Investigation of Lipase-Catalyzed Biodiesel Production Using Ionic Liquid [BMIM][PF<sub>6</sub>] as a Co-solvent in 500 mL Jacketed Conical and Shake Flask Reactors Using Triolein or Waste Canola Oil as Substrates
Bibliographic record
Abstract
The production of biodiesel was investigated using a lipase-catalyzed (Novozym 435) reaction involving methyl acetate and ionic liquid [BMIM][PF6] as a co-solvent. The use of a lipase catalyst removed the need for alkali wastewater removal and treatment, and the methyl acetate and ionic liquid helped prevent deactivation and improve activity and stability of the lipase, respectively. Experiments were carried out in shake flask and jacketed conical reactors. Runs performed in shake flask reactor produced similar fatty acid methyl ester (FAME) yields to previous work using a small-scale reactor (83%), indicating that the reaction can achieve high yields provided that sufficient mixing between the oil and ionic liquid phases occur. The highest yield achieved in the conical reactor was 54% because of the relatively poor mixing in the reactor as a result of two phases present in the mixture. An additional benefit of using ionic liquid as a co-solvent in the process was for its ease of separation of products. Two distinct phases were present at the end of the reaction, with the ionic liquid phase containing the triacetylglycerol byproduct and any unreacted methyl acetate. The byproduct was then separated by washing with water, and the ionic liquid was removed by decantation and reused. FAMEs were also successfully produced from waste canola oil, with a 72% yield achieved in a small-scale reactor and a 30% yield in a 500 mL jacketed conical reactor.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".