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Record W2774470152 · doi:10.3390/mi8120354

Rotating Circular Micro-Platform with Integrated Waveguides and Latching Arm for Reconfigurable Integrated Optics

2017· article· en· W2774470152 on OpenAlexafffund
Jonathan Brière, Mohannad Y. Elsayed, Menouer Saidani, Martin Bérard, Philippe-Olivier Beaulieu, Hadi Rabbani-Haghighi, Frédéric Nabki, Michaël Ménard

Bibliographic record

VenueMicromachines · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsÉcole de Technologie SupérieureActive Ethernet Passive Optical Networks Over λ MultipleXing (Canada)Université du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsOpticsMicroelectromechanical systemsOptical switchCircular motionMaterials scienceOptoelectronicsSilicon nitrideClosing (real estate)SiliconPhysicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

This work presents a laterally rotating micromachined platform integrated under optical waveguides to control the in-plane propagation direction of light within a die to select one of multiple outputs. The platform is designed to exhibit low constant optical losses throughout the motion range and is actuated electrostatically using an optimized circular comb drive. An angular motion of ±9.5° using 180 V is demonstrated. To minimize the optical losses between the moving and fixed parts, a gap-closing mechanism is implemented to reduce the initial air gap to submicron values. A latch structure is implemented to hold the platform in place with a resolution of 0.25° over the entire motion range. The platform was integrated with silicon nitride waveguides to create a crossbar switch and preliminary optical measurements are reported. In the bar state, the loss was measured to be 14.8 dB with the gap closed whereas in the cross state it was 12.2 dB. To the authors' knowledge, this is the first optical switch based on a rotating microelectromechanical device with integrated silicon nitride waveguides reported to date.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.853

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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2017
Admission routes2
Has abstractyes

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