Electron polarization and plasmon effects in anisotropic nanostructures
Bibliographic record
Abstract
Properties of nanorods with the length 2 a and radius b (a>b), containing free carriers, in the external d.c. or a.c. electric field are analyzed theoretically. Static polarizability of nanorods depends on their orientation in the field and is determined by the ratio, the nanorod size in the field direction to the screening length of the material rs. When this ratio is very small or very large, the properties of nanorods are similar to those of a dielectric and metallic ellipsoid, respectively. For a≫b, polarization characteristics of nanorods are strongly anisotropic and can be metallic in one direction and dielectric in the other direction. For semiconductor nanorods suspended in a polar liquid, polarizability in different directions may have different signs. For a.c. field, conductivity of nanorods contains plasmon peaks with essentially different frequencies for longitudinal and transverse plasmons. With decreasing a and b, frequencies of both plasmons increase and their amplitudes dramatically decrease. Dynamics of conducting nanorods in external electric fields represents superposition of their angular alignment along the field direction and the drift motion in the field gradient, with the first process being faster. Thus, in non-uniform fields nanorods drift in the field gradient according to the signs and values of their longitudinal and transverse polarizations.
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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".