Dual‐Scale Integration Design of Sn–ZnO Catalyst toward Efficient and Stable CO<sub>2</sub> Electroreduction
Bibliographic record
Abstract
emission and producing valuable fuels. In the quest to resolve its current problems of low-energy efficiency and insufficient durability, a dual-scale design strategy is proposed by implanting a non-noble active Sn-ZnO heterointerface inside the nanopores of high-surface-area carbon nanospheres (Sn-ZnO@HC). The metal d-bandwidth tuning of Sn and ZnO alters the extent of substrate-molecule orbital mixing, facilitating the breaking of the *COOH intermediate and the yield of CO. Furthermore, the confinement effect of tailored nanopores results in a beneficial pH distribution in the local environment around the Sn-ZnO nanoparticles and protects them against leaching and aggregating. Through integrating electronic and nanopore-scale control, Sn-ZnO@HC achieves a quite low potential of -0.53 V vs reversible hydrogen electrode (RHE) with 91% Faradaic efficiency for CO and an ultralong stability of 240 h. This work provides proof of concept for the multiscale design of electrocatalysts.
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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) | 0.000 | 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 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".