Biodiesel synthesis from <i>Brassica napus</i> seed oil using statistical optimization approach
Why this work is in the frame
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Bibliographic record
Abstract
In this study, response surface methodology (RSM) based on a central composite rotatable design was applied to establish the optimum conditions for the methanolysis of Brassica napus (B. napus) seed oil. Four process variables were evaluated at two levels (24 experimental design): the methanol/oil molar ratio (3:1–12:1), the catalyst concentration in relation to oil mass (0.25–1.25 wt. % KOH), the reaction temperature (25–65 °C), and the alcoholysis reaction time (20–120 min). The use of RSM resulted in a quadratic polynomial equation obtained by multiple regression analysis to predict transesterification. The results have shown that the methanol-oil-molar ratio and reaction time significantly affect the biodiesel yield. The highest biodiesel yield (95.7%) was obtained with the 8:1 methanol/oil ratio and 0.97% catalyst concentration at 55 °C reaction temperature for 70 min reaction time. A linear relationship was noted between the observed and predicted values. The characteristics of biodiesel produced in the present study as revealed by gas chromatography analyses confirmed the existence of four major fatty acid methyl esters (FAME) (oleic-, linoleic-, linolenic-, and palmitic-acids). The fuel properties of B. napus oil methyl esters, i.e., cetane number, kinematic viscosity, oxidative stability, cloud point, pour point, cold filter plugging point, flash point, ash and sulfur-contents, acid value, copper strip corrosion, density, and higher heating value, were determined, which were within the limit of biodiesel standards such as ASTM D6751 and EN 14214.
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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 | 0.000 | 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 | 0.001 | 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 it