Biobased Antiviral Nonwoven Mask Filter with High Filtration Performance
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The COVID-19 pandemic has resulted in an increased demand of functional nonwovens for face mask applications. In this study, biobased nonwoven filters (NWFs) loaded with silver nanoparticles (AgNPs) were developed. The AgNPs were prepared by reducing Ag + with lignin extracted from Miscanthus × giganteus . The effects of AgNO 3 concentration, reaction time, and temperature on AgNP synthesis were studied using UV–vis spectroscopy. The AgNPs were incorporated into ethyl cellulose fibers through electrospinning. The resulting composite fibers were characterized by scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, and X-ray diffraction. The average diameter of AgNPs was 6.54 ± 2.3 nm, while the bead-free electrosopun fibers had diameters ranging from 153 to 184 nm. The filtration efficiency, pressure drop, and quality factor of the NWFs were tested against NaCl aerosol particles (≥0.3 μm). The NWF samples tested had filtration efficiency of higher than 99%, with pressure drop and quality factor values of 86.20–88.25 Pa and 0.0690–0.0772 Pa –1, respectively. The antiviral properties of the AgNP-loaded NWFs were evaluated against a surrogate virus, Pseudomonas bacteriophage Φ6, resulting in a 5 log 10 (PFU/mL) reduction beyond the starting viral titer. This study demonstrated the potential of the antiviral NWFs for high-performance mask filter applications.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".