Novel Insights into the Kinetics, Evolved Gases, and Mechanisms for Biomass (Sugar Cane Residue) Pyrolysis
Why this work is in the frame
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Bibliographic record
Abstract
Biomass, a renewable energy source, via available thermo-chemical processes has both engineering and environmental advantages. However, the understanding of the kinetics, evolved gases, and mechanisms for biomass pyrolysis is limited. We first propose a novel temperature response mechanism for the pyrolysis of sugar cane residue using thermogravimetric analysis-Fourier transform infrared spectrometry-mass spectrometry (TG-FTIR-MS) combined with Gaussian model and two-dimensional correlation spectroscopy (2D COS). The existence and contribution of distinct peaks in TG-FTIR spectra were innovatively distinguished and quantified, and the temperature-dependent dynamics of gas amounts were determined using Gaussian deconvolution. The 2D-TG-FTIR/MS-COS results revealed for the first time that the primary sequential temperature responses of gases occurred in the order: H2O/CH4 > phenols/alkanes/aromatics/alcohols > carboxylic acids/ketones > CO2/ethers > aldehyde groups/acetaldehyde. Subtle sequential changes even occurred within the same gases during pyrolysis. The quantity dynamics and sequential responses of gases were fitted to the combined effects of the order-based, diffusion, and chemical reaction mechanisms for the component degradation. The combination of TG-FTIR-MS, Gaussian model, and 2D COS is a promising approach for the online monitoring and real-time management of biomass pyrolysis, providing favorable strategies for pyrolysis optimization, byproduct recovery, energy generation, and gas emission control in engineering and environmental applications.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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