Effect of Metals on the Hydrogenolysis of Glycerol to Higher Value Sustainable and Green Chemicals Using a Supported HSiW Catalyst
Bibliographic record
Abstract
Pt, Pd, Ni, and Cu supported on HSiW/Al 2 O 3 catalysts were studied for the hydrogenolysis of glycerol. It was found that Pt is the best promoter for the production of 1,3-propanediol (1,3-PD) and 1-propanol (1-PO). Ni, a much cheaper metal, has fairly comparable reactivity to Pt, while Cu does not show any activity for the production of 1,3-PD. The catalysts were characterized by XRD and NH 3 -TPD. The strength of the acid sites affects the distribution of products. A reaction mechanism for a NiHSiW/Al 2 O 3 catalyst involving rate-determining parallel dehydration of primary alcohol to produce acetal and of secondary alcohol to produce 3-hydroxypropylaldehdye (3-HPA) was proposed. Hydrogenolysis of 1,3-PD is 15 times slower than that of 1,2-PD. Most of the 1-PO is derived from 1,2-PD. An optimal balance of acid sites of appropriate acid strength and hydrogenation sites will lead to a highly selective catalyst for the production of higher value sustainable chemicals from glycerol.
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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".