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Irreversible bonding of polyimide and polydimethylsiloxane (PDMS) based on a thiol-epoxy click reaction

2016· article· en· W2522788347 on OpenAlexafffund
Michelle Hoang, Hyun‐Joong Chung, Anastasia Elias

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsPolydimethylsiloxaneEpoxyPolyimideMaterials scienceAdhesiveSurface modificationClick chemistryMicrofabricationSubstrate (aquarium)PolymerLayer (electronics)FabricationComposite materialNanotechnologyPolymer chemistryChemical engineering

Abstract

fetched live from OpenAlex

Polyimide is one of the most popular substrate materials for the microfabrication of flexible electronics, while polydimethylsiloxane (PDMS) is the most widely used stretchable substrate/encapsulant material. These two polymers are essential in fabricating devices for microfluidics, bioelectronics, and the internet of things; bonding these materials together is a crucial challenge. In this work, we employ click chemistry at room temperature to irreversibly bond polyimide and PDMS through thiol-epoxy bonds using two different methods. In the first method, we functionalize the surfaces of the PDMS and polyimide substrates with mercaptosilanes and epoxysilanes, respectively, for the formation of a thiol-epoxy bond in the click reaction. In the second method, we functionalize one or both surfaces with mercaptosilane and introduce an epoxy adhesive layer between the two surfaces. When the surfaces are bonded using the epoxy adhesive without any surface functionalization, an extremely small peel strength (<0.01 N mm −1 ) is measured with a peel test, and adhesive failure occurs at the PDMS surface. With surface functionalization, however, remarkably higher peel strengths of ~0.2 N mm −1 (method 1) and >0.3 N mm −1 (method 2) are observed, and failure occurs by tearing of the PDMS layer. We envision that the novel processing route employing click chemistry can be utilized in various cases of stretchable and flexible device fabrication.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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

Citations71
Published2016
Admission routes2
Has abstractyes

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