Microwave effect on kinetics of paper cups pyrolysis
Bibliographic record
Abstract
Abstract Not only are microwaves notorious in food heating, but they exhibit interesting properties in different domains including chemical engineering. Their ability to concentrate heat transfer inside dielectric materials enhances process efficiency and permits high heating rates. Nonetheless, their effect on reactions is still controversial. While some researchers believe in non‐thermal effects due to the efficient conversion of microwave energy to enhance reactions without heat dissipation, others assert that microwave frequencies are not high enough to excite molecular bonds. In this study, paper cups pyrolysis is achieved in electrical and microwave TGA using two heating modes. The effect of microwaves on the kinetics of paper cups pyrolysis is shown to depend on the heating regime: at a moderate heating rate, microwave pyrolysis started at a lower temperature, while the pyrolysis in the electrical and microwave TGA have similar kinetic parameters at high heating conditions. This difference is linked with reaction mechanisms. At moderate heating conditions, cellulose decomposes first to an intermediate compound then to final products. The intermediate has a short reaction time and interacts with the microwave. Hence, hot spots at the molecular scale are generated in a short amount of time below the detectable limits of existing temperature measurements media. At a high heating rate, the decomposition of cellulose is direct and no effect is observed.
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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 | 0.001 |
| 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) | 0.003 | 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".