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Record W2903442602 · doi:10.1021/acs.macromol.8b01348

Entropic Network Model for Star Block Copolymer Thermoplastic Elastomers

2018· article· en· W2903442602 on OpenAlexafffund
Amanda Parker, Jörg Rottler

Bibliographic record

VenueMacromolecules · 2018
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElastomerThermoplastic elastomerStar polymerMaterials scienceCopolymerDeformation (meteorology)PolymerStrain rateComposite materialStar (game theory)Ultimate tensile strengthBreakupPolymer sciencePolymer chemistryMechanicsPhysics

Abstract

fetched live from OpenAlex

Uniaxial tensile deformation of star block polymer elastomers with up to 10 arms is studied with molecular dynamics simulations of a bead–spring representation at two different deformation rates. The mechanical response is rationalized in terms of an entropic network model, which we generalize from linear to star polymers. The model universally accounts for the stress in the entire deformation range well into the nonlinear regime. As the strain rate is increased, we find additional hardening as the number of arms increases, which can be attributed to the breakup of physical cross-links.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.692

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations9
Published2018
Admission routes2
Has abstractyes

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