Preparation and characterisation of Cao nanoparticle for biodiesel production from mixture of edible and non-edible oils
Bibliographic record
Abstract
Calcium nitrate (CaO/CaN) and snail shell (CaO/SS) were successfully utilised for the development of CaO nanoparticle and used in biodiesel synthesis from a mixture of edible and non-edible oils. These solid base heterogeneous catalysts were characterised by FT-IR, XRD, and TGA techniques. Debye-Scherer equation also calculated the average crystalline size of a nanometer. The comparable catalytic activity of CaO/CaN and CaO/SS catalyst was also studied for biodiesel production and found the increment of biodiesel yield from 88% to 92% using CaO/SS. The used optimum reaction conditions were: 6 wt% catalyst loading, 65°C reaction temperature, 12:1 methanol: oil molar ratio and four hr of reaction time. This research shows that developed basic nano catalyst from snail shell exhibit good catalytic activity. Five reusability runs were also done and found that no loss of catalytic activity up to five runs.
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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".