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Record W4396223060 · doi:10.1002/mats.202400022

Numerical Modeling and Simulation of the Nonisothermal Double Quench Phase Separation Process for the Production of Polymeric Membranes Using Polystyrene‐Cyclohexanol Polymer Solution

2024· article· en· W4396223060 on OpenAlexafffund
Samira Ranjbarrad, Philip Chan

Bibliographic record

VenueMacromolecular Theory and Simulations · 2024
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsToronto Metropolitan University
FundersAlliance de recherche numérique du CanadaNatural Sciences and Engineering Research Council of CanadaToronto Metropolitan University
KeywordsQuenching (fluorescence)Materials sciencePhase (matter)PolystyreneThermodynamicsMembraneStructure formationSeparation processChemical engineeringPolymerChemistryComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The double quench phase separation is a simplified type of continuous cooling process that is widely seen in industrial processes for polymeric membrane formation. Uncommon quenching conditions can lead to the creation of novel membrane microstructures. This study aims to theoretically investigate the impact of nonisothermality on the morphology formation during the double‐quench thermally‐induced phase separation process. First, quench is employed during different stages of phase separation to observe the possibility of secondary morphology formation. Next, two initial quench temperatures are selected, one shallow and the other deep. The initial solution temperature and the secondary quench temperature are kept constant to inspect the impact of the initial quench temperature on the structure formation. Lastly, the results of the secondary quench are compared with and without employing the enthalpy of demixing. Results verified that the stage of phase separation, the initial and secondary quench temperatures, cooling rate, and the secondary quench composition are the most important parameters in the the nonisothermal double quench phase separation process. The morphology should be well‐developed in order for the secondary structure formation. In addition, it is shown that heat generation during demixing in the primary and secondary quenches significantly influences the secondary morphology formation.

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 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 score0.364
Threshold uncertainty score0.378

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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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