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Record W2078673875 · doi:10.1103/physreve.70.011201

Modeling inhomogeneous van der Waals fluids using an analytical direct correlation function

2004· article· en· W2078673875 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Review E · 2004
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsHoneywell (Canada)
Fundersnot available
Keywordsvan der Waals forceHelmholtz free energyRadial distribution functionLimit (mathematics)Statistical physicsMean field theoryPhysicsCorrelation function (quantum field theory)Hard spheresDistribution functionComplex fluidField (mathematics)ThermodynamicsMolecular dynamicsMathematicsQuantum mechanicsMathematical analysis

Abstract

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Rosenfeld's perturbative method [J. Chem. Phys. 98, 8126 (1993)]] for constructing the Helmholtz energy functional of classical systems is applied to studying inhomogeneous Lennard-Jones fluids, in which the key input-the bulk direct correlation function-is obtained from the first-order mean-spherical approximation (FMSA) [J. Chem. Phys. 118, 4140 (2003)]]. Preserving its high fidelity at the bulk limit, the FMSA shows stable and satisfactory performance for a variety of inhomogeneous Lennard-Jones fluids including those near hard walls, inside slit pores, and around colloidal particles. In addition, the inhomogeneous FMSA reproduces reliably the radial distribution function at its bulk limit. The FMSA is found, in particular, much better than the mean-field theory for fluids near hard surfaces. Unlike alternative non-mean-field approaches, the FMSA is computationally as efficient as the mean-field theory, free of any numerical determination of structure information, weight functions, or empirical parameters.

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.

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 score0.288
Threshold uncertainty score0.620

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 head0.295
Teacher spread0.263 · 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