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Record W2072329498 · doi:10.1021/ma9023813

Wormlike Polymer Brush: A Self-Consistent Field Treatment

2010· article· en· W2072329498 on OpenAlexaff
Mingge Deng, Ying Jiang, Haojun Liang, Jeff Z. Y. Chen

Bibliographic record

VenueMacromolecules · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsScalingBrushPolymerLimit (mathematics)Chain (unit)Power lawField (mathematics)Polymer brushGraftingMaterials scienceStatistical physicsPhysicsPolymer chemistryThermodynamicsMathematicsMathematical analysisGeometryPolymerizationQuantum mechanicsComposite materialStatistics

Abstract

fetched live from OpenAlex

We investigate a homopolymer brush system on the basis of the wormlike-chain model, incorporating an Onsager-type interaction between polymer segments in the excluded-volume interaction. The model depends on the ratio between the total polymer length and the persistent length and a reduced grafting density as two basic parameters. Our numerical solutions to the self-consistent field theory are compared with scaling properties that can be deduced in various limits. In the limit of long chain and weak-to-moderate grafting density, our numerical results follow the scaling power law predicted by the classical-trajectory theory of a flexible polymer brush. In the limit of long chain and high grafting density, our numerical results show that the brush properties are comparable to the conformational properties of a nematic wormlike solution. In the limit of rod brush, our numerical results are consistent with the solution of a trial-function treatment from a previous mean-field theory.

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)0.001
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.260
Teacher spread0.249 · 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

Citations32
Published2010
Admission routes1
Has abstractyes

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