Ethyl esters from the single‐phase base‐catalyzed ethanolysis of vegetable oils
Bibliographic record
Abstract
Abstract The effects of alcohol/oil molar ratio, base concentration, and temperature on the single‐phase base‐catalyzed ethanolyses of sunflower and canola oils were determined. The use of tetrahydrofuran as co‐solvent, as well as higher than usual alcohol/substrate molar ratios, prevented glycerol separation. This allowed each reaction to reach equilibrium rather than just steady‐state conditions. High conversions of oil lowered the concentrations of MG and DG surfactants in the products, and thereby mitigated the formation of emulsions usually associated with ethanolysis reactions. An alcohol/oil molar ratio of 25∶1, together with the necessary amount of cosolvent, gave optimal results. At this molar ratio, despite equilibrium being achieved, ethanolysis, unlike methanolysis, did not quite produce biodiesel‐standard material, the MG content being approximately 1.5 mass%. For methanolysis and 1‐butanolysis, the corresponding values were 0.6 and 2.0 mass%, respectively. The use of 1.4 mass% KOH (equivalent to 1.0 mass% NaOH) led to ethanolysis equilibrium within 6–7 min at 23°C rather than 15 min when only 1.0 mass% was used. At 60°C, equilibrium was reached within only 2 min. Soybean and canola oils behaved the same.
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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".