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Record W2026299300 · doi:10.1115/imece2004-61337

Thermophysical Properties of a Slurry of Distilled Water and Microencapsulated Phase-Change Materials

2004· article· en· W2026299300 on OpenAlexaff
David A. Scott, B. R. Baliga

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsSlurryDistilled waterMaterials scienceViscometerDifferential scanning calorimetryThermal conductivityCapillary actionPhase-change materialPhase (matter)Composite materialViscosityCore (optical fiber)Chemical engineeringThermodynamicsThermalChemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

This paper presents experimental measurements of some effective thermophysical properties of slurries consisting of microencapsulated phase change materials (MCPCMs) suspended in distilled water. The related apparatus and procedures are also presented and discussed. The MCPCMs considered here consist of a core of phase-change material (PCM), in this case a substance akin to octadecane, surrounded by a solid shell. The effective density of the slurries was measured using hydrometers. The effective thermal conductivity of the slurries was measured using an in-house designed apparatus. The effective kinematic viscosity of the slurries was measured using a series of glass capillary viscometers. A differential scanning calorimeter (DSC) was used to obtain the effective specific heat, melting and freezing temperatures of the core PCMs, and the latent heat of the slurries. Slurry concentrations between 0% (pure distilled water) and 20% by mass of the MCPCMs were considered in this investigation, at temperatures ranging from 5°C to 65°C. Where possible, the results have been compared to predictions obtained using available analytical expressions with properties of the constitutive materials as inputs.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.312

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 head0.055
GPT teacher head0.261
Teacher spread0.206 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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