Catalytic Conversion of Glycerol to Methyl Lactate over Au-CuO/Sn-Beta: The Roles of Sn-Beta
Bibliographic record
Abstract
The production of methyl lactate as a degradable polymer monomer from biomass was an important topic for a sustainable society. In this manuscript, glycerol was oxidated to methyl lactate catalyzed by the combination of Au-CuO and Sn-Beta. The influence of Sn content, Sn source, and the preparation conditions for Sn-β was studied. The Au content in Au/CuO was also investigated by varying the Au content in Au/CuO. The catalysts were characterized by XRD, FTIR spectroscopy of pyridine adsorption, and TEM to study the role of Sn and the influence of different parameters for catalyst preparation. After the optimization of reaction parameters, the yield of methyl lactate from glycerol reached 59% at 363 K after reacting in 1.6 MPa of O2 for 6 h.
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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".