Kinetics of Canola Oil Transesterification in a Membrane Reactor
Bibliographic record
Abstract
Biodiesel is quickly gaining attention as a renewable and environmentally friendly replacement for petroleum-based diesel. The dominant process involved in its production is transesterification consisting of three consecutive reversible reactions. For this work, the transesterification of canola oil was conducted using a continuous membrane reactor in the presence of NaOH as a catalyst. The forward and reverse rate constants of all three steps involved in the transesterification in the membrane reactor are reported. The proposed mathematical model fitted the experimental results well. It was found that increasing the catalyst concentration increased the reaction rates and the residence time did not have a significant influence on the reaction rates. Runs were performed at 0.05, 0.1, and 0.5 wt % NaOH based on the oil. A mole ratio of 24:1 methanol/oil was used in this work. The forward rate constants were greater than previously reported for a batch process. This was attributed to the excellent mixing in the membrane reactor loop, the higher methanol/oil mole ratio used here, and the continuous removal of product from the reaction medium. The advantages of using a membrane rector to enhance the reaction rate in the transesterification of canola oil in a membrane reactor were clearly shown.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".