Qualitative and kinetic analysis of torrefaction of lignocellulosic biomass using DSC-TGA-FTIR
Bibliographic record
Abstract
Torrefaction is a thermochemical conversion technique to improve the fuel properties of lignocellulosic biomass by treating at temperature 200 ℃-300 ℃ in the minimum oxygen environment for a reasonable residence time. In this study, thermal decomposition and thermal activities of miscanthus and wheat straw during the torrefaction at 200 ℃, 275 ℃, and 300 ℃ in a nitrogen environment for 45 minutes of residence time are analyzed in a simultaneous thermogravimetric analyzer (micro TGA) with a differential scanning calorimetry (DSC), and a macro-TGA. The output of the micro TGA is fed into the Fourier transform infrared spectrometry (FTIR) and qualitative analysis of the gaseous product is carried out. The composition of different gas products during the torrefaction of biomass are compared critically and kinetics were analyzed. It is found that the weight loss due to degradation of initial biomass in second stage (torrefaction process) is a much faster conversion process than the weight loss process in the first stage (drying process). The weight loss of biomass increases with increase in the residence time and torrefaction treatment temperatures. The yield after torrefaction is a solid bio-coal product. The torrefied product were less reactive and has nearly 25% better heating value than the raw biomass. Between the two feedstocks studied, torrefied miscanthus proved to be a more stable fuel than the torrefied wheat straw. The major gaseous components observed during torrefaction are water, carbon dioxide, carbon monoxide, 1,2-Dibromethylene.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".