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Record W2013266025 · doi:10.1002/mats.200400104

End‐Anchored Polymers: Compression by Different Mechanisms and Interpenetration of Apposing Layers

2005· article· en· W2013266025 on OpenAlex

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

VenueMacromolecular Theory and Simulations · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCompression (physics)PolymerDeformation (meteorology)Range (aeronautics)Materials scienceSurface energySurface (topology)MechanicsComposite materialThermodynamicsMathematicsGeometryPhysics

Abstract

fetched live from OpenAlex

Abstract Summary: This paper presents a systematic study of the compression of end‐anchored polymer layers by a variety of mechanisms. We treat layers in both good and Θ solvents, and in the range of polymer densities that is normally encountered in experiments. Our primary technique is numerical self‐consistent field (NSCF) theory. We compare the NSCF results for the different mechanisms with each other, and with those of the analytic SCF theory. For each mechanism, we calculate the density profiles, layer thicknesses, and free energies, all as functions of the degree of polymerization and surface coverage. The free energy and the deformation of each layer depend on the compression mechanism, and they can be very different from the ASCF theory. For example, the energy of compression can be as much as three times greater than the analytical SCF (ASCF) prediction, and it does not reduce to simple, universal functions of the reduced distance between the surfaces. The overall physical picture simplifies if the free energy is expressed in terms of the layer deformation, rather than the reduced surface separation. We also examine and quantify the interpenetration of layers, discuss why ASCF theory applies better to some compression mechanisms than others, and end with comments on the difficulties in extracting quantitative information from surface‐forces experiments. Comparisons of forces of compression in a good solvent for the three different systems, as functions of D / n b . The lower three curves are for σ * = 3, and the upper three are for σ * = 23. image Comparisons of forces of compression in a good solvent for the three different systems, as functions of D / n b . The lower three curves are for σ * = 3, and the upper three are for σ * = 23.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.097
Threshold uncertainty score0.425

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)0.0000.000

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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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