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Record W1971182609 · doi:10.1063/1.2992530

Numerical simulation of phase separation coupled with crystallization

2008· article· en· W1971182609 on OpenAlex
Douglas Zhou, An‐Chang Shi, Pingwen Zhang

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

VenueThe Journal of Chemical Physics · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsMcMaster University
Fundersnot available
KeywordsNucleationCrystallizationMaterials sciencePhase (matter)Separation (statistics)Chemical physicsEthyleneComputer simulationThermodynamicsKineticsChemical engineeringMechanicsChemistryPhysicsCatalysisOrganic chemistryComputer scienceClassical mechanics

Abstract

fetched live from OpenAlex

The kinetics of liquid-liquid phase separation and polymer crystallization observed in double-quench experiments with blends of poly(ethylene-co-hexene) and poly(ethylene-co-butene) are studied using time-dependent Ginzburg-Landau Model. Numerical simulations demonstrate that our model can successfully reproduce three experimental phenomena: The decrease in number and size of crystallized spherulites with increasing time in phase separation, the preponderance of nuclei near the domain interface, and the subphase separation and subcrystallization occurring when the second quench is very deep. Moreover, the simulations are consistent with the recently proposed mechanism of "phase separation fluctuation assisted nucleation" in the crystallization process.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.171

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 head0.026
GPT teacher head0.284
Teacher spread0.259 · 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