Silk Foam Terahertz Waveguides
Bibliographic record
Abstract
Fabrication and characterization in the THz frequency range of silk foams and silk foam‐based waveguides using lyophilisation and casting techniques are reported. The lack of biocompatible and biofriendly waveguides for low‐loss, low‐dispersion guidance of THz waves motivates the work for applications in remote and stand‐off sensing in biomedical and agro‐alimentary industries. Silk foams produced are 94% porous. Optical characterization is carried out using THz time‐domain spectroscopy. The cutback measurements of foam samples show that the foam refractive index is close to that of air ( ). Silk foam losses scale quadratically with frequency ( ), being one order of magnitude smaller than those of solid silk. As an example of a basic guided wave device, fabrication and optical characterization of 10 cm‐long, 5 mm‐diameter step‐index THz fibers having silk foam in the core and air in the cladding is demonstrated. Cutback measurements confirm that in the mid‐THz spectral range, step‐index fibers operate effectively in a single mode regime. Effective refractive index and propagation loss at frequencies higher that 0.2 THz are close to that of a silk foam from which the fiber core is made. At the same time, at these frequencies, modal group velocity dispersion is smaller than .
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 | 0.000 | 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) | 0.001 | 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".