TPA Supported on SBA-15 as Solid Acid Catalysts for the Biodiesel Production
Bibliographic record
Abstract
Biodiesel has gained worldwide recognition for many years due to its renewability, lubricating property and environmental benefits. This research is focused on synthesis of 12-Tungstophosphoric acid (TPA) supported on SBA-15 as acid catalysts for the biodiesel production from a model feedstock Triolein. A large number of 0-35% TPA supported on SBA-15 catalysts were synthesized by impregnation method and the catalysts were characterized using BET, XRD, FTIR, TEM and ICP-MS. The catalytic activity of these catalysts was tested by transesterification of Triolein using a stirred tank reactor. The effect of operating conditions such as catalyst conc. and methanol to Triolein molar ratio on the transesterification of Triolein was studied using response surface methodology (RSM). Based on the study, 25% TPA is identified as the optimum catalyst loading on SBA-15 by impregnation. From the optimization study of 25% TPA impregnated SBA-15 using RSM model, 4.15 wt% catalyst (based on Triolein) and 39:1 methanol to Triolein molar ratio is found to be the optimum reaction condition, when the reaction temperature is kept fixed at 200°C, stirring speed at 600 rpm and allowing 10-h of reaction time. Predicted ester yield at the above condition is 97.4 %, and the actual (experimental) yield is 97.2%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".