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Record W1971182609 · doi:10.1063/1.2992530

Numerical simulation of phase separation coupled with crystallization

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

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.

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)0.002
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.026
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

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

Citations17
Published2008
Admission routes1
Has abstractyes

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