Lipase‐catalyzed hydrolysis of canola oil in supercritical carbon dioxide
Bibliographic record
Abstract
Abstract The effect of pressure, temperature, and CO2 flow rale on the extent of conversion and the product composition in the enzyme‐catalyzed hydrolysis of canola oil in supercritical carbon dioxide (SCCO2) was investigated using lipase from Mucor miehei immobilized on macroporous anionic resin (Lipozyme IM). Reactions were carried out in a continuous flow reactor at 10, 24, and 38 MPa and 35 and 55°C. Supercritical fluid chromatography was used to analyze the reaction products. A conversion of 63–67% (triglyceride disappearance) was obtained at 24–38 MPa. Mono‐and diglyceride production was minimum at 10 MPa and 35°C. Monoglyceride production was favored at 24 MPa. The amount of product obtained was higher at 24–38 MPa due to enhanced solubility in SCCO2. Complete hydrolysis of oil should be possible by increasing the enzyme load and/or decreasing the quantity of the oil substrate. There was a drop in triglyceride conversion over a 24‐h reaction time at 38 MPa and 55°C, which may be an indication of loss of enzyme activity. Pressure, temperature, and CO2 flow rate are important parameters to be optimized in the enzyme‐catalyzed hydrolysis of canola oil in SCCO2 to maximize its conversion to high‐value products.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".