Transesterification of Fish Oil to Produce Fatty Acid Ethyl Esters Using Ultrasonic Energy
Bibliographic record
Abstract
Abstract This study evaluated the production of fatty acid ethyl esters from fish oil using ultrasonic energy and alkaline catalysts dissolved in ethanol. The feasibility of fatty acid ethyl ester production was determined using an ultrasonic bath and probe, and between 0.5 and 1% KOH (added to the fish oil). Furthermore, factors such as ultrasonic device (bath and probe), catalyst (KOH and C2H5ONa), temperature (20 and 60 °C), and duration of exposure (10–90 min) were assessed. Sodium ethoxide was found to be a more efficient catalyst than KOH when transesterifying fish oil. Ultrasonic energy applied for greater than 30 min at 60 °C using 0.8% of C2H5ONa as a catalyst transesterified over 98% fish oil triglycerides to fatty acid ethyl esters. It is reasonable to conclude that the yield of fatty acid ethyl esters produced by applying ultrasonic energy to fish oil is related to the sonication time. Due to increases in the surface area contact between the reactants and the catalyst, ultrasonic energy has the potential to reduce the production time required by a conventional large‐scale commercial transesterification method that uses agitation as a way of mixing.
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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".