A kinetics study of microwave pyrolysis of sewage sludge and corn stalk mixture
Bibliographic record
Abstract
Abstract Fast pyrolysis of sewage sludge (SS), corn stalk (CS), and their mixture under both direct and indirect microwave heating was carried out in a prototype microwave thermogravimetric reactor at high heating rates, 179 and 203 K/min, respectively. It was found that the samples could be heated up rapidly by direct microwave heating, while there is a temperature lag of the sample to the heated reactor wall in indirect heating. The Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) methods were used to analyze the thermogravimetric data of SS, CS, and their mixture under direct microwave heating. When the FWO method was used, the average activation energies of SS, CS, and their mixture were obtained as 6.0, 18.9, and 39.8 kJ/mol, respectively. When the KAS method was used, the average activation energies of CS and mixture were 12.6 and 31.6 kJ/mol, respectively. Those values are much lower than reported under conventional heating, and likely result from the interaction of microwave irradiation and the biomass samples. The reaction kinetics of directly microwave‐heated biomass pyrolysis from this study provide essential data for modelling, scaling, and designing the microwave‐assisted in‐situ catalytic pyrolysis reactors with mixed biomass and catalyst particles.
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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".