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Record W2225104118 · doi:10.1021/acs.macromol.5b02286

Field-Theoretic Simulation of Block Copolymers at Experimentally Relevant Molecular Weights

2015· article· en· W2225104118 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

VenueMacromolecules · 2015
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsUniversity of Waterloo
FundersNational Science Foundation
KeywordsLamellar structureCopolymerMonte Carlo methodDissipative particle dynamicsStatistical physicsMaterials scienceThermodynamicsPolymerField (mathematics)Phase (matter)Mean field theoryField theory (psychology)PhysicsChemical physicsCondensed matter physicsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

Field-theoretic simulation (FTS) offers an efficient means of predicting the equilibrium behavior of high-molecular-weight structured polymers, provided one is able to deal with the strong ultraviolet (UV) divergence that occurs at realistic molecular weights. Here melts of lamellar-forming diblock copolymer are studied using a Monte Carlo version (MC-FTS), where the composition field fluctuates while the pressure field follows the mean-field approximation. We are able to control the UV divergence by introducing a new effective Flory–Huggins interaction parameter, χ e, thereby permitting MC-FTS for molecular weights extending down to values characteristic of experiment. Results for the disordered-state structure function, the layer spacing and compressibility of the ordered lamellar phase, and the position of the order–disorder transition (ODT) show excellent agreement with recent particle-based simulation. Given the immense versatility of FTS, this opens up the opportunity for quantitative studies on a wide range of more complicated block copolymer systems.

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 score0.006
Threshold uncertainty score0.973

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 head0.011
GPT teacher head0.259
Teacher spread0.248 · 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