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Record W4415005154 · doi:10.1016/j.molliq.2025.128692

Enhanced stability nanofluids for sustainable high-voltage transformer applications

2025· article· en· W4415005154 on OpenAlex
Samson Okikiola Oparanti, I. Fofana, Reza Jafari, Youssouf Brahami, Kouba Marie Lucia Yapi

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Molecular Liquids · 2025
Typearticle
Languageen
FieldEngineering
TopicPower Transformer Diagnostics and Insulation
Canadian institutionsUniversité du Québec à Chicoutimi
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsNanofluidTransformer oilMineral oilNanoparticlePulmonary surfactantDielectricDissipation factor

Abstract

fetched live from OpenAlex

The demand for sustainable alternatives to fossil-based insulating liquids in power transformers has intensified due to environmental concerns associated with mineral oils. Natural esters, such as canola oil, are renewable and biodegradable insulating liquids, but their adoption remains limited due to poor thermo-oxidative stability, ionization resistance, and standardization. To address these limitations, this study presents the development and characterization of a canola-based nanofluid enhanced with TiO 2 nanoparticles to improve its suitability for transformer insulation. TiO 2 nanoparticles with an average size of 5 nm were dispersed into canola oil using two surfactants, Polysorbate 80 and Span 80, at concentrations ranging from 2 g/L to 8 g/L. The novelty of this work lies in the use of ultra-fine (5 nm) TiO 2 nanoparticles combined with a comparative optimization of surfactant type and concentration to achieve long-term colloidal stability and improved dielectric performance, an approach previously unreported in this context. Nanofluid stability was assessed via turbidity measurements and visual inspection, with Span 80 demonstrating superior long-term stabilization. Results show that nanoparticles and surfactant addition slightly increased the density and viscosity of the base oil but remained within acceptable limits for transformer applications. Dielectric analysis revealed a reduction in dissipation factor with the addition of nanoparticles, with optimum performance at 0.2 wt% of nanoparticles and 2 g/L of surfactant. Furthermore, the AC breakdown voltage improved by 27.01 % at an optimal formulation of 0.2 wt% TiO 2 and 2 g/L Span 80. The developed nanofluid demonstrates strong potential as a sustainable and high-performance alternative to mineral oil for next-generation transformer applications. • Development of a canola-based nanofluid enhanced with TiO 2 nanoparticles. • Stability enhancement using Polysorbate 80 and Span 80 surfactants. • Span 80 demonstrated superior long-term stabilization through turbidity assessment. • Tan δ reduces with optimum performance at 0.2 wt% of TiO 2 and 2 g/L of Span 80. • BDV improved by 27.01 % at an optimal formulation of 0.2 wt% TiO 2 and 2 g/L Span 80.

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)0.000
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: none
Teacher disagreement score0.816
Threshold uncertainty score0.507

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 head0.004
GPT teacher head0.223
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