Terahertz field depolarization and absorption within composite media
Bibliographic record
Abstract
In this work, we pursue a deeper understanding of the expression of the inclusion morphology and index contrast in the refraction and absorption characteristics of composites within the terahertz (THz) spectrum. The composites are composed of SiO2 and Si nanoparticles as well as SiO2 and Si microparticles functioning as deeply subwavelength inclusions in a polydimethylsiloxane (PDMS) host. Terahertz time-domain spectroscopy is used for experimental characterization of the composites over a wide range of volumetric fractions, and the trends that emerge are contrasted to theoretical predictions from the Bruggeman model. It is found that the refraction characteristics have a heightened dependence on the inclusions' shape when their index contrast with respect to the host becomes sufficiently large. We attribute such a correlation to terahertz field depolarization that occurs within inclusions at high index contrasts and the dependence of the fields to the inclusions' shape—as defined by a depolarization factor in the generalized form of the Bruggeman model. Moreover, it is found that the absorption characteristics have a heightened dependence on the inclusions' size when that size becomes sufficiently small. We attribute this to the manifold of surface states that form in small inclusions, due to their high surface-to-volume ratio, which raises the absorption beyond that of the bulk. It is concluded that the Bruggeman model can accurately characterize the refraction and absorption of THz radiation within composites having deeply subwavelength inclusions if their (shape-dependent) polarization and (size-dependent) absorption are suitably defined.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".