Selective liquid‐phase oxidation of toluene with molecular oxygen catalyzed by <scp> Mn‐TiO <sub>2</sub> </scp> under solvent‐free conditions
Bibliographic record
Abstract
Abstract In this paper, we reported the preparation, characterization, and catalytic performance of TiO 2 doped with Mn for the selective oxidation of toluene to benzyl alcohol and benzaldehyde without any solvent. The structure of the catalyst was determined by X‐ray diffraction (XRD), X‐ray photoelectron spectroscopy (XPS), nitrogen adsorption–desorption analysis (Brunauer–Emmet–Teller [BET]), scanning electron microscope (SEM), transmission electron microscope (TEM), and mapping. The results demonstrated that the catalytic properties of Mn‐TiO 2 were higher than those of pure Mn 3 O 4 and TiO 2 . The effects of reaction temperature, reaction time, oxygen pressure, and the amount of catalyst were studied. Under the optimal conditions, Mn‐TiO 2 could afford 6.4% toluene conversion at a combined benzyl alcohol/benzaldehyde selectivity of 58.6%. Moreover, the catalyst can be repeated in the experiment for five times without significant loss of activity.
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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) | 0.000 | 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".