Water-stable, biocompatible, and highly luminescent perovskite nanocrystals-embedded fiber-based paper for anti-counterfeiting applications
Bibliographic record
Abstract
Abstract In this study, we present a promising and facile approach toward the fabrication of non-toxic, water-stable, and eco-friendly luminescent fiber paper composed of polycaprolactone (PCL) polymer and CsPbBr 3 @SiO 2 core–shell perovskite nanocrystals. PCL-perovskite fiber paper was fabricated using a conventional electrospinning process. Transmission electron microscopy (TEM) clearly revealed incorporation of CsPbBr 3 @SiO 2 nanocrystals in the fibers, while scanning electron microscopy (SEM) demonstrated that incorporation of CsPbBr 3 @SiO 2 nanocrystals did not affect the surface and diameter of the PCL-perovskite fibers. In addition, thermogravimetric analysis (TGA) and contact angle measurements have demonstrated that the PCL-perovskite fibers exhibit excellent thermal and water stability. The fabricated PCL-perovskite fiber paper exhibited a bright green emission centered at 520 nm upon excitation by ultra-violet (UV) light (374 nm). We have demonstrated that fluorescent PCL-perovskite fiber paper is a promising candidate for anti-counterfeiting applications because various patterns can be printed on the paper, which only become visible after exposure to UV light at 365 nm. Cell proliferation tests revealed that the PCL-perovskite fibers are cytocompatibility. Consequently, they may be suitable for biocompatible anti-counterfeiting. The present study reveals that PCL-perovskite fibers may pave way toward next generation biomedical probe and anti-counterfeiting applications. Graphical Abstract
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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) | 0.001 | 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) | 0.001 | 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".