Physiochemical characterization and support interaction of alumina‐supported heteropolyacid catalyst for biodiesel production
Bibliographic record
Abstract
Abstract 12‐Tungstophosphoric acid (TPA)‐supported γ‐Al2O3 catalysts were synthesized with varying TPA loadings. Catalysts characteristics were determined using Brunauer–Emmett–Teller surface area analysis, thermogravimetric analyses, X‐ray diffraction, Raman, pyridine‐adsorbed Fourier‐transform infrared spectroscopy, and 13C hpdec (high‐power 1H decoupling) nuclear magnetic resonance, whereas surface morphology was studied using scanning electron microscope and transmission electron microscopy analyses. Surface defects were found in the catalyst with higher TPA loadings (55–65 wt.%). The presence of WOx was observed at higher loadings and later agglomerated into tungsten oxide crystals. The TPA impregnated catalysts were investigated for biodiesel synthesis from canola oil. The reaction was found to be independent of mass transfer limitation. The activation energy was 33.6 kJ mol−1, and pre‐exponential factor was 7.3*10−2 min−1. The turnover frequency for the supported catalysts was found in the range of 9.7*10−4–8.8*10−2 min−1. A conversion of 94.9 ± 2.3% was obtained under the optimized conditions, that is, 10 wt.% of the catalyst loading, 17.5 methanol to oil molar ratio, 4 MPa, and at 200°C in 10 hr.
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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".