Bibliographic record
Abstract
Layered 2D graphene oxide (GO) films are integrated with micro-ringresonators (MRRs) to experimentally demonstrate enhanced nonlinear optics.Both uniformly coated (1−5 layers) and patterned (10−50 layers) GO films areintegrated on complementary-metal-oxide-semiconductor (CMOS)-compatibledoped silica MRRs using a large-area, transfer-free, layer-by-layer GO coatingmethod with precise control of the film thickness. The patterned devices furtheremploy photolithography and lift-off processes to enable precise control of thefilm placement and coating length. Four-wave-mixing (FWM) measurementsfor different pump powers and resonant wavelengths show a significantimprovement in efficiency of 7.6 dB for a uniformly coated device with 1 GOlayer and 10.3 dB for a patterned device with 50 GO layers. The measurementsagree well with theory, with the enhancement in FWM efficiency resultingfrom the high Kerr nonlinearity and low loss of the GO films combined withthe strong light–matter interaction within the MRRs. The dependence of GO’sthird-order nonlinearity on layer number and pump power is also extractedfrom the FWM measurements, revealing interesting physical insights aboutthe evolution of the GO films from 2D monolayers to quasi bulk-like behavior.These results confirm the high nonlinear optical performance of integratedphotonic resonators incorporated with 2D layered GO films.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.149 | 0.090 |
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".