Stegeman figures for 3/sup rd/-order optical nonlinearity in hybrid semiconductor nanocrystal Qot-polymer film
Bibliographic record
Abstract
Summary form only given. To be useful in transmissive devices exploiting nonlinear phase change such as nonlinear directional couplers and optical limiters, the material must provide a /spl pi/ phase change before the optical power exciting the phase change is substantially absorbed. The Stegeman figures of merit W and T/sup 3/ quantify this requirement. The Stegeman figure of merit relating to linear absorption, T, has a substantial technological component inside inhomogeneous (hence scattering) materials, including the hybrid polymer-nanocrystal materials considered herein. We have sought new chemical routes to ensuring a uniform dispersion of nanocrystals inside the polymer even at high nanocrystal concentrations. We prepared CdS nanocrystals in aqueous solution using thiols as stabilizer. The nanocrystals were transferred from aqueous to organic phase, homogeneously mixed with PMMA, and processed into solid films. Measured fractional transmission and scattering spectra are shown for a 200 /spl mu/m thick film. In pure PMMA, absorption is strong only below 380 nm. Doping with semiconductor nanocrystals introduces strong absorption around 480 nm and below. Above 500 nm, scattering dominates loss. The decrease in scattered intensity with wavelength is consistent with Rayleigh scattering.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.099 | 0.010 |
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".