Pyrolysis of Lignins: Experimental and Kinetics Studies
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Bibliographic record
Abstract
Lignins are generally used as a low grade fuel in the pulp and paper industry. In this work, pyrolysis of Alcell and Kraft lignins obtained from the Alcell process and Westvaco, respectively, was carried out in a fixed-bed reactor and in a thermogravimetric analyzer (TGA) using helium (13.4 mL/min/g of lignin) and nitrogen (50 mL/min/g of lignin), respectively. The reaction temperature was increased from 300 to 1073 K, while the heating rates were varied from 5 to 15 K/min. The gaseous products mainly consisted of H 2, CO, CO 2, CH 4, and C 2+ . With increase in heating rate from 5 to 15 K/min both lignin conversion and hydrogen production increased from 56 to 65 wt % and from 25 to 31 mol %, respectively for fixed-bed pyrolysis reaction of Alcell lignin at 1073 K, whereas at the same condition the conversion and hydrogen production increased from 52 to 57 wt % and from 30 to 43 mol % for Kraft lignin. The distributed activation energy model (DAEM) was used to analyze complex reactions involved in the lignin pyrolysis process. In this model, reactions are assumed to consist of a set of irreversible first-order reactions that have different activation energies. This model was used to calculate the activation energy, E, the distribution of activation energy f ( E ), and the frequency factor k 0 for the pyrolysis of Alcell and Kraft lignins in a thermogravimetric analyzer (TGA). For the pyrolysis in TGA, the activation energies for Kraft and Alcell lignins varied from 129 to 361 kJ/mol with maximum distribution at ∼250−270 kJ/mol and from 80 to 158 kJ/mol with maximum distribution at ∼118−125 kJ/mol, respectively.
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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 it