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Record W2012273178 · doi:10.1002/cjce.5450790313

On the prediction of surface tension for multicomponent mixtures

2001· article· en· W2012273178 on OpenAlexaffvenue
Zhibao Li, Benjamin C.‐Y. Lu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSurface tensionTernary operationThermodynamicsBinary numberAqueous solutionMolecular dynamicsMaterials scienceMaximum bubble pressure methodSurface (topology)Tension (geology)ChemistryPhysical chemistryComputational chemistryPhysicsMathematicsComputer science

Abstract

fetched live from OpenAlex

Abstract A prediction method for surface tension of real mixtures was developed based on the Davis theory, and tested with the molecular dynamics simulation results of Mecke et al. (1997) for surface tension of the Lennard‐Jones fluid. An effective Lennard‐Jones potential was introduced for correlating surface tension for real pure liquids and binary liquid mixtures, leading to prediction of surface tension of multicomponent systems, including aqueous mixtures. The overall average absolute percentage deviations (AAPD) obtained in the correlated results for 62 pure liquids, 91 non‐aqueous and 11 aqueous binaries are 0.66, 0.80, and 1.75, respectively. In the prediction of the surface tension for 9 ternary and 4 quaternary systems, using the molecular parameters of pure liquids and the adjustable binary parameters, the overall AAPDs are 1.75 and 1.03, respectively.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.214

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 head0.011
GPT teacher head0.182
Teacher spread0.171 · 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

Citations22
Published2001
Admission routes2
Has abstractyes

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