Low-power telecom-pumped broadband mid-infrared supercontinuum generation in a SiC–AsSe <sub>2</sub> cascaded waveguide
Bibliographic record
Abstract
Abstract Supercontinuum (SC) generation in the mid-infrared (MIR) regime is pivotal for a wide range of applications, including spectroscopy, biomedical sensing, and environmental monitoring. In this work, we demonstrate MIR supercontinuum generation spanning 1.41–12.43 µ m at the −30 dB power level in a selenium-based chalcogenide waveguide, achieved with relatively low input power from a commercially available 1.55 µ m pump source. Direct pumping of chalcogenide waveguides at telecom wavelengths is hindered by unfavorable dispersion; to overcome this, we propose a dual-stage cascaded waveguide design with identical cross-sections for both stages. The first stage, a silicon carbide (SiC) waveguide, is efficiently excited by the telecom-band pump, and its output is subsequently coupled into an arsenic diselenide (AsSe 2 ) waveguide, enabling substantial spectral broadening into the MIR. The cascaded structure, consisting of 8 mm-long SiC and AsSe 2 cores, is dispersion-engineered to tailor group velocity dispersion and maximize nonlinear interaction. Moreover, employing a common MgF 2 bottom cladding and air top cladding for both stages simplifies the fabrication process. Numerical investigations confirm that this configuration enables broadband SC generation with a minimal peak power of only 1 kW.To the best of the authors’ knowledge, the cascaded SiC–AsSe 2 geometry reported here achieves among the broadest MIR coverage reported to date when using a 1.55 µ m pump and 1 kW peak power. This advancement establishes a practical and scalable pathway for MIR SC sources, unlocking new opportunities across diverse application domains.
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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) | 0.001 | 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".