Synthesis of Biodiesel from Canola Oil Using Heterogeneous Base Catalyst
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A series of alkali metal (Li, Na, K) promoted alkali earth oxides (CaO, BaO, MgO), as well as K 2 CO 3 supported on alumina (Al 2 O 3 ), were prepared and used as catalysts for transesterification of canola oil with methanol. Four catalysts such as K 2 CO 3 /Al 2 O 3 and alkali metal (Li, Na, K) promoted BaO were effective for transesterification with >85 wt% of methyl esters. ICP‐MS analysis revealed that leaching of barium in ester phase was too high (~1,000 ppm) when BaO based catalysts were used. As barium is highly toxic, these catalysts were not used further for transesterification of canola oil. Optimization of reaction conditions such as molar ratio of alcohol to oil (6:1–12:1), reaction temperature (40–60 °C) and catalyst loading (1–3 wt%) was performed for most efficient and environmentally friendly K 2 CO 3 /Al 2 O 3 catalyst to maximize ester yield using response surface methodology (RSM). The RSM suggested that a molar ratio of alcohol to oil 11.48:1, a reaction temperature of 60 °C, and catalyst loading 3.16 wt% were optimum for the production of ester from canola oil. The predicted value of ester yield was 96.3 wt% in 2 h, which was in agreement with the experimental results within 1.28%.
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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 it