Effect of ionic liquid pretreatment on lignocellulosic biomass from oilseeds
Bibliographic record
Abstract
In this study,three kinds of ionic liquid,including 1-butyl-3-methylimidazolium chloride([Bmim]Cl),1-butyl-3-methylimidazolium bromide([Bmim]Br)and 1-octyl-3-methylimidazolium chloride([Omim]Cl),were selected to pretreat the lignocellulosic parts of oilseeds:peanut husk,peanut straw and cole straw.The untreated and pretreated materials were investigated through the compositional,enzymatic hydrolysis and structural analysis.Among the untreated materials,peanut straw with the highest sugar yield 54.31% and the lowest lignin content was considered as the preferable substrate for biofuels production.After ionic liquid pretreatment,the effect of[Bmim]Cl on sugar yield was more significant, which lead to 85.43%sugar yield for peanut straw.The structural changes were also analyzed by scanning electron microscope(SEM)and Fourier transform-infrared(FT-IR).Among the raw materials,peanut straw's morphological structure was distinctive with broken surface,incompact structural and lower crystallinity.After pretreatment,all material turned to be more porous and rough than before.On the basis,the mechanism of lignocellulose's dissolution by ionic liquid with different cation and anion were also discussed. The results showed that the chlorine and[Bmim]+were vital on the effect of ionic liquid pretreatment.
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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".