Use of CdS quantum dot-functionalized cellulose nanocrystal films for anti-counterfeiting applications
Bibliographic record
Abstract
Structural colors and photoluminescence have been widely used for anti-counterfeiting and security applications. We report for the first time the use of CdS quantum dot (QD)-functionalized cellulose nanocrystals (CNCs) as building blocks to fabricate nanothin films via layer-by-layer (LBL) self-assembly for anti-counterfeiting applications. Both negatively- and positively-charged CNC/QD nanohybrids with a high colloidal stability and a narrow particle size distribution were prepared. The controllable LBL coating process was characterized by scanning electron microscopy and ellipsometry. The rigid structure of CNCs leads to nanoporous structured films on poly(ethylene terephthalate) (PET) substrates with high transmittance (above 70%) over the entire range of visible light and also resulted in increased hydrophilicity (contact angles of ∼40 degrees). Nanothin films on PET substrates showed good flexibility and enhanced stability in both water and ethanol. The modified PET films with structural colors from thin-film interference and photoluminescence from QDs can be used in anti-counterfeiting applications.
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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) | 0.000 | 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) | 0.001 | 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".