The role of impurities in the La2O3 catalysed carboxylation of crude glycerol
Bibliographic record
Abstract
The direct carboxylation of crude glycerol, obtained as a by-product of bio-diesel synthesis, with CO2 has been investigated over lanthanum oxide as a heterogeneous catalyst for the first time. Adiponitrile is employed as a dehydrating agent in order to shift the reaction equilibrium to the product side. The selectivity of the reaction towards glycerol carbonate when using crude glycerol is significantly reduced as compared to employing refined glycerol: 2.3% cf. 17% respectively. Glycerol conversion, however remains approximately constant: 54% cf. 58%. In order to understand the role of the impurities present in crude glycerol, model systems consisting of refined glycerol and one or more of water, methanol, methyl palmitate (as a model fatty acid methyl ester), and sodium methoxide have been prepared and used as reaction media to systematically evaluate their effect. All of these impurities are seen to reduce the selectivity towards glycerol carbonate, instead favouring the formation of 4-(hydroxymethyl)oxazolidin-2-one, with the exception of methanol where no detrimental effect is observed and the measured selectivity increases slightly to ca. 22%. This effect is ascribed, in part, to improved mass transfer as a consequence of an increased solubility of carbon dioxide in the liquid media when methanol is present. Additionally, adiponitrile is observed to play a crucial role in the reaction mechanism beyond its simple role as a dehydrating agent. These results provide insights into the required purification steps for crude glycerol, and suggest the possibility of employing crude glycerol directly, and its use as a chemical feedstock; in both cases by minimising costly separation and purification steps.
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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 | 0.001 | 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".