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Record W3003153335 · doi:10.1063/1.5136270

Optical frequency comb generation with low temperature reactive sputtered silicon nitride waveguides

2020· article· en· W3003153335 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAPL Photonics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsnot available
FundersRMIT UniversityAustralian Research CouncilOntario Ministry of Natural Resources and ForestryAustralian National Fabrication Facility
KeywordsMaterials scienceOptoelectronicsSilicon nitrideLithium niobateResonatorPhotonicsSilicon on insulatorWaveguideSiliconSilicon photonicsPhotonic integrated circuit

Abstract

fetched live from OpenAlex

Integrated silicon nitride (SiN) waveguides with anomalous dispersion have the potential to bring practical nonlinear optics to mainstream photonic integrated circuits. However, high-stress and high-processing temperatures remain an obstacle to mass adoption. We report low-stress, high-confinement, dispersion-engineered SiN waveguides utilizing low temperature grown reactive sputtered thin-films. We demonstrate a microring resonator with an intrinsic quality factor of 6.6 × 105, which enabled us to generate a native free spectral range spaced frequency comb with an estimated on-chip pump power of 850 mW. Importantly, the peak processing temperature is 400 °C making this approach fully back-end compatible for hybrid integration with preprocessed CMOS substrates and temperature sensitive photonic platforms such as lithium niobate on insulator.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.223
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it