<scp>Ultralow‐Energy‐Barrier H<sub>2</sub>O<sub>2</sub></scp> Dissociation on Coordinatively Unsaturated Metal Centers in Binary <scp>Ce‐Fe</scp> Prussian Blue Analogue for Efficient and Stable <scp>Photo‐Fenton</scp> Catalysis
Bibliographic record
Abstract
The low intrinsic activity of Fenton catalytic site and high demand for light‐energy input inhibit the organic‐pollution control efficiency of photo‐Fenton process. Here, through structural design with density functional theory (DFT) calculations, Ce is predicted to enable the construction of coordinatively unsaturated metal centers (CUCs) in Prussian blue analogue (PBA), which can strongly adsorb H2O2 and donate sufficient electrons for directly splitting the O–O bond to produce ·OH. Using a substitution‐co‐assembly strategy, binary Ce‐Fe PBA is then prepared, which rapidly degrades sulfamethoxazole with the pseudo‐first‐order kinetic rate constant exceeding reported values by 1–2 orders of magnitude. Meanwhile, the photogenerated electrons reduce Fe(III) and Ce(IV) to promote the metal valence cycle in CUCs and make sulfamethoxazole degradation efficiency only lose 6.04% in 5 runs. Overall, by introducing rare earth metals into transition metal–organic frameworks, this work guides the whole process for highly active CUCs from design and construction to mechanism exploration with DFT calculations, enabling ultrafast and stable photo‐Fenton 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".