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Record W1963786353 · doi:10.1080/08927020903483296

Self-assembly of alternating copolymers and the role of hydrophobic interactions: characterisation by molecular modelling

2010· article· en· W1963786353 on OpenAlexafffund
Anita S.W. Chan, Michael N. Groves, Cecile Malardier‐Jugroot

Bibliographic record

VenueMolecular Simulation · 2010
Typearticle
Languageen
FieldChemistry
TopicElectrostatics and Colloid Interactions
Canadian institutionsRoyal Military College of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCopolymerMaleic anhydrideAmphiphilePolymerAb initioAqueous solutionChemistryPolymer chemistryMolecular dynamicsMaterials sciencePolymer scienceComputational chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This paper describes the characterisation and the properties of amphiphilic alternating copolymers and their self-assembly into nanoarchitectures in aqueous solution. To investigate the role of the nature of the hydrophobic groups on the association, the self-assembly of two different polymers are compared: poly(isobutylene-alt-maleic anhydride) (IMA) and poly(styrene-alt-maleic anhydride). A structural analysis using computational methods is performed to investigate and characterise the behaviour of IMA chains at different pH values. The optimisation of IMA at different pH values is performed using a complete conformational method which applied both semi-empirical and ab initio molecular modelling methods. The present paper describes in detail the conformational analysis of IMA, the association among IMA chains to form the nanostructures and discusses the influence of the nature of the hydrophobic groups on the association. The theoretical prediction is also compared to experiment.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.003
GPT teacher head0.227
Teacher spread0.225 · 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 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

Citations16
Published2010
Admission routes2
Has abstractyes

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