Chromophore Orientations in a Nonlinear Optical Azopolymer Diffraction Grating: Even and Odd Order Parameters from Far-Field Raman and Near-Field Second Harmonic Generation Microscopies
Bibliographic record
Abstract
A diffraction grating with a large diffraction efficiency (η = 25% on the first order) was inscribed on an azobenzene-containing polymer thin film, electrically poled, and characterized using spatially resolved Raman confocal microscopy and near-field scanning optical microscopy (NSOM) coupled with second-order nonlinear optical measurements. Linear (Raman) and nonlinear (second harmonic generation or SHG) polarized microscopic measurements were performed on a grating with ∼1.4 μm periodicity, revealing the molecular orientations in various regions of the sinusoidal relief surface. The most probable distribution functions f (θ) of the chromophore orientations were derived using the two first even parity Legendre polynomials 〈 P 2 〉 and 〈 P 4 〉 together with the two odd order parameters 〈 P 1 〉 and 〈 P 3 〉, as determined by Raman and SHG, respectively. These distribution functions show that the poling treatment is quite efficient and also emphasize the importance of determining both couples of the order parameters in such a surface-modulated optical element. In particular, new information is provided about the formation mechanism of the additional surface modulations of half periodicity that are revealed by the SHG-NSOM data but are not detected in the far-field Raman scattering measurements.
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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) | 0.000 | 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 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".