Synthesis and Performance of Sulfated Zirconia Catalyst in Esterification of Oleic Acid
Bibliographic record
Abstract
In this work, the performance of sulfated zirconia catalyst used in the synthesis of biodiesel by esterification of oleic acid was studied. For catalyst preparation the zirconium dioxide (ZrO) by Aldrich was used as precursor. The sulfated zirconia obtained was calcined for 3 hours at different temperatures (200, 400, 600 and 700 °C) in an oxygen atmosphere. Each of the calcination conditions generated a sample of catalyst, which was used in the esterification reaction. The esterification reaction was carried out using reagents such as oleic acid and methanol at a molar ratio 1:20. The sulfated zirconia catalyst was used in the reaction in various proportions by weightrelative to the weight of oleic acid (0.5, 1.0, 3.0 and 5%). The analysis of methyl ester conversion was performed by gas chromatography and mass spectrometry (CGMS) and the percentage area of the characteristic peaks as methyl oleate was quantified. A characterization of sulfated zirconia was also performed using scanning electron microscopy (SEM) and X-ray diffraction (XRD). Finally, the catalyst performance was studied in the reduction of the acid index (AI) and the conversion of free fatty acids of oleic acid and compared to other commonly used catalyst for this purpose, which is concentrated sulfuric acid (H2SO4).
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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 | 0.001 | 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".