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Record W2945895546 · doi:10.1115/1.4043824

Correlations of Equilibrium Interfacial Tension Based on Mutual Solubility/Density: Extension to n-Alkane–Water and n-Alkane–CO2 Binary/Ternary Systems and Comparisons With the Parachor Model

2019· article· en· W2945895546 on OpenAlexaff
Zehua Chen, Daoyong Yang

Bibliographic record

VenueJournal of Energy Resources Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsAlkaneSolubilityChemistryThermodynamicsSurface tensionTernary operationMethaneTernary numeral systemAtmospheric temperature rangePhase (matter)HydrocarbonOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

In this study, new and pragmatic interfacial tension (IFT) correlations for n-alkane–water and n-alkane–CO2 systems are developed based on the mutual solubility of the corresponding binary systems and/or density in a pressure range of 0.1–140.0 MPa and temperature range of 283.2–473.2 K. In addition to being more accurate (i.e., the absolute average relative deviation (AARD) is 1.96% for alkane–water systems, while the AARDs for alkane–CO2 systems are 8.52% and 25.40% in the IFT range of >5.0 mN/m and 0.1–5.0 mN/m, respectively) than either the existing correlations or the parachor model (the AARDs for alkane–CO2 systems are 12.78% and 35.15% in the IFT range of >5.0 mN/m and 0.1–5.0 mN/m, respectively), such correlations can be applied to the corresponding ternary systems for an accurate IFT prediction without any mixing rule. Both a higher mutual solubility and a lower density difference between two phases involved can lead to a lower IFT, while pressure and temperature exert effects on IFT mainly through regulating the mutual solubility/density. Without taking effects of mutual solubility into account, the widely used parachor model in chemical and petroleum engineering fails to predict the IFT for CO2/methane–water pair and n-alkane–water pairs, though it yields a rough estimate for the CO2–water and methane–water pair below the CO2 and methane critical pressures of 7.38 and 4.59 MPa, respectively. However, the parachor model at least considers the effects of solubility in the alkane-rich phase to make it much accurate for n-alkane–CO2 systems. For n-alkane–CO2 pairs, the correlations developed in this work are found to be much less sensitive to the liquid density than the parachor model, being more convenient for practical use. In addition, all the IFTs for the CO2–water pair, methane–water pair, and alkane–CO2 pair can be regressed as a function of density difference of a gas–liquid system with a high accuracy at pressures lower than the critical pressures of either CO2 or methane.

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 score0.206
Threshold uncertainty score0.513

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 head0.008
GPT teacher head0.200
Teacher spread0.193 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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