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Record W2063921364 · doi:10.1002/polb.22369

Absorption and engulfing transitions in nanoparticle infiltration into a polymer brush: A monte carlo simulation

2011· article· en· W2063921364 on OpenAlex
Yantao Chen, Jeff Z. Y. Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2011
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of Waterloo
FundersNational Natural Science Foundation of China
KeywordsBrushPolymerPolymer brushNanoparticleMonte Carlo methodMaterials scienceChemical physicsNanotechnologyPolymer chemistryChemical engineeringComposite materialChemistryPolymerization

Abstract

fetched live from OpenAlex

Abstract We study the structure of an infiltrating hard spherical nanoparticle into a polymer brush using extensive off‐lattice Monte Carlo simulations of a basic theoretical model. We show that as long as the spherical particle is coated with a surface layer that interacts attractively with brush monomers, it can penetrate deeply into a dense polymer brush near the grafting surface. The infiltration process contains two stages: diffusing nanoparticle absorbing onto the surface of the polymer brush and engulfing of the nanoparticle by polymer chains. After the nanoparticle fully immerses in the dense polymer brush region, the buoyant forces levels off because of symmetric repulsions that endows increasing nanoparticle mobility and encourages the second transition. © 2011 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2011

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.004
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 head0.038
GPT teacher head0.290
Teacher spread0.251 · 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