Kinetics of transesterification reaction using CAO/AL<sub>2</sub>O<sub>3</sub> catalyst synthesized by sol‐gel method
Bibliographic record
Abstract
Calcium oxide is one of the appropriate catalysts for biodiesel production. In this study, 40 wt. % CaO/Al2O3 catalyst was used. Transesterification reaction was performed in optimal condition presented in the previous study (0.05 molar nitric acid and gelation temperature of 70 °C) in a 250 mL two‐necked flask. All the experiments were carried out in the presence of soybean oil, methanol (methanol to oil molar ratio of 12:1), and catalyst concentration of 6 wt. %. Stirrer speed was set at 350 rpm. This study investigated the effects of reaction temperature and reaction time on produced biodiesel conversion. Methyl ester conversion changes in all temperatures and across different times indicated pseudo‐first order kinetic, so, first, the observed rate constant was obtained at various temperatures. Then, observed activation energy of soybean oil methanolysis in the presence of CaO/Al2O3 catalyst was determined. The results show that maximum errors of model are in primary times because methanol is insoluble in soybean oil. At the other times and by biodiesel and glycerol production, there was increased solubility of methanol in oil. The methyl esters production rate is related to diffusion of methanol in oil film and reaction rate constants which are calculated these constants.
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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) | 0.001 | 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".