An overview of cotton and polyester, and their blended waste textile valorisation to value-added products: A circular economy approach – research trends, opportunities and challenges
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fast-changing fashion trends have resulted in increases in textile production and waste generation. The environmental impacts of the production, consumption and end-of-life of textiles are amply documented. Therefore, the industry has started to shift from the linear economy principle of ‘take-make-waste’ to the circular economy concept, where textiles can reenter the life cycle rather than being wasted and thus form a closed loop, resulting in resource savings and reduced environmental impacts. To this end, valorization of solid waste streams from the textile industry to recover fibers and marketable value-added products has gained increasing attention in recent years. Textile waste valorization involves three main steps: pretreatment, enzymatic hydrolysis and fiber regeneration. This review presents the main methodologies and the most recent technical developments in these valorization strategies, the value-added products obtained and their applications. Furthermore, the review describes fermentative products synthesized using cellulosic glucose from the cotton fraction of waste streams. Gaps and challenges in existing strategies are identified for potential future research. This review will help to apprize researchers and practitioners of important recent developments in effective textile valorization via upcycling and guide them in the design of efficient strategies for sustainable management of textile waste streams.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it