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Record W2951107222 · doi:10.3390/polym11061076

Computer Simulation of Anisotropic Polymeric Materials Using Polymerization-Induced Phase Separation under Combined Temperature and Concentration Gradients

2019· article· en· W2951107222 on OpenAlexafffund
Shima Ghaffari, Philip K. Chan, Mehrab Mehrvar

Bibliographic record

VenuePolymers · 2019
Typearticle
Languageen
FieldMaterials Science
TopicBlock Copolymer Self-Assembly
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsPolymerizationMonomerMaterials sciencePhase (matter)CondensationAnisotropyThermodynamicsPolymer chemistryAnalytical Chemistry (journal)Chemical engineeringChemistryPolymerChromatographyComposite materialOpticsOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

In this study, the self-condensation polymerization of a tri-functional monomer in a monomer-solvent mixture and the phase separation of the system were simultaneously modeled and simulated. Nonlinear Cahn–Hilliard and Flory–Huggins free energy theories incorporated with the kinetics of the polymerization reaction were utilized to develop the model. Linear temperature and concentration gradients singly and in combination were applied to the system. Eight cases which faced different ranges of initial concentration and/or temperature gradients in different directions, were studied. Various anisotropic structural morphologies were achieved. The numerical results were in good agreement with published data. The size analysis and structural characterization of the phase-separated system were also carried out using digital imaging software. The results showed that the phase separation occurred earlier in the section with a higher initial concentration and/or temperature, and, at a given time, the average equivalent diameter of the droplets <dave> was larger in this region. While smaller droplets formed later in the lower concentration/temperature regions, at the higher concentration/temperature side, the droplets went through phase separation longer, allowing them to reach the late stage of the phase separation where particles coarsened. In the intermediate stage of phase separation, <dave> was found proportional to t * α , where α was in the range between 1 3 and 1 2 for the cases studied and was consistent with published results.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.025
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.289
Teacher spread0.274 · 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.

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

Citations15
Published2019
Admission routes2
Has abstractyes

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