Torrefaction of Barley Straw for the Co-Production of Energy and Adsorbent Materials
Bibliographic record
Abstract
The purpose of this study was first to examine and then to maximize, the adsorbency of torrefied barley straw, in order to remove basic dyes like Methylene Blue (MB) from wastewater.On the other hand, the effect of the torrefaction process on the heating value of the material was investigated.Moderate modification conditions (220 ºC, 20 min) were found to maximize adsorbency of modified barley straw.The experimental data were simulated by a pseudo-second order kinetic model.The torrefaction also significantly enhanced the higher heating value of the pretreated barley straw compared to the untreated material.Specifically, the calorific value increased from 16.1 MJ/kg to 19.4 MJ/kg for sample torrefied at 240 ºC during 40 min.Consequently, the torrefaction of barley straw leads to the coproduction of material with enhanced energy content in combination with improved adsorption capacity.The coproduction of energy and adsorbents from lignocellulosic biomass takes into account (i) the biorefinery (more than one product) and (ii) the Industrial Ecology concept (using solid waste to clean wastewater pollution).
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".