Biodiesel Production by Single and Mixed Immobilized Lipases Using Waste Cooking Oil
Bibliographic record
Abstract
Biodiesel is one of the important biofuels as an alternative to petroleum-based diesel fuels. In the current study, enzymatic transesterification reaction was carried out for the production of biodiesel from waste cooking oil (WCO) and experimental conditions were optimized, in order to reach maximum biodiesel yield. Bacillus stearothermophilus and Staphylococcus aureus lipase enzymes were individually immobilized on CaCO3 to be used as environmentally friendly catalysts for biodiesel production. The immobilized lipases exhibited better stability than free ones and were almost fully active after 60 days of storage at 4 °C. A significant biodiesel yield of 97.66 ± 0.57% was achieved without any pre-treatment and at 1:6 oil/methanol molar ratio, 1% of the enzyme mixture (a 1:1 ratio mixture of both lipase), 1% water content, after 24 h at 55 °C reaction temperature. The biocatalysts retained 93% of their initial activities after six cycles. The fuel and chemical properties such as the cloud point, viscosity at 40 °C and density at 15 °C of the produced biodiesel complied with international specifications (EN 14214) and, therefore, were comparable to those of other diesels/biodiesels. Interestingly, the resulting biodiesel revealed a linolenic methyl ester content of 0.55 ± 0.02% and an ester content of 97.7 ± 0.21% which is in good agreement with EN14214 requirements. Overall, using mixed CaCO3-immobilized lipases to obtain an environmentally friendly biodiesel from WCO is a promising and effective alternative for biodiesel production catalysis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".