Investigation of the Effects of Ionic Liquid 1-Butyl-3-methylimidazolium Acetate Pretreatment and Enzymatic Hydrolysis of Typha capensis
Bibliographic record
Abstract
Pretreatment of Typha capensis (TC) with ionic liquid (IL) 1-butyl-3-methylimidazolium acetate [BMIM(OAc)] shows that the structural integrity-like degree of polymerization, polydispersity index, and lignin were altered, providing easy access to enzymes, and improved its digestibility to fermentable sugars. Hydrolysis of pretreated samples by a pre-optimized mixture of cellulose enzymes achieved an optimal reducing sugar yield (RSY) of 82.4 g/100 g after 6 h of pretreatment incubation. Because the costs of ILs are high, pre-hydrolysis and recycling are used to improve the economics. Pre-hydrolysis steps using sodium hydroxide followed by IL treatment were found to be better than sulfuric acid pre-hydrolysis followed by IL. Pre-hydrolysis treatment with alkali reduced pretreatment time from 6 h to 15 min, and total solid (TS) was increased from 5 to 10% without significant reduction in the glucose and RSYs. During solvent recycling, about 10% of initial lignin at each cycle was being accumulated into the liquid stream containing the IL, with minimal traces of carbohydrates. Treatment of the recycled IL at 10th and 15th cycles enabled recovery of about 93% of the IL-soluble lignin released into the liquid stream and improved the effectiveness of pretreatment. The investigation reveals the possibility of improving IL pretreatment outcome by increasing the TS through NaOH pre-hydrolysis. With the possible recycling of the IL up to 15 cycles, the overall costs of using this procedure are considerably reduced.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".