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Record W2326018987 · doi:10.1103/physreve.88.052105

Pulling alternating copolymers adsorbed on a striped surface

2013· article· en· W2326018987 on OpenAlexafffund
G K Iliev, S G Whittington

Bibliographic record

VenuePhysical Review E · 2013
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of TorontoYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDesorptionDegenerate energy levelsCopolymerPerpendicularAdsorptionSurface (topology)PolymerMonomerMaterials scienceChemical physicsThermodynamicsPhysicsChemistryPhysical chemistryMathematicsGeometryComposite materialQuantum mechanics

Abstract

fetched live from OpenAlex

We consider a partially directed walk model of a strictly alternating copolymer adsorbing on a striped surface where the energy is associated with the numbers of the two types of monomers adsorbed on the two types of surface sites. A force is applied to the last monomer and the polymer responds to this force, sometimes by desorbing. The force can be applied at various angles, with the surface component parallel or perpendicular (or at some other angle) to the stripe direction. The desorption behavior is strongly dependent on the force direction and the response gives information about the shape and direction of the polymer adsorbed on the surface, especially at low temperatures. In some cases the ground state is degenerate and this also has an important effect on the temperature dependence of the critical force needed for desorption. We give a complete solution of the problem using generating function techniques and an approximate treatment that is especially useful at low temperatures and helps in our physical understanding of the situation.

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)0.001
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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

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