Kinetics of the reaction of ethanol and lauric acid catalyzed by deep eutectic solvent based on benzyltrimethylammonium chloride
Bibliographic record
Abstract
Abstract In this work, three types of deep eutectic solvents (DESs: BAC‐PTSA, BAC‐2PTSA, and BAC‐3PTSA) based on benzyltrimethylammonium chloride (BAC) were successfully synthesized by mixing benzyltrimethylammonium chloride with p‐toluenesulphonic acid monohydrate (PTSA) and used as catalysts for the esterification reaction of ethanol and lauric acid. The kinetics of the reaction of ethanol and lauric acid in the presence of DESs as catalysts was investigated systemically in the temperature range of 333.15–353.15 K. The influences of different parameters including type of DESs, reaction temperature, catalyst loading, and initial reactant molar ratio on the conversion of lauric acid were discussed. The kinetic experimental data obtained were successfully correlated by the pseudohomogeneous (PH) model based on the activities. Moreover, BAC‐3PTSA is easily synthesized and reused six times without any significant decrease in catalytic activity.
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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) | 0.001 | 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".