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Record W2070515799 · doi:10.1063/1.2776261

Bidirectional mapping between self-consistent field theory and molecular dynamics: Application to immiscible homopolymer blends

2007· article· en· W2070515799 on OpenAlexaff
Thomas D. Sewell, K. Ø. Rasmussen, Dmitry Bedrov, Grant D. Smith, R. B. Thompson

Bibliographic record

VenueThe Journal of Chemical Physics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStatistical physicsMolecular dynamicsRepresentation (politics)Monte Carlo methodField (mathematics)Particle (ecology)Field theory (psychology)Work (physics)PolymerMaterials sciencePhysicsThermodynamicsMathematicsStatisticsQuantum mechanics

Abstract

fetched live from OpenAlex

A bidirectional mapping scheme that bridges particle-based and field-based descriptions for polymers is presented. Initial application is made to immiscible homopolymer blends. The forward mapping (upscaling) approach is based on the use of molecular dynamics simulations to calculate interfacial density profiles for polymer molecular weights that can be readily relaxed using standard simulation methods. These profiles are used to determine the optimal, effective interaction parameter that appears in the one-parameter self-consistent field theory treatment employed in the present work. Reverse mapping from a field representation to a particle-based description is accomplished by the application of a density-biased Monte Carlo method that generates representative chain configurations in the blend using statistical weights derived from fields obtained from self-consistent 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 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 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 score0.130
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.239
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2007
Admission routes1
Has abstractyes

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