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OSTE+ Polymer Composite with Rare Earth Hard Magnetic Particles for Flexible Reaction Injection-Moldable Microfluidic Actuators

2021· article· en· W4207062278 on OpenAlexaff
Chelsey Currie, Bonnie L. Gray

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComposite numberPolymerMaterials scienceNanotechnologyComputer scienceComposite material

Abstract

fetched live from OpenAlex

We present a novel magnetic composite polymer (M-CP) that consists of off-thiol-ene-epoxy (OSTE+) polymer thermoplastic resin embedded (doped) with rare earth (hard) magnet particles, resulting in an M-CP that is flexible and capable of strong, bi-directional actuation. While previously shown for microfluidics, OSTE+ has not yet been embedded with functional (e.g., magnetic) particles. We demonstrate that a magnetic OSTE+ using a matrix polymer of OSTEMER 324 Flex embedded with 25% by weight rare earth ((Nd0.7Ce0.3)10.5Fe83.9B5.6) magnetic powder remains flexible after photopatterning, can be permanently magnetized, and retains a permanent magnetic field for at least 15 months. We develop a fabrication flow for this new material, as well as determine its ultraviolet (UV) curing times. Further development of magnetic OSTE+ could advance the integration of flexible M-CP microactuators into mass-manufacture, as OSTE+ integrates well with diverse substrates and can be tailored to have different ranges of Young's modulus, allowing for flexible actuators to be built into an otherwise rigid device.

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 score0.003

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 science0.0000.000
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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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
Published2021
Admission routes1
Has abstractyes

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