Boosting Benzene Oxidation with a Spin‐State‐Controlled Nuclearity Effect on Iron Sub‐Nanocatalysts
Bibliographic record
Abstract
Abstract A fundamental understanding of the nature of nuclearity effects is important for the rational design of superior sub‐nanocatalysts with low nuclearity, but remains a long‐standing challenge. Using atomic layer deposition, we precisely synthesized Fe sub‐nanocatalysts with tunable nuclearity (Fe 1 –Fe 4 ) anchored on N,O‐co‐doped carbon nanorods (NOC). The electronic properties and spin configuration of the Fe sub‐nanocatalysts were nuclearity dependent and dominated the H 2 O 2 activation modes and adsorption strength of active O species on Fe sites toward C−H oxidation. The Fe 1 ‐NOC single atom catalyst exhibits state‐of‐the‐art activity for benzene oxidation to phenol, which is ascribed to its unique coordination environment (Fe 1 N 2 O 3 ) and medium spin state ( t 2g 4 e g 1 ); turnover frequencies of 407 h −1 at 25 °C and 1869 h −1 at 60 °C were obtained, which is 3.4, 5.7, and 13.6 times higher than those of Fe dimer, trimer, and tetramer catalysts, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".