Production of cycloalkane-rich fuel by vacuum pyrolysis of mixed waste plastics using combined titanium and aluminum oxide: a preliminary investigation
Bibliographic record
Abstract
The mitigation of plastic pollution constitutes one of the major challenges worldwide. Innovative research approaches have been solicited to improve the properties of fuel derived from plastic pyrolysis. The present study looks at the effect on the chemical composition of pyrolysis oil of the application in situ of a mixed metal oxide of titanium and aluminum in vacuum pyrolysis of mixed waste polyethylene, polypropylene, and polyethylene terephthalate. The experiment was performed at process parameters of 250 °C temperature, 79.9 Kpa vacuum pressure, and 1:10 catalyst-to-feedstock ratio, first without the mixed metal oxide (parent reaction) and then with the mixed metal oxide (modified reaction). The results showed that the presence of combined titanium and aluminum oxides in the reaction medium accounted for the presence of alkyl-substituted cycloalkanes at an area% of 33.97% in the liquid product, and a calorific value of 11,950 cal/gm was reported for the modified reaction. The parent reaction produced higher liquid and gaseous yields of 28.3% and 43.1% respectively while the modified reaction produced a greater percentage of char (23.8%) and residual wax(36.0%). The fuel properties of the liquid products obtained were equally determined.
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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".