Ultrasound-assisted transesterification of soybean oil using low power and high frequency and no external heating source
Bibliographic record
Abstract
In this work, high frequency and low power ultrasound without external heating source and mechanical stirring in biodiesel production were studied. Transesterification of soybean oil with methanol and catalyzed by KOH was investigated using ultrasound equipment and ultrasonic transducer. The effect of ultrasonic output power (3 W-9 W), ultrasonic frequency (1 MHz and 3 MHz), and alcohol to oil molar ratio (6:1 and 8:1) have been investigated. The increase in ultrasonic power provided higher conversion rates. In addition, higher conversion rates were obtained by increasing the ultrasonic frequency from 1 MHz to 3 MHz (48.7% to 79.5%) for the same reaction time. Results also indicate that the speed of sound can be used to evaluate the produced biodiesel qualitatively. Further, the ultrasound system presented electric consumption (46.2W∙h) four times lower than achieved using the conventional method (211.7W∙h and 212.3W∙h). Thus, biodiesel production using low power ultrasound in the MHz frequency range is a promising technology that could contribute to biodiesel production processes.
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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) | 0.000 | 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".