Glycerol transesterification with ethyl acetate to synthesize acetins using ethyl acetate as reactant and entrainer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Transesterification of glycerol with ethyl acetate was performed over acidic catalysts in the batch and semi-batch systems. Ethyl acetate was used as reactant and entrainer to remove the produced ethanol during the reaction, through azeotrope formation. Since the azeotrope of ethyl acetate and ethanol forms at 70 oC, all the experiments were performed at this temperature. Para-toluene sulfonic acid, sulfuric acid, and Amberlyst 36 were used as catalyst. The effect of process parameters including ethyl acetate to glycerol molar ratio (6-12), reaction time (3-9 h), and the catalyst to glycerol weight (2.5-9.0%), on the conversion and products selectivities were investigated. Under reflux conditions, 100% glycerol conversion was obtained with 45%, 44%, and 11% selectivity to monoacetin, diacetin, and triacetin, respectively. Azeotropic reactive distillation led to 100% conversion of glycerol with selectivities of 3%, 48% and 49% for monoacetin, diacetin, and triacetin. During the azeotropic reactive distillation, it was possible to remove ethanol to shift the equilibrium towards diacetin and triacetin. Therefore, the total selectivity to diacetin and triacetin was increased from 55% to 97% through azeotropic distillation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it