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Record W3162603990 · doi:10.1021/acsami.1c04367

Universal Strain Energy-Mediated Dynamic Porosity in Physically Networked Elastomers and Their Applications

2021· article· en· W3162603990 on OpenAlexaff
Navid Namdari, Sheikh Rasel, Bilal Nizar Abdul Halim, Md Emran Hossain Bhuiyan, Hossein Sojoudi, Reza Rizvi

Bibliographic record

VenueACS Applied Materials & Interfaces · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsYork University
Fundersnot available
KeywordsMaterials scienceElastomerPorosityComposite materialStrain (injury)

Abstract

fetched live from OpenAlex

Mechanical and physical properties of porous polymers are highly dependent on the arrangement of their internal pores, which once synthesized are widely considered static. However, here we introduce an unconventional dynamic porosity strategy in physically networked elastomer polymers, irrespective of their chemistry. This strategy allows for an omnidirectional and reversible reconfiguration of porosity in response to applied mechanical deformations, even at ambient conditions. In particular, the normal contact pressure between human fingers (just 0.62 MPa) applied on thin elastomer films results in a permanent reversion of the pores to a denser and more solid state. The porous-to-solid transition leads to a 3 order of magnitude reduction in pore density and up to a 22% relative volumetric shrinkage of the films, resulting in an opaque-to-transparent transition (OTT) that acts as a visual indication of porosity state (porous vs nonporous). It is shown that the pore reversion pressure onset is dependent on the average pore-to-pore distance that is controllable through process-specific parameters. Furthermore, the porosity transition is reversible for multiple cycles when the through-plane compression activation is coupled with an in-plane stretch (ε = 700%). A strain energy-mediated thermodynamic model is successfully implemented to confirm the effects of mechanical deformations on pore reversion and generation. Finally, applications of the newfound dynamic porosity concept are exploited for pressure indication, on-demand modulation of materials' mechanical and thermal characteristics, and flexible photomasks.

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 score0.002
Threshold uncertainty score0.963

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 head0.005
GPT teacher head0.205
Teacher spread0.200 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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