Water-stable, biocompatible, and highly luminescent perovskite nanocrystals-embedded fiber-based paper for anti-counterfeiting applications
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
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
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 | 0.000 | 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