Conversion of waste‐soap and soap‐like materials into diesel and gasoline by catalytic pyrolysis using virgin soap as model
Bibliographic record
Abstract
Abstract In this work, soap was converted into a hydrocarbon‐rich product through catalytic pyrolysis using cement as a catalyst. The intention was to develop a new economical and effective method for preparing diesel and gasoline from soap waste in food processing. The optimum conditions for pyrolysis were investigated in a batch process under static conditions at different reactor temperatures, catalyst amounts, and reaction durations. The resulting oil product was analyzed using GC‐FID, GC‐MS, and FTIR. The best yield occurred at a reaction temperature of 400 °C for 60 min with 0.3 g/g (30 mass%) catalyst in soap waste, which resulted in 0.71 g/g (71 mass%) hydrocarbons with small fractions of pyran, ketone, and oxygenated compounds of mixed functional groups. The resulting liquid pyrolysate mainly consisted of diesel‐like oil with a small fraction of gasoline and some oils that had boiling‐point temperature ranges similar to kerosene.
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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".