Orbital Interactions in Bi‐Sn Bimetallic Electrocatalysts for Highly Selective Electrochemical CO<sub>2</sub> Reduction toward Formate Production
Bibliographic record
Abstract
Abstract A highly selective and durable electrocatalyst for carbon dioxide (CO 2 ) conversion to formate is developed, consisting of tin (Sn) nanosheets decorated with bismuth (Bi) nanoparticles. Owing to the formation of active sites through favorable orbital interactions at the Sn‐Bi interface, the Bi‐Sn bimetallic catalyst converts CO 2 to formate with a remarkably high Faradaic efficiency (96%) and production rate (0.74 mmol h −1 cm −2 ) at −1.1 V versus reversible hydrogen electrode. Additionally, the catalyst maintains its initial efficiency over an unprecedented 100 h of operation. Density functional theory reveals that the addition of Bi nanoparticles upshifts the electron states of Sn away from the Fermi level, allowing the HCOO* intermediate to favorably adsorb onto the Bi‐Sn interface compared to a pure Sn surface. This effectively facilitates the flow of electrons to promote selective and durable conversion of CO 2 to formate. This study provides sub‐atomic level insights and a general methodology for bimetallic catalyst developments and surface engineering for highly selective 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".