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Record W2144196281 · doi:10.1109/jmems.2011.2111355

Low-Stress CMOS-Compatible Silicon Carbide Surface-Micromachining Technology—Part I: Process Development and Characterization

2011· article· en· W2144196281 on OpenAlexafffund
Frédéric Nabki, Tomas A. Dusatko, Srikar Vengallatore, Mourad N. El-Gamal

Bibliographic record

VenueJournal of Microelectromechanical Systems · 2011
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsMcGill UniversitySierra Wireless (Canada)Université du Québec à Montréal
FundersMcGill University
KeywordsMaterials scienceSilicon carbideSurface micromachiningFabricationOptoelectronicsSiliconCarbideEtching (microfabrication)Deposition (geology)NanotechnologyLayer (electronics)Composite material

Abstract

fetched live from OpenAlex

A low-temperature (<; 300 °C) low-stress microelectromechanical systems fabrication process based on a silicon carbide structural layer is presented. A partially conductive sintered target enables low-temperature dc sputtering of amorphous silicon carbide (SiC) at high deposition rates (75 nm/min). The low stress of the structural film allows for mechanically reliable structures to be fabricated, while the low-temperature deposition allows for pre-SiC metallization. The process is designed for low-cost film deposition and for complementary metal-oxide-semiconductor postintegration, stemming from chemical and thermal compatibility. Process flow, deposition, etching, and stress control are discussed, and a detailed process characterization is reported.

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: 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
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.196
Teacher spread0.181 · 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

Citations33
Published2011
Admission routes2
Has abstractyes

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