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Record W2026762624 · doi:10.1139/p03-118

Solidliquid transition of charge-stabilized colloidal dispersions: a single-component structure-function approach

2004· article· en· W2026762624 on OpenAlexvenueno aff
Shiqi Zhou

Bibliographic record

VenueCanadian Journal of Physics · 2004
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsYukawa potentialColloidPhysicsElectrolyteCharge (physics)CoulombComponent (thermodynamics)Function (biology)Line (geometry)ThermodynamicsCondensed matter physicsChemical physicsQuantum mechanicsPhysical chemistryChemistry

Abstract

fetched live from OpenAlex

We have extended the Raveché–Mountain–Streett one-phasecriterion that governs the freezing of Lennard-Jones systems to a hard-core repulsive Yukawa-model (HCRYM) system. We find in the framework of the Rogers–Young (RY) approximation for an Ornstein–Zernike integral equation that an HCRYM fluid freezes when the ratio α = g(rmin)/g(rmax), where rmax is the distance corresponding to the maximum in the radial distribution function g(r) and rmin is the distance corresponding to the subsequent minimum in g(r), is approximately 0.215. To describe the freezing of charge-stabilized colloidal dispersions in electrolytes, which consist of colloidal macroions,electrolyte small ions, and solvent molecules, we employ the single-component model in which the colloidal particles interact through the effective screened Coulomb potential of Belloni. Whenthe macroion surface effective charge number is taken as an adjustable parameter, the theoretical freezing line predicted by the RY g(rmin)/g(rmax) = 0.215 Raveché–Mountain–Streett one-phase criterion is in very good agreement with the corresponding experimental data.PACS Nos.: 61.25.Em, 61.20.Gy

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.188
Teacher spread0.173 · 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 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

Citations3
Published2004
Admission routes1
Has abstractyes

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