Dynamic anti-counterfeiting security features using multicolor dianthryl sulfoxides
Bibliographic record
Abstract
A new concept for difficult-to-replicate security inks for use in advanced anti-counterfeiting applications is presented. Inks fabricated from a mixture of photoactive dyes result in a unique fluorescent color upon irradiation that differs from the starting fluorescence. The dyes are substituted 9,9'-dianthryl sulfoxides that undergo photochemical extrusion of a sulfoxide moiety (SO) to produce emissive red, blue, and green emitters. The resulting emissive feature has specific Commission international de l'éclairage (CIE) coordinates that are used for authentication. Additionally, the temporal evolution of the fluorescence can be monitored, introducing a dynamic nature to these security features. The three compounds show different rates of photoconversion dependent on the irradiation wavelength, allowing selective wavelengths for activation to be used for additional security. CIE coordinates can be extracted from patches containing the three compounds using an inexpensive, commercially available smartphone application (app) and compared against a known value to confirm the validity of the method.
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.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".