Glycerol Carbonate from Dimethyl Carbonate and Glycerol Over TBD‐Functionalized SBA‐16
Bibliographic record
Abstract
Abstract The transesterification reaction of glycerol with dimethyl carbonate (DMC) into glycerol carbonate presents an attractive route for simultaneous biodiesel by‐product valorization and indirect CO 2 utilization. In this study, a heterogeneous catalyst was developed for this reaction by grafting 1,5,7‐triazabicyclo[4.4.0]dec‐5‐ene (TBD) on mesoporous SBA‐16 silica (TBD@SBA‐16), combining strong basicity with high surface area and structural stability. Various physicochemical characterizations (BET, TGA, FTIR, NMR, SAXS, TEM) confirmed the successful formation, functionalization, and thermal stability of samples. The forward reaction was identified as endothermic and entropy‐driven, with an activation energy of 23.3 kJ/mol in the presence of homogeneous TBD, as validated by kinetic and thermodynamic analyses. This reaction was monitored for the influence of reaction parameters, including catalyst loading, reaction time, temperature, and DMC/glycerol molar ratio. Under optimal conditions (3 wt% catalyst, 90 °C, 2 h, 4:1 DMC: glycerol molar ratio), glycerol conversion reached 97% with glycerol carbonate yield exceeding 98%. The grafted catalyst displayed higher selectivity and operational practicality compared to homogeneous TBD. Reusability studies over five successive cycles revealed just a minor activity loss (∼4%) and low TBD leaching. These findings highlight the efficiency and stability of TBD@SBA‐16 as a viable heterogeneous catalyst for the selective synthesis of glycerol carbonate.
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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) | 0.001 | 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 | 0.001 |
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".