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Thermal stability of carbon nanotube-based nanofluids for solar thermal collectors

2015· article· en· W1485449304 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials Research Innovations · 2015
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsMcGill University
Fundersnot available
KeywordsNanofluidCarbon nanotubeMaterials scienceChemical engineeringAbsorbanceThermal stabilitySolventCarbon fibersNanotechnologyOrganic chemistryComposite materialNanoparticleChromatographyChemistryComposite number

Abstract

fetched live from OpenAlex

AbstractCarbon nanotube dispersions are promising candidates for use as working fluids in high-performance solar collectors. However, one major stumbling block in the way of their widespread application is the difficulty in achieving stable nanofluid suspensions at elevated temperatures. In this study, the stability of plasma- and acid-functionalised multi-walled carbon nanotube dispersions at temperatures up to 150°C was investigated. Therminol 55 and propylene glycol were used as the main solvents, while water was used as a reference solvent. The results of UV-VIS-NIR absorption spectroscopy showed that no agglomeration occurred in the plasma-functionalised multi-walled carbon nanotube nanofluids heated to 150°C. However, minor variations were observed in the absorbance of acid-functionalised multi-walled carbon nanotubes in propylene glycol and therminol 55 base fluids at high temperatures.Keywords: Carbon nanotubesNanofluidsSolar collectorsThermal stability

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.

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)0.002
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 score0.004
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.102
GPT teacher head0.321
Teacher spread0.219 · 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