Mid-infrared Fourier-transform spectrometer based on metamaterial lateral cladding suspended silicon waveguides
Bibliographic record
Abstract
Integrated mid-infrared micro-spectrometers have a great potential for applications in environmental monitoring and space exploration. Silicon-on-insulator (SOI) is a promising platform to tackle this integration challenge, owing to its unique capability for large volume and low-cost production of ultra-compact photonic circuits. However, the use of SOI in the mid-infrared is restricted by the strong absorption of the buried oxide layer for wavelengths beyond 4 µm. Here, we overcome this limitation by utilizing metamaterial-cladded suspended silicon waveguides to implement a spatial heterodyne Fourier-transform (SHFT) spectrometer operating at wavelengths near 5.5 µm. The metamaterial-cladded geometry allows removal of the buried oxide layer, yielding measured propagation loss below 2 dB/cm at wavelengths between 5.3 and 5.7 µm. The SHFT spectrometer comprises 19 Mach–Zehnder interferometers with a maximum arm length imbalance of 200 µm, achieving a measured spectral resolution of 13 cm−1 and a free spectral range of 100 cm−1 at wavelengths near 5.5 µm.
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 | 0.001 |
| Open science | 0.001 | 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".