Synthesis, characterization, and performance of x_MoO <sub>3</sub> /Z‐22 and x_MoO <sub>3</sub> / <scp>MMP</scp> catalysts for biodiesel production
Bibliographic record
Abstract
Abstract The growing global demand for renewable fuels has driven the search for efficient catalysts in biodiesel production. This study presents the synthesis and characterization of x_MoO 3 /Z‐22 and x_MoO 3 /MMP heterogeneous catalysts, and evaluates the effects of process variables on biodiesel yield through statistical analysis. The micro‐mesoporous catalyst MMP was prepared using Z‐22 zeolite as a seed, while molybdenum trioxide was incorporated via incipient impregnation using ammonium heptamolybdate. X‐ray diffraction (XRD) confirmed the presence of crystalline phases associated with both the zeolite and molybdenum oxides. NH 3 ‐temperature‐programmed desorption (NH 3 ‐TPD) revealed that increasing MoO 3 content in x_MoO 3 /MMP enhanced total acidity, attributed to a higher concentration of active species on the catalyst surface. The highest fatty acid methyl ester (FAME) yield (99%) was obtained with the 15_MoO 3 /MMP catalyst under optimized conditions: an oil‐to‐alcohol molar ratio of 20:1, temperature of 150°C, and reaction time of 3 h. Statistical analysis based on a factorial experimental design demonstrated that MoO 3 loading (wt.%) and reaction time were the most statistically significant factors ( p < 0.05) influencing biodiesel yield.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".