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Record W4389540997 · doi:10.17118/11143/20993

A review on recent progresses of nano/micro encapsulated phase changematerial slurries

2023· review· en· W4389540997 on OpenAlexafffund
Kasra Ghasemi, Syeda Humaira Tasnim, Shohel Mahmud

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsSlurryNano-Materials sciencePhase changeNanotechnologyPhase (matter)Engineering physicsEngineeringComposite materialChemistry

Abstract

fetched live from OpenAlex

Heat transfer fluids play a significant role in cooling or heating systems to maintain or obtain a particular temperature. A relatively novel concept is adding nano/microencapsulated phase change material (N/MPCM) to the carrier fluid to increase the heat capacity and improve the heat transfer rate. However, the applicability of using particles and their performance demand further investigations. In this study, a review of the recent progress has been made on using N/MPCM slurry as the working fluid is provided. The effects of particles’ thermophysical properties, including size, concentration, melting point and enthalpy, on different performance indicators such as exergy, efficiency, pumping power and performance evaluation criterion are among the covered topics. Although the promising potentials of MPCM slurry have increased interest in this field, there are still significant research gaps in the literature that are suggested for future investigations.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.251
GPT teacher head0.452
Teacher spread0.201 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes2
Has abstractyes

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