Steering Carbon Hybridization State in Carbon-Based Metal-free Catalysts for Selective and Durable CO<sub>2</sub> Electroreduction
Bibliographic record
Abstract
Electrocatalytic CO 2 reduction using metal-free catalysts offers a promising and cost-effective approach to global carbon neutrality. However, metal-free catalysts frequently suffer from unsatisfactory catalytic performances, especially a low current density and poor stability. Herein, by modulating the orbital hybridization state of carbon, we strategically design a regulable sp 3 and sp 2 hybrid carbon interface embedded with adjacent boron and nitrogen sites in carbon-based metal-free catalysts for CO 2 electroreduction. Soft X-ray chemical imaging visually uncovers that the electronic structure and bonding configuration of the boron active site at the hybrid carbon interface are modulated by the neighboring nitrogen site and sp 3 carbon. The concomitant electron density reconfiguration around the interface not only delivers optimum upshift of the boron p-band center, and accordingly the moderate valence-electron depletion, to stabilize the *OCHO intermediate favorable for HCOOH generation but also weakens the boron–carbon and boron–hydrogen hybridization of competing *COOH and *H species, respectively, to promote HCOOH selectivity over CO and H 2 . The designed electrocatalyst realizes a record-high formate partial current density of up to 50.8 mA cm –2 among metal-free catalysts in the H-cell and maintains a high Faradaic efficiency (>90%) over 108 h. This work elevates the carbon interface design with a tailored carbon hybridization state 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".