controlling the reversible redox reaction occurred on the TMDs/TM ion interface. As a proof‐of‐concept application, a variety of SAs‐TMDs were applied to hydrogen evolution reaction. The optimized HESAs‐TMDs (Pt,Ru,Rh,Pd,Re‐MoSe 2 ) delivers a much higher activity and durability than state of‐the‐art Pt. Thus, our work will broaden the family of single‐atom catalysts and provide a new guideline for the rational design of high‐performance single‐atom catalysts.
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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".