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Record W2034734955 · doi:10.1021/ma990746l

Monte Carlo Study of the Second Virial Coefficient and Statistical Exponent of Star Polymers with Large Numbers of Branches

2000· article· en· W2034734955 on OpenAlexaff
Kazuhito Shida, Kaoru Ohno, Masayuki Kimura, Yoshiyuki Kawazoe

Bibliographic record

VenueMacromolecules · 2000
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsRadius of gyrationVirial coefficientMonte Carlo methodExponentStatistical physicsLattice (music)PhysicsThermodynamicsPolymerMathematicsStatistics

Abstract

fetched live from OpenAlex

Computer simulations on the self- and mutual-avoiding effects of two star polymers in a good solvent are reported where the number f of the branches has been extended to the region where no experimental results are yet available. A simple and efficient Monte Carlo (MC) sampling technique was used for the lattice-model simulations. Calculations were performed for 8- to 24-arm star polymers, which complement our previous work and also Rubio et al.'s off-lattice MC simulations. The radius of gyration, the total number of configurations, and its exponent γ( f ) are evaluated. The values of γ( f ) obtained are consistent with the large f behavior ∼ f 3/2 predicted by Ohno ( Phys. Rev. 1989, A40, 1424). The pair-distribution function, the second virial coefficient, and the penetration function are also evaluated. The first order ε-expansion, which is a naive approximation of the penetration function, has been known to become increasingly inaccurate for large f . The results of the simulations give further confirmation of the inaccuracy.

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 categoriesInsufficient payload (model declined to judge)
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 score0.017
Threshold uncertainty score0.999

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)0.0020.000

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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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.

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

Citations13
Published2000
Admission routes1
Has abstractyes

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