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Record W2094657037 · doi:10.1063/1.2121707

First-order mean-spherical approximation for interfacial phenomena: A unified method from bulk-phase equilibria study

2005· article· en· W2094657037 on OpenAlexaff
Yiping Tang

Bibliographic record

VenueThe Journal of Chemical Physics · 2005
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsHoneywell (Canada)
Fundersnot available
KeywordsSurface tensionComputationWork (physics)Measure (data warehouse)Phase (matter)Statistical physicsHomogeneousDensity functional theoryFunction (biology)Local-density approximationPhysicsSquare (algebra)Surface (topology)ThermodynamicsMathematicsQuantum mechanicsGeometryComputer science

Abstract

fetched live from OpenAlex

The recently proposed first-order mean-spherical approximation (FMSA) [Y. Tang, J. Chem. Phys. 121, 10605 (2004)] for inhomogeneous fluids is extended to the study of interfacial phenomena. Computation is performed for the Lennard-Jones fluid, in which all phase equilibria properties and direct correlation function for density-functional theory are developed consistently and systematically from FMSA. Three functional methods, including fundamental measure theory for the repulsive force, local-density approximation, and square-gradient approximation, are applied in this interfacial investigation. Comparisons with the latest computer simulation data indicate that FMSA is satisfactory in predicting surface tension, density profile, as well as relevant phase equilibria. Furthermore, this work strongly suggests that FMSA is very capable of unifying homogeneous and inhomogeneous fluids, as well as those behaviors outside and inside the critical region within one framework.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.624

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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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

Citations21
Published2005
Admission routes1
Has abstractyes

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