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Record W2027167795 · doi:10.1021/ie801451a

The Modified Sanchez−Lacombe Equation of State Applied to Polydisperse Polyethylene Solutions

2009· article· en· W2027167795 on OpenAlexaff
Ryan A. Krenz, Torben Laursen, Robert A. Heidemann

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2009
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEquation of stateThermodynamicsMaterials scienceFlory–Huggins solution theoryWork (physics)Critical point (mathematics)Cloud pointPhase (matter)Acentric factorPolymerChemistryPhysicsOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

The modified Sanchez−Lacombe equation of state (MSL-EOS) is Neau’s version of the Sanchez−Lacombe equation of state modified to include a Péneloux-type volume translation. The purpose of this work is to report parameters for modeling the phase behavior of polyethylene solutions. The MSL equation is an empirical equation that contains four parameters to define each pure compound whether a solvent or a polydisperse polymer. The MSL equation uses conventional linear and quadratic mixing rules. A parametrization can be used to obtain the pure compound parameters from the molar mass, critical temperature, critical pressure, and acentric factor. These properties cannot be defined for polydisperse polymers, and parameters were determined from a combination of liquid density ( PVT ) data and polymer + solvent cloud point ( xPT ) data. Binary interaction parameters have been obtained for over 50 mixtures by correlating the fluid phase boundaries. Binary mixtures including ethylene, hexane, and/or cyclohexane are of particular interest to polyethylene production. A single binary interaction parameter is usually sufficient to represent vapor−liquid equilibrium, but temperature dependence is required to accurately represent liquid−liquid equilibrium. The MSL equation of state can be used to correlate the cloud points of polyethylene solutions at high pressures.

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)0.001
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 score0.012
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.090
GPT teacher head0.303
Teacher spread0.213 · 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

Citations39
Published2009
Admission routes1
Has abstractyes

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