Bibliographic record
Abstract
Cellulose pyrolysis is an important area in biomass thermochemical conversion. Developing advanced pyrolysis technology requires basic understanding of chemical kinetics. This paper deals with the improvement of the kinetic model for cellulose pyrolysis. To study this process, intensive reviews, calculations, comparisons and analyses were carried out based on the well known Broido Shafizadeh kinetic model. An improved kinetic model of cellulose pyrolysis was proposed. First, the validity of the kinetic data on competitive reactions in Broido Shafizadeh model was checked. Through analyses and comparisons, a new kinetics model was developed to overcome the error caused by heat and mass transfer limitation in the parameter deduced experiment. Then, the so called 'active cellulose' was examined. The appearance of liquid 'active cellulose' during pyrolysis was analyzed on the basis of modelcalculation and shown to be important in the case of high heating rate pyrolysis processes and should be considered in the improved kinetic model. At last, the secondary reaction of volatile components was added as a part of the kinetic model. Relevant kinetic data were chosen from literature. The proposed kinetic model for cellulose pyrolysis is a step toward the reality and will certainly benefit further study on cellulose pyrolysis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".