Enhancement of fuel and physicochemical properties of canola residues via microwave torrefaction
Bibliographic record
Abstract
Conversion of low value agricultural residues to better-quality products e.g. biofuel, bioproducts can solve the issues related to energy crisis as well as environmental challenges. Torrefaction , a thermochemical pretreatment was employed on canola residue (CR) to augment the physicochemical properties of biomass for heat and energy applications . In the present study, the effects of microwave torrefaction on canola residue have been investigated for the following operating parameters: microwave power (250–450 W), residence time (10–20 min), and feeding load (70–110 g). Box Behnken design method was used to design the experiments and find the interaction between process parameters. Both mass and energy yields diminished with rise in microwave power and torrefaction reaction time. The results show that the carbon content significantly increased with degree of torrefaction while oxygen content had a reverse trend, therefore the atomic ratio of torrefied biomass reduced remarkably. Torrefied biomass shows higher carbon percentages than that for the bituminous coal . In addition, a noticeable decrease in volatile matter was observed with growth in torrefaction severity and thus increased fixed carbon content. The higher heating value (HHV) was boosted up by 26% (promoted from 17.8 MJ/kg to 22.4 MJ/kg). HHV of highly torrefied canola residue is very close to bituminous coal . Fourier transform infrared spectroscopy (FTIR) analysis showed that surface functional groups for example O H, C H, and C O decreased with torrefaction severity indicating the improvement of hydrophobicity of torrefied biomass. Scanning electron microscopy (SEM) results represent a more porous structure at highest torrefaction conditions which happened due to thermal cracking and decomposition of lignin and decreased the grinding energy by 89% compared to that for raw biomass . Moreover, inductively coupled plasma-mass spectrometry (ICP) analysis data showed that concentrations of minerals, alkaline and other essential element amplified with degree of torrefaction. The influence of microwave power was the highest on properties of torrefied biomass, followed by residence time and feeding load. The optimum torrefaction conditions were found at 450W with 90 g feeding load for residence time of 20 min.
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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".