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Record W1986246022 · doi:10.1021/jp903519c

An Accurate Equation of State for Fluids and Solids

2009· article· en· W1986246022 on OpenAlexaff
Gholamabbas Parsafar, H. V. Spohr, G. N. Patey

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2009
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEquation of stateThermodynamicsCritical point (mathematics)Ionic bondingTriple pointChemistryLimit (mathematics)Statistical physicsMaterials sciencePhysicsIonMathematicsMathematical analysisOrganic chemistry

Abstract

fetched live from OpenAlex

A simple functional form for a general equation of state based on an effective near-neighbor pair interaction of an extended Lennard-Jones (12,6,3) type is given and tested against experimental data for a wide variety of fluids and solids. Computer simulation results for ionic liquids are used for further evaluation. For fluids, there appears to be no upper density limitation on the equation of state. The lower density limit for isotherms near the critical temperature is the critical density. The equation of state gives a good description of all types of fluids, nonpolar (including long-chain hydrocarbons), polar, hydrogen-bonded, and metallic, at temperatures ranging from the triple point to the highest temperature for which there is experimental data. For solids, the equation of state is very accurate for all types considered, including covalent, molecular, metallic, and ionic systems. The experimental pvT data available for solids does not reveal any pressure or temperature limitations. An analysis of the importance and possible underlying physical significance of the terms in the equation of state is given.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0120.008

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 head0.256
Teacher spread0.245 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations41
Published2009
Admission routes1
Has abstractyes

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