Conversion of guaiacol as lignin model component using acid-treated, multi-walled carbon nanotubes supported Ru–MnO bimetallic catalysts
Bibliographic record
Abstract
Acid-treated, multi-walled carbon nanotube (AMWCNT) supported Ru and MnO bimetallic catalysts were prepared for liquid phase hydrodeoxygenation of guaiacol. The physicochemical properties of the prepared catalysts were characterized by FTIR, XRD, NH 3 -TPD, CO 2 -TPD, TEM, and XPS. MnO species were loaded on the inner surface of carbon nanotubes and were helpful for Ru particle dispersion. The 6%Ru-8%MnO/AMWCNTs with smaller Ru particle size, better dispersion, and more basic sites gave the best catalytic performance of 99.38% conversion of guaiacol and 85.84% selectivity to cyclohexanol. The effects of reaction conditions on liquid phase guaiacol hydrodeoxygenation were discussed and a possible reaction path was proposed.
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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 | 0.000 | 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 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".