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Record W2041740806 · doi:10.1021/ma020508h

A Pseudo Equation-of-State Approach for the Estimation of Solubility Parameters of Polyethylene by Inverse Gas Chromatography

2002· article· en· W2041740806 on OpenAlexafffund
Xiaohua Kong, Maria Dulce Lamego Vieira da. Silveira, Liyan Zhao, Phillip Choi

Bibliographic record

VenueMacromolecules · 2002
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInverse gas chromatographySolubilityEquation of stateThermodynamicsPolymerHildebrand solubility parameterCompressibilityPolyethyleneLinear low-density polyethyleneIntermolecular forceChemistryPhase (matter)InverseMacromoleculeGas chromatographyVolume (thermodynamics)ChromatographyOrganic chemistryMathematicsMoleculePhysics

Abstract

fetched live from OpenAlex

Hildebrand solubility parameters ( δ ) of a series of linear low-density polyethylenes (LLDPE) were measured at several elevated temperatures by the inverse gas chromatography (IGC) method of DiPaola-Baranyi and Guillet [ Macromolecules 1978, 11, 228−235] with the incorporation of a compressible regular solution model, recently proposed by Ruzette and Mayes [ Macromolecules 2001, 34, 1894−1907], for data analysis. It was found that, with the inclusion of the pressure−volume−temperature (PVT) properties of the pure components in the data analysis, the measured δ agreed well with those obtained from PVT measurements on similar systems. This suggests that the model of Ruzette and Mayes, even though it is mathematically less sophisticated than the conventional equation-of-state (EOS) theories, it is useful for deriving solubility properties of polymers. The results were consistent with the prediction of conventional EOS theories that, in addition to the type and strength of intermolecular interaction, PVT properties of the individual components comprising polymer solutions and blends also play a significant role in determining their phase behavior, especially at elevated temperatures.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.299

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 head0.032
GPT teacher head0.233
Teacher spread0.201 · 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 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

Citations23
Published2002
Admission routes2
Has abstractyes

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