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Record W4412976562 · doi:10.1021/acs.macromol.5c00874

Molecular-Scale Simulation of Auxetic Behavior in Side-Chain Liquid Crystalline Polymers (SCLCPs)

2025· article· en· W4412976562 on OpenAlexafffund
Sadollah Ebrahimi, Olivier Couture, Armand Soldera

Bibliographic record

VenueMacromolecules · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaInnovation for Defence Excellence and Security
KeywordsPolymerAuxeticsChain (unit)Polymer scienceScale (ratio)Materials scienceLiquid crystallineSide chainMolecular dynamicsPolymer chemistryChemistryChemical engineeringComposite materialPhysicsComputational chemistryEngineering

Abstract

fetched live from OpenAlex

Auxetic materials, characterized by a negative Poisson’s ratio (NPR), exhibit unique mechanical properties with applications in medical and military technologies. Recent experimental and theoretical studies have demonstrated bulk auxetic behavior in liquid crystal elastomers (LCEs), highlighting the molecular reorientation mechanisms involved. However, side-chain liquid crystalline polymers (SCLCPs) remain underexplored for intrinsic molecular auxeticity. Using coarse-grained molecular dynamics simulations, we investigate SCLCPs inspired by Griffin’s architecture, focusing on their phase transitions and Poisson’s ratio. One-arm and two-arm SCLCP variants were simulated, revealing NPR in one-arm systems at low lateral monomer volume fractions ( R < 6%), driven by the swirling motion of longitudinal monomer domains. Phase transitions from amorphous to polycrystalline smectic-like configurations were analyzed using a cooling process, with properties evaluated below the transition threshold (∼400 K). To enhance accuracy, the ab initio calculations on energy interactions between different configurations of ellipsoids and beads were performed. Our findings elucidate molecular mechanisms underlying auxetic behavior in SCLCPs, complementing existing LCE studies and offering insights for designing tailored auxetic polymers.

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 score0.237
Threshold uncertainty score0.661

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 head0.240
Teacher spread0.234 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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