Ternary Sn‐Ti‐O Electrocatalyst Boosts the Stability and Energy Efficiency of CO<sub>2</sub> Reduction
Bibliographic record
Abstract
Abstract Simultaneously improving energy efficiency (EE) and material stability in electrochemical CO2 conversion remains an unsolved challenge. Among a series of ternary Sn‐Ti‐O electrocatalysts, 3D ordered mesoporous (3DOM) Sn0.3Ti0.7O2 achieves a trade‐off between active‐site exposure and structural stability, demonstrating up to 71.5 % half‐cell EE over 200 hours, and a 94.5 % Faradaic efficiency for CO at an overpotential as low as 430 mV. DFT and X‐ray absorption fine structure analyses reveal an electron density reconfiguration in the Sn‐Ti‐O system. A downshift of the orbital band center of Sn and a charge depletion of Ti collectively facilitate the dissociative adsorption of the desired intermediate COOH* for CO formation. It is also beneficial in maintaining a local alkaline environment to suppress H2 and formate formation, and in stabilizing oxygen atoms to prolong durability. These findings provide a new strategy in materials design for efficient CO2 conversion and beyond.
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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".