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Record W2774935616 · doi:10.1109/nano.2017.8117294

Maximizing deflection in MEMS and microfluidic actuators fabricated in permanently magnetic composite polymers

2017· article· en· W2774935616 on OpenAlexaff
Mona Rahbar, Bonnie L. Gray

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsSimon Fraser UniversityStemcell Technologies
Fundersnot available
KeywordsActuatorDeflection (physics)Microelectromechanical systemsMaterials scienceMicrofluidicsFluidicsComposite numberPolymerComposite materialOptoelectronicsNanotechnologyOpticsElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

We investigate several design considerations in the development of magnetic composite polymer (M-CP) micro-actuators with high deflection based on rare-earth magnetic micro- and nano-powders embedded in polydimethyl siloxane (PDMS). In particular, we show that higher actuator deflection results from permanently magnetized M-CP structures compared to non-permanently magnetized ones; and that combinations of thicker and thinner M-CP structures, as well as hybrid M-CP/PDMS structures, can result in higher actuator deflection. We demonstrate each of these design considerations through analysis and experimentation on different actuator types that are employed for microelectromechanical systems (MEMS) and microfluidic devices.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.564

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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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