Application of optical microscopy as a screening technique for cellulose and lignin solvent systems
Bibliographic record
Abstract
Abstract Rapid and facile screening techniques to determine the effectiveness of solvents for cellulose or biomass dissolution can advance biomass processing research. Here, we report the use of a simple optical microscopy method to screen potential cellulose and lignin solvents. The described methodology was used to screen the dissolution of cellulose and lignin in two imidazolium‐based ionic liquids (ILs), two phosphonium‐based ILs, as well as a N,N‐dimethylacetamide/lithium chloride (DMAc/LiCl) solution in less time than other techniques. The imidazolium‐based ILs and the DMAc/LiCl were found to dissolve both cellulose and lignin. Also, it was observed that one of the phosphonium‐based ILs dissolved lignin and not cellulose, demonstrating a potential for biomass fractionation applications. © 2011 Canadian Society for Chemical Engineering
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".