Non‐Metal Silicon Single‐Atom Catalysts with Unsymmetrically Tetradentate O <sub>3</sub> N <sub>1</sub> Moiety Enabling Ampere‐Level H <sub>2</sub> O <sub>2</sub> Electrosynthesis
Bibliographic record
Abstract
Abstract The development of efficient and stable catalysts for scalable and sustainable hydrogen peroxide (H 2 O 2 ) electrosynthesis via two‐electron oxygen reduction reaction (2e‐ORR) is of great significance to replace the high‐pollution anthraquinone oxidation process. Herein, O/N dual‐coordinated silicon (Si) single‐atom catalysts (SACs) uniformly immobilized on N‐doped graphene (SiO 3 ‐NC) are successfully synthesized using silicate as Si dopant via controllable solvothermal and nitridation processes. In the synthesize reaction, Si centers convert from Si–O 3 planar triangle to unsymmetrical Si–O 3 N 1 tetrahedron, which effectively modify the electronic distribution of the carbon matrix, providing high‐density active sites for electrocatalytic H 2 O 2 production. SiO 3 ‐NC catalysts achieve industrial‐relevant current densities for H 2 O 2 production with a record‐high productivity of 63.69 mol h −1 g cat. −1 , while maintaining exceptional Faradaic efficiencies and stability. In situ spectroscopic studies and theoretical calculations uncover that the unsymmetrically Si–O 3 N 1 configuration acts as an active center, which affords near‐optimal binding strength for OOH* adsorption and accelerates the kinetics of H 2 O 2 formation, thus promoting 2e‐ORR process.
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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".