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Record W2106326364 · doi:10.1109/35.965375

MEMS optical switches

2001· article· en· W2106326364 on OpenAlexaff
Tze-Wei Yeow, K. L. Eddie Law, A.A. Goldenberg

Bibliographic record

VenueIEEE Communications Magazine · 2001
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicroelectromechanical systemsOptical switchScalabilityFabricationActuatorSurface micromachiningComputer scienceProcess (computing)Electronic engineeringMaterials scienceNanotechnologyEngineering

Abstract

fetched live from OpenAlex

Leveraging MEMS's inherent advantages such as the batch fabrication technique, small size, integrability, and scalability, MEMS is positioned to become the dominant technology in optical crossconnect switches. MEMS optical switches with complex movable 3D mechanical structures, micro-actuators, and micro-optics can be monolithically integrated on the same substrate by using the matured fabrication process of the integrated circuit industry. In this article we report various popular actuating mechanisms and switch architectures of MEMS optical switches. The basics of surface and bulk micromachining techniques used to fabricate MEMS devices are reviewed. Examples of 2D and 3D approaches to MEMS optical switches are described. The pros and cons of the two approaches are analyzed. In the short term, MEMS-based optical switches seem to have captivated the attention of both the industry and academia. However, there are challenges that threaten the long-term survival of this technology. The problems that remain to be fully addressed are discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.005

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 head0.035
GPT teacher head0.277
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations139
Published2001
Admission routes1
Has abstractyes

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Same venueIEEE Communications MagazineSame topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207