Asymmetric Coordination in Cobalt Single‐Atom Catalysts Enables Fast Charge Dynamics and Hierarchical Active Sites for Two‐Stage Kinetics in Photodegradation of Organic Pollutants
Bibliographic record
Abstract
Abstract Single‐atom catalysts (SACs) have attracted growing interest in solar‐driven catalysis, though challenges persist due to symmetrical metal coordination, which results in limited driving force and sluggish charge dynamics. Additionally, uneven energy and mass distribution complicate reaction pathways, ultimately restricting solar energy utilization and catalytic efficiency. Herein, we synthesized cobalt single atoms decorated carbon nitride catalysts featuring a highly asymmetric Co─C 2 N 3 coordination, tailored for photocatalytic organic pollutants removal. Advanced experimental studies and simulation results collectively revealed that the unique microenvironment surrounding Co single atoms improved charge dynamics and created reactive hot spots, facilitating the generation of reactive oxygen species during the photocatalytic degradation of organic pollutants. These enhanced charge dynamics, combined with hierarchical active sites, resulted in two‐stage reaction kinetics and excellent stability for the degradation of bisphenol A in wastewater, distinctly outperforming the first‐stage kinetics observed for polymeric carbon nitride. This work advances the understanding of structure‐performance relationships in SAC‐based photocatalytic degradation and offers valuable insights for the design of next‐generation SACs in environmental catalysis.
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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".