A Greener Way of Making Cellulose Clothing
Bibliographic record
Abstract
Cotton is the world's most demanding non-food crop. Cotton grows in arid countries such as India and China. However, its production consumes an enormous 250 billion tons of water annually, amplifying water scarcity. Cellulose, found in plants like wood, bamboo, and mosses, offers a sustainable alternative for textiles. Traditionally, cellulose is processed into textiles using the viscose method, which involves carbon disulfide. This process releases hydrogen sulfide, harmful to aquatic life and human health, and carbon disulfide, a hazardous pollutant affecting the reproductive system and vision. Many research groups have proposed an alternative method, which involves dissolving cellulose in dimethyl sulfoxide (DMSO) and Diazabicyclo[5.4.0]undec-7-ene (DBU) under 1 atm of CO2. DBU, with a pKaH ~ 12, deprotonates cellulose’s hydroxyl groups forming a DMSO-soluble cellulose carbonate complex that can be spun into filaments. However, DBU is costly, hazardous, and prone to hydrolysis, leading to byproducts. The objective of the research was to find a more environmentally friendly, less toxic, and cost-effective base for cellulose dissolution. Two tertiary amines, triethylamine (pKaH~9) and tripropylamine (pKaH~10.7), were tested. Due to its low basicity triethylamine failed to dissolve cellulose even under high CO2 pressure (up to 50 bar), resulting in a cloudy solution. Tripropylamine is insoluble in DMSO, therefore resulting in a phase separation of a tripropylamine layer and cellulose/DMSO layer. Additionally, 2,2,6,6-tetramethyl-piperidine was also tested at high CO2 pressure (up to 50 bar), but a biphasic solution was formed at 10 bar . This indicates that the protonated form of the base does not dissolve in DMSO. Ultimately, no alternative base was found to be sufficiently basic to deprotonate the hydroxyl groups on cellulose and promote dissolution, even at high pressure.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".