Pelletization and quality evaluation of torrefied selected biomass with microwave absorber
Bibliographic record
Abstract
Camelina straw and switchgrass are herbaceous biomass feedstock for biofuel production, and they can be produced in large quantities in North America. The current study investigated the pelleting of optimized microwave torrefied camelina straw and switchgrass with and without biochar and high-density polyethylene (HDPE) as a binder during densification. The primary research focused on the influence of the binder levels (0, 10, and 25 wt.%) added to the torrefied biomass on pellet quality. The addition of 25 wt.% HDPE significantly improved pellet characteristics, such as pellet density, dimensional stability, tensile strength, durability, and the effects of interparticle interaction on pellet properties. The pelleting conditions were optimized and validated using the torrefaction treatment conditions: microwave power 520 W, biochar 20 wt.%, residence time of 20 min, and binder level of 25 wt.% HDPE. The X-ray photoelectron spectroscopy (XPS) analysis of the pellet ash revealed that adding HDPE increased the carbon and decreased the oxygen contents. Thus, the oxygen/carbon ratio had similarities to ash from the XPS and elemental analysis results and exhibited uniform chemical properties between the ash surface and torrefied yield fraction ash. The torrefied camelina straw and switchgrass with and without biochar/HDPE pellet ash characteristics indicated a strong potential for using these herbaceous biomass for heat production and electricity generation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".