Interface‐Induced Electrocatalytic Enhancement of CO<sub>2</sub>‐to‐Formate Conversion on Heterostructured Bismuth‐Based Catalysts
Bibliographic record
Abstract
Abstract Electrochemical CO2 reduction reaction (CO2RR) is a promising approach to convert CO2 to carbon‐neutral fuels using external electric powers. Here, the Bi2S3‐Bi2O3 nanosheets possessing substantial interface being exposed between the connection of Bi2S3 and Bi2O3 are prepared and subsequently demonstrate to improve CO2RR performance. The electrocatalyst shows formate Faradaic efficiency (FE) of over 90% in a wide potential window. A high partial current density of about 200 mA cm−2 at −1.1 V and an ultralow onset potential with formate FE of 90% are achieved in a flow cell. The excellent electrocatalytic activity is attributed to the fast‐interfacial charge transfer induced by the electronic interaction at the interface, the increased number of active sites, and the improved CO2 adsorption ability. These collectively contribute to the faster reaction kinetics and improved selectivity and consequently, guarantee the superb CO2RR performance. This study provides an appealing strategy for the rational design of electrocatalysts to enhance catalytic performance by improving the charge transfer ability through constructing a functional heterostructure, which enables interface engineering toward more efficient CO2RR.
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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".