Vibron and Phonon Hybridization in Dielectric Nanostructures
Bibliographic record
Abstract
Plasmon hybridization theory has been an invaluable tool in advancing our understanding of the optical properties of metallic nanostructures. Through the prism of molecular orbital theory, it allows one to interpret complex structures as “plasmonic molecules” and easily predict and engineer their electromagnetic response. However, this formalism is limited to conducting particles. Here, we present a hybridization scheme for the external and internal vibrations of dielectric nanostructures that provides a straightforward understanding of the infrared signatures of these particles through analogy to existing hybridization models of both molecular orbitals and plasmons extending the range of applications far beyond metallic nanostructures. This method not only provides a qualitative understanding, but also allows for the quantitative prediction of vibrational spectra of complex nanoobjects from well-known spectra of their primitive building blocks. The examples of nanoshells illustrate how spectral features can be understood in terms of symmetry, number of nodal planes, and scale parameters.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".