Perylene Tetracarboxylic−Phthalocyanine Mixed Thin Solid Films. Surface-Enhanced Resonance Raman Scattering Imaging Studies
Bibliographic record
Abstract
The analytical application of surface-enhanced Raman scattering and surface-enhanced resonance Raman scattering (SERRS) in micro-Raman global imaging of mixed films is demonstrated by the use of laser powers below 1 mW and time acquisitions of a few seconds. SERRS eliminates the need for high-power lasers to record global images. Thin solid mixed films of phthalocyanine (chloroindium, chlorogallium, copper, cobalt, zinc, and metal-free phthalocyanine), bis( n -propylimido)perylene, and thio-bis( n -propylimido)perylene derivatives were fabricated by vacuum co-evaporation onto glass and silver island films. The spatial distribution or degree of mixing in the co-evaporated films on silver was probed by using SERRS. The micro-Raman spectra and images were recorded by using laser lines at 514.5, 633, and 780 nm. The monochromatic light, with frequency in and out of resonance with the dye's electronic absorption, allows selective observation of the corresponding material in the mixed film.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".