Experimental characterization of Spherical Bragg Resonators for electromagnetic emission engineering at microwave frequencies
Bibliographic record
Abstract
This work reports experimental investigation and numerical validation of millimeter-sized Spherical Bragg Resonators (SBRs) fabricated using 3D printing technology. The frequency dependencies of the reflection and transmission coefficients were analyzed, and eigenfrequency values were calculated to examine the density of photonic states in air/PLA-polylactide SBRs, showing the appearance of an eigenmode and an increase in the local density of states in the core of a defect cavity. A decay rate enhancement of [Formula: see text] was obtained for a dipole placed in the core of the defect SBR. The study also investigated the influence of the source position on the resonator's electromagnetic wave energy. Scattering efficiencies up to order twelve of the multipole electric and magnetic contribution in a 10-layer SBR were calculated to validate the presence of the resonant modes observed in the scattering measurements performed for parallel and perpendicular polarizations. The results demonstrate that SBRs can act as omnidirectional cavities to enhance or inhibit spontaneous emission processes by modifying the density of electromagnetic states compared to free space. This finding highlights the potential of SBRs engineering spontaneous electromagnetic emission processes in various applications, including dielectric nanoantennas, optoelectronics devices, and quantum information across the entire electromagnetic spectrum.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".