Depth Profiling of the Optical Absorption Coefficient in Ultraviolet-Degraded Poly(Vinylchloride) Films by Dual Beam Light Profile Microscopy
Bibliographic record
Abstract
Dual beam laser light profile microscopy (LPM) was applied in this work to the depth mapping of the optical absorption coefficient in photo-degraded poly(vinyl chloride) films. Depth profiles followed the absorption coefficient of a conjugated polyene photoproduct at visible wavelengths in photolyzed films of approximately 200 mum thickness. Both continuous and layered (separable laminate) films were studied. The absorption coefficient profiles reconstructed from photo-degraded thin films showed the classic concentration profiles seen in the literature for PVC degraded in the presence of oxygen and nitrogen atmospheres. In the case of single thin layers with continuous properties, the depth profiles were smooth and regular with minimum spatial noise. In the LPM of laminate structures, more optical anomalies were present because of the multiply interfacial structures that appeared in both the images and the reconstructed depth profiles. Notwithstanding, it was possible to profile the optical absorption coefficient at a level of error comparable to standard microtome methods. The latter was determined by comparing the LPM results to a destructive layer-by-layer analysis performed in parallel on the imaged materials. The dual beam LPM method should be generally useful for establishing polyene concentration profiles in industrial materials produced by photochemical, thermal, and chemical degradation mechanisms.
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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 | 0.001 | 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) | 0.001 | 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".