Nano-crumples induced Sn-Bi bimetallic interface pattern with moderate electron bank for highly efficient CO2 electroreduction
Bibliographic record
Abstract
Abstract CO 2 electroreduction reaction offers an attractive approach to global carbon neutrality. Industrial CO 2 electrolysis towards formate requires stepped-up current densities, which is limited by the difficulty of precisely reconciling the competing intermediates (COOH* and HCOO*). Herein, nano-crumples induced Sn-Bi bimetallic interface-rich materials are in situ designed by tailored electrodeposition under CO 2 electrolysis conditions, significantly expediting formate production. Compared with Sn-Bi bulk alloy and pure Sn, this Sn-Bi interface pattern delivers optimum upshift of Sn p-band center, accordingly the moderate valence electron depletion, which leads to weakened Sn-C hybridization of competing COOH* and suitable Sn-O hybridization of HCOO*. Superior partial current density up to 140 mA/cm 2 for formate is achieved. High Faradaic efficiency (>90%) is maintained at a wide potential window with a durability of 160 h. In this work, we elevate the interface design of highly active and stable materials for efficient CO 2 electroreduction.
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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".