MétaCan
Menu
Back to cohort
Record W4254903145 · doi:10.1149/ma2016-02/30/1938

(Invited) SiO<sub>x</sub>N<sub>y</sub> Back-End Integration Technologies for Heterogeneously Integrated Si Platform

2016· article· en· W4254903145 on OpenAlexaboutno aff
Hidetaka Nishi, Tai Tsuchizawa, Takaaki Kakitsuka, Koichi Hasebe, Koji Takeda, Tatsuro Hiraki, Takuro Fujii, Tsuyoshi Yamamoto, Shinji Matsuo

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicSilicon and Solar Cell Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsWaveguideMaterials sciencePhotonicsOptoelectronicsArrayed waveguide gratingSilicon on insulatorPhotonic integrated circuitGratingSilicon photonicsInsertion lossWavelengthOpticsWavelength-division multiplexingSiliconPhysics

Abstract

fetched live from OpenAlex

Network traffic is continuously increasing, and the global IP traffic reaches 2 zettabytes in 2019 [1]. Photonic integrated circuits on Si-based substrates are highly demanded for coping with increasing telecommunication network traffic and energy consumption in low-cost ways. Particularly, Si and Ge provide modulators and photodetectors in telecom wavelength with a full monolithic way on SOI substrates. In addition, InP provides lightsources based on low-temperature direct-bonding technique. To connect these dynamic and active devices, we propose back-end photonic wiring by using SiO x N y -based waveguides. In this paper, I review recent progress of our work. First, I briefly review our early work; Si-Ge-SiO x integration technology and application to the WDM receiver. To increase integration density, recently, we also have developed a silicon-nitride (SiN) waveguide[1]. SiN has moderately high refractive index and provides moderately small passive devices with tolerance for nonlinear effects. We confirmed 1-dB/cm propagation loss for 1.3-, 1.5-, and 1.6-um wavelength range and applied to a compact and low-loss 16-ch. arrayed-waveguide grating (AWG) filter with 200GHz spacing. In addition, for lightsource integration, a InP-wire waveguide was successfully integrated with the SiO x waveguide via a spot-size converter (SSC) on SiO 2 /Si substrates[2]. The fabricated InP waveguide provides 5.2-dB/cm propagation loss and connected to the SiO x waveguide with a 0.7-dB loss and less than -50-dB reflectance. The InP waveguide can be used as output waveguide for the membrane laser, which utilizes strong optical confinement within the active area to obtain high modulation efficiency and low power consumption[3, 4]. With introducing distributed-reflector (DR) laser structure, the membrane laser exhibits low threshold current of 0.6 mA, output power of 0.7 mW, and 25.8-Gbit/s NRZ direct modulation with 132-fJ/bit energy consumption. In addition, the output InP wire waveguide is successfully integrated with the SiO x waveguide, which exhibits fiber coupling loss of 2.7 dB and low reflectance at the chip facet to obtain sufficient optical output power and stable single-mode operation. [1] K. Okazaki et al., Proc. GFP 2014, Vancouver, paper WP43. [2] H. Nishi et al., IEEE Photonics Journal, vol. 7, pp. 4900308, 2015. [3] S. Matuso et al., J. Lightwave Technol., vol. 33, pp. 1217, 2015. [4] H. Nishi et al., Proc. ECOC 2015, Valencia, paper We.2.5.3.

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicSilicon and Solar Cell TechnologiesFrench-language works237,207