Non-destructive quantification of alignment of nanorods embedded in uniaxially stretched polymer films
Bibliographic record
Abstract
Among several methods developed for uniaxial alignment of metallic nanorods for optical applications, alignment by film stretching consists in embedding the rods in a transparent thin film of thermoplastic polymer, followed by simultaneous heating and uniaxial stretching of the composite film. As to the quantification of the resulting alignment, it has been limited to statistical calculations based on microscopic examination, which is incomplete, subject to errors due to geometric distortions of the scanning electron microscope images and destructive, since it involves cutting of samples. In contrast, we present in this paper a non-destructive quantification of the average orientation of the rods, based on a probabilistic approach combined with numerical simulations of absorbance spectra and spectrometric characterization of the composite film. Assuming electromagnetically non-interacting rods, we consider the longitudinal absorbance peak of their ensemble to consist of the superposition of their individual spectra that we obtain by numerical simulation using the size and shape adapted dielectric function of the metal and the finite difference time domain method. The accuracy of the solution depends on the number of discretization intervals, the accuracy of the numerical simulations, and the accurate knowledge of the polydispersity of the rods. For the sake of concreteness, we used nanorods to describe the quantification steps but the method is equally valid for any dichroic particles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".