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Record W2067906008 · doi:10.1117/12.472728

Reliability and qualification of an integrated MEMS attenuator for optical component applications

2003· article· en· W2067906008 on OpenAlexaff
Ryan Hickey, H. Fettig, James Wylde, Stephane J. Legros, R. E. Mallard, H. Nentwich, Christopher Hart

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsAttenuator (electronics)Microelectromechanical systemsActuatorReliability engineeringReliability (semiconductor)Deflection (physics)Electronic engineeringDevice under testEngineeringElectrical engineeringComputer sciencePower (physics)Materials science

Abstract

fetched live from OpenAlex

This paper describes a test system and presents preliminary results of a long-term reliability study of an electro-thermally actuated integrated MEMS optical attenuator. These tests are designed to address the specific failure modes and life prediction models required for "set and forget" components and to identify deficiencies that exist in the current telecom (Telcordia) testing standards as they apply to MEMS. The failure modes are activated by overstressing the devices to a much higher power than would be observed under normal operating conditions. The paper describes a multi-module experimental test station for exciting devices at up eight different power levels, both AC and DC. At set intervals devices are tested off-board to measure changes in actuator deflection and resistance over time. The preliminary results show that devices start to degrade at power levels 92% over operating power after 400 hours of stress.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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 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

Citations2
Published2003
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207