Influence of CuO nanoparticles and oil concentration on the thermodynamic properties of R600a during forced boiling convection

The effects of copper oxide (CuO) nanoparticles and Polyalphaolefin (PAO) lubricating oil on the thermophysical transport parameters of R600a (isobutane) and its flow boiling heat transfer coefficient are evaluated in this work using semi-empirical correlations. Commonly occurring refrigerant–oil mixes in vapor compression refrigeration cycles result from lubrication needs in system components, affecting both transport qualities and heat transfer performance. Considering the effect produced by the heat flows, 10 kW/m 2 , 15 kW/m 2 and 20 kW/m 2 , to which the fluids are being subjected. This work investigates refrigerant combinations with a maximum nanoparticle–oil ratio of 5% resulting in three formulations: R600a/CuO, R600a/PAO, and R600a/CuO/PAO as modest nanoparticle concentrations can improve these qualities. Key thermal transport parameters, including density, thermal conductivity, dynamic viscosity, and specific heat, show improvement by CuO nanoparticles with oil. Still, the R600a/CuO/PAO mixture shows hardly any variation from pure R600a. The Gungor and Winterton correlation assessed the forced flow boiling heat transfer coefficient. The results reveal that whilst PAO oil reduces the coefficient at 5%, the coefficient rises with increasing concentrations of nanoparticles in the refrigerant. The heat transfer coefficient decreases slightly when both CuO and PAO are present.

Authors

Institutions

Publication Details

Journal
International Journal of Thermofluids
Published
2025-08-18
DOI
https://doi.org/10.1016/j.ijft.2025.101372
Primary Topic
Nanofluid Flow and Heat Transfer
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Influence of CuO nanoparticles and oil concentration on the thermodynamic properties of R600a during forced boiling convection

Fernando Toapanta-Ramos, César Nieto‐Londoño
5 links
International Journal of Thermofluids
Nanofluid Flow and Heat Transfer
article

Influence of CuO nanoparticles and oil concentration on the thermodynamic properties of R600a during forced boiling convection

Fernando Toapanta-Ramos, César Nieto‐Londoño
article en

Abstract

The effects of copper oxide (CuO) nanoparticles and Polyalphaolefin (PAO) lubricating oil on the thermophysical transport parameters of R600a (isobutane) and its flow boiling heat transfer coefficient are evaluated in this work using semi-empirical correlations. Commonly occurring refrigerant–oil mixes in vapor compression refrigeration cycles result from lubrication needs in system components, affecting both transport qualities and heat transfer performance. Considering the effect produced by the heat flows, 10 kW/m 2 , 15 kW/m 2 and 20 kW/m 2 , to which the fluids are being subjected. This work investigates refrigerant combinations with a maximum nanoparticle–oil ratio of 5% resulting in three formulations: R600a/CuO, R600a/PAO, and R600a/CuO/PAO as modest nanoparticle concentrations can improve these qualities. Key thermal transport parameters, including density, thermal conductivity, dynamic viscosity, and specific heat, show improvement by CuO nanoparticles with oil. Still, the R600a/CuO/PAO mixture shows hardly any variation from pure R600a. The Gungor and Winterton correlation assessed the forced flow boiling heat transfer coefficient. The results reveal that whilst PAO oil reduces the coefficient at 5%, the coefficient rises with increasing concentrations of nanoparticles in the refrigerant. The heat transfer coefficient decreases slightly when both CuO and PAO are present.

International Journal of ThermofluidsVol. 29
Universidad Pontificia Bolivariana (CO), Politecnica Salesiana University (EC)
Universidad Politécnica Salesiana del Ecuador
Openalex Percentile: Top 80%
Nanofluid Flow and Heat Transfer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.