Catalytic Vicinal Diacylation of Epoxidized Triglycerides in Canola Oil
Bibliographic record
Abstract
Abstract The epoxy ring opening and vicinal diacylation of fatty acids in vegetable oils was found to be promising reaction to synthesize stable biolubricants and bioplasticizers. The current research investigation is emphasized on the synthesis of a value added product vicinally diacylated canola oil by sulfated‐ZrO2. The two‐step research approach employed includes: (i) epoxidation, and (ii) epoxy ring opening and vicinal diacylation of epoxidized triglycerides in the canola oil. Sulfated‐ZrO2 was prepared and characterized to measure the physico‐chemical properties required for the effective catalysis. The Taguchi (L16 orthogonal array) statistical design method was employed to optimize the process conditions for the maximum formation of diacylated canola oil. Sulfated‐ZrO2 demonstrated promising activity for the epoxy ring opening and vicinal diacylation of canola oil, and 99 % conversion was achieved at the optimum process conditions of temperature 130 °C, epoxy to acetic anhydride molar ratio (1:1.25), 16 wt% of catalyst loading and reaction time of 1 h which were inferred from the Taguchi analyses. The products were characterized and confirmed with FT‐IR, 1H NMR and sodium spray mass spectroscopy. Spectroscopic analysis also confirmed the absence of intermediate products. The statistical analyses was undertaken to determine the order, rank and interactions among the process variables. The reaction followed Langmuir–Hinshelwood–Hougen–Watson type mechanism and the kinetic data was fitted in overall second order equation. Calculated apparent activation energy was 23.1 kcal/mol.
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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) | 0.000 | 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 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".