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Record W2474805528 · doi:10.1021/acs.macromol.5b02158

Ionomer Self-Assembly in Dilute Solution Studied by Coarse-Grained Molecular Dynamics

2016· article· en· W2474805528 on OpenAlexafffund
Mahdi Ghelichi, Kourosh Malek, Michael Eikerling

Bibliographic record

VenueMacromolecules · 2016
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsNational Research Council CanadaSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research GridCompute CanadaUniversity of Manitoba
KeywordsIonomerMolecular dynamicsChemistryDynamics (music)Chemical physicsPolymer chemistryMaterials scienceChemical engineeringComputational chemistryPolymerPhysicsCopolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Coarse-grained molecular dynamics simulations, reported in this article, elucidate the self-assembly of semiflexible ionomer molecules into cylindrical bundle-like aggregates. Ionomer chains are composed of hydrophobic backbones, grafted with pendant side chains that are terminated by anionic headgroups. Bundles have a core of backbones surrounded by a surface layer of charged anionic headgroups and a diffuse halo of counterions. Parametric studies of bundle properties unravel the interplay of backbone hydrophobicity, strength of electrostatic interactions between charged moieties, side chain content, and counterion valence: expectedly, the size of bundles increases with backbone hydrophobicity; the aggregate size depends nonmonotonically on the Bjerrum length; increasing the grafting density of pendant side chains results in smaller bundles; and the counterion valence exerts a strong effect on bundle size and counterion localization in the near-bundle region. Results reveal how the ionomer architecture and solvent properties influence the ionomer aggregation and associated electrostatic and mechanical bundle properties. These properties of ionomer aggregates are vital for rationalizing the water sorption behavior and transport phenomena as well as the chemical and mechanical stability of ionomer membranes.

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 score0.150
Threshold uncertainty score0.669

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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

Citations53
Published2016
Admission routes2
Has abstractyes

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