Potential-Driven Coordinated Oxygen Migration in an Electrocatalyst for Sustainable H<sub>2</sub>O<sub>2</sub> Synthesis
Bibliographic record
Abstract
Local coordination environment (LCE) manipulation has emerged as a significant approach for modulating the electrocatalytic behavior of low-dimensional nanomaterials. However, challenges persist in accurately identifying active sites and understanding dynamic changes during operation. Here, we underscore the influence of LCE on the electrochemical production of H 2 O 2, utilizing the Pd cluster as a model catalyst. Density functional theory (DFT) calculations illustrate the role of first- and second-coordinated sulfur and oxygen in modulating the binding strength of HOO*. Guided by DFT screening, the as-prepared Pd cluster (Pd x /HMCS) catalyst presents exceptional catalytic performance with a high mass activity of 4.06 A mg –1 at 0.45 V and selectivity above 94%. The Pd x /HMCS catalyst also delivers promising potential for industrial practices with a production rate of 16.3 mol g cat –1 h –1 in flow cell evaluation. Elaborated in situ characterizations confirm that under operation, oxygen migrates from the second coordination sphere (CS) to the first CS to achieve oxygen coverage on the catalyst surface. Such an oxygen migration phenomenon and the optimized first and second coordination environment give rise to the outstanding performance.
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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".