Ultraviolet protection and antibacterial properties of textile fabric made of silver nanoparticles/alkaline lignin/regenerated cellulose fiber
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
Regenerated cellulose fibers (e.g., viscose, modal) and natural cotton fibers remain dominant in summer textile production owing to their inherent softness, breathability, and moisture absorption. Nevertheless, their limited ultraviolet (UV) resistance and proneness to microbial colonization restrict extended applications. To address these limitations, we developed a novel regenerated cellulose-based composite fiber incorporating silver nanoparticles (AgNPs) and alkaline lignin (AL) through a wet-spinning approach. The synthesis process involved dissolving AL and cotton cellulose (CC) in an N,N-dimethylacetamide/lithium chloride (DMAc/LiCl) solution, followed by wet spinning to produce AL/CC fibers. Subsequently, AgNPs were in situ synthesized on the surface of the AL/CC-g fibers, resulting in Ag/AL/CC-g fibers. The structural, chemical composition, and thermal stability of the Ag/AL/CC-g fibers were characterized through XPS, SEM, DSC, TG. The Ag/AL/CC-g fibers exhibited good antibacterial activity, achieving a > 99.99 % reduction rate against both E.coli and S.aureus. The UV-blocking capability of Ag/AL/CC-g fabric (woven from Ag/AL/CC-g fibers) was evaluated, revealing a direct correlation between AL content and UV absorption. Notably, the Ag/AL/CC-g fabric(with 46 % AL and 7 % AgNPs) demonstrated “excllent” UV protection, achieving a UPF value exceeding 40, according to the European standard(EN 13758–2).This study presents a novel and effective approach to fabricating cellulose-based textiles with dual functionality—enhanced UV resistance and robust antibacterial properties—expanding their potential applications in high-performance summer apparel and medical textiles.
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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 | 0.000 | 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) | 0.000 | 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