Grindability of Torrefied Camelina Straw and Microparticle Evaluation by Confocal Laser Scanning Microscopy for Use as Biofuel
Bibliographic record
Abstract
This study examined the combined effect of torrefaction and microwave absorbers on improving biomass thermochemical characteristics and grindability for heat, power, and value-added products. Camelina straw in two grinds, ground (6.4 mm screen size) and chopped with biochar addition (0%, 10% and 20%), was torrefied in a bench-scale microwave reactor at torrefaction temperatures of 250 °C and 300 °C with residence times of 10, 15 and 20 min under inert conditions and nitrogen-activated. After torrefaction, the geometric mean particle and size distribution, moisture content, ash content, bulk and particle densities were determined, and the grinding performance values of torrefied ground and chopped with and without biochar were determined and compared with the raw camelina straw. The results showed that the geometric diameter decreased after torrefaction in both grinds. The specific energy required for grinding torrefied biomass decreased significantly with biochar addition, longer residence times, and increased torrefaction temperatures. Torrefied ground camelina straw with biochar after grinding had the lowest grinding energy of 34.30 kJ at 300 °C/20 min. The surface morphology by confocal laser scanning microscopy of torrefied camelina straw particles indicated that biochar addition (>10%) and a torrefaction temperature at 250 °C can create profound surface distortion, and beyond 300 °C, colossal surface damage and carbonized weight fractions were produced.
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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".