Electron Localization and Lattice Strain Induced by Surface Lithium Doping Enable Ampere‐Level Electrosynthesis of Formate from CO<sub>2</sub>
Bibliographic record
Abstract
Abstract The electrochemical CO2 conversion to formate is a promising approach for reducing CO2 level and obtaining value‐added chemicals, but its partial current density is still insufficient to meet the industrial demands. Herein, we developed a surface‐lithium‐doped tin (s‐SnLi) catalyst by controlled electrochemical lithiation. Density functional theory calculations indicated that the Li dopants introduced electron localization and lattice strains on the Sn surface, thus enhancing both activity and selectivity of the CO2 electroreduction to formate. The s‐SnLi electrocatalyst exhibited one of the best CO2‐to‐formate performances, with a partial current density of −1.0 A cm−2 for producing formate and a corresponding Faradaic efficiency of 92 %. Furthermore, Zn–CO2 batteries equipped with the s‐SnLi catalyst displayed one of the highest power densities of 1.24 mW cm−2 and an outstanding stability of >800 cycles. Our work suggests a promising approach to incorporate electron localization and lattice strain for the catalytic sites to achieve efficient CO2‐to‐formate electrosynthesis toward potential commercialization.
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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".