Exposure of Active Metal Sites on Cu14 Nanoclusters for Highly Selective Electrocatalytic Nitrate Reduction
Bibliographic record
Abstract
Atomically precise metal nanoclusters (NCs) have been extensively used as catalysts for various reactions owing to the ultimate controllability of their parameters, such as the number of constituent atoms, crystal structure, and alloying characteristics. However, for many metal NCs, their surfaces are entirely covered by ligands, preventing the exposure of surface metal atoms that serve as active sites, and thus hindering their catalytic functionality. Herein, we report that exposure of metal sites in Cu14 NC can be achieved by facile modification of the thiolate ligands. Consequently, we found that Cu14 NCs with exposed Cu sites exhibit significantly higher ammonia selectivity and production rate in electrochemical nitrate reduction. These findings underscore the importance of atomically precise control over metal NCs, not only regarding their overall geometric structures but also with respect to their reactive sites, for achieving highly selective and active catalysts, contributing to the future design of diverse metal NC catalysts.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".