Publication:
A New Evaluation Strategy for Nanofluid Usage as a Coolant in PEM Fuel Cells

dc.authorscopusid57194852098
dc.authorscopusid57215829500
dc.authorscopusid57895305200
dc.authorwosidSahi̇n, Fevzi/L-8303-2018
dc.authorwosidAcar, Mahmut Caner/Nra-9568-2025
dc.authorwosidGenc, Omer/Kma-2266-2024
dc.contributor.authorGenc, Omer
dc.contributor.authorSahin, Fevzi
dc.contributor.authorAcar, Mahmut Caner
dc.contributor.authorIDAcar, Mahmut Caner/0000-0002-6206-5374
dc.date.accessioned2025-12-11T00:50:42Z
dc.date.issued2025
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Genc, Omer; Acar, Mahmut Caner] Nigde Omer Halisdemir Univ, Mech Engn Dept, Nigde, Turkiye; [Genc, Omer; Acar, Mahmut Caner] Nigde Omer Halisdemir Univ, T Nejat Veziroglu Clean Energy Res Ctr, Nigde, Turkiye; [Sahin, Fevzi] Ondokuz Mayis Univ, Mech Engn Dept, Samsun, Turkiyeen_US
dc.descriptionAcar, Mahmut Caner/0000-0002-6206-5374;en_US
dc.description.abstractNanofluids exhibit higher thermal performance than conventional fluids and are preferred as cooling fluids in thermal management of polymer electrolyte membrane (PEM) fuel cells. In order for a nanofluid to be used in PEM fuel cell cooling, it should have high stability, high heat removal performance, and low electrical conductivity (EC). In this study, the utilization of Fe3O4-water nanofluid in PEM fuel cell cooling was investigated using a novel technique that considered all three of these features into account. The nanofluid was synthesized in varying mass ratios of 0.1%-0.5% and its thermophysical properties, EC, and zeta potential were measured. According to the findings, when EC and stability were taken into account, the pH value of the Fe3O4-water nanofluid should exceed 7. The thermal performance of the nanofluids was assessed using the performance evaluation ratio (PER), Mouromtseff number (Mo), and h(r) under both laminar and turbulent flow conditions. A maximum heat transfer improvement of 19% for laminar and 18% for turbulent flow conditions was achieved at a mass ratio of 0.4%. In addition, an artificial neural network (R-2 = 0.9999, MSE = 0.000944) was used to model the EC. For the first time in the literature, a correlation was proposed to predict the EC of a nanofluid on the basis of pH and mass ratios.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.doi10.1002/fuce.70005
dc.identifier.issn1615-6846
dc.identifier.issn1615-6854
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-105004742101
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1002/fuce.70005
dc.identifier.urihttps://hdl.handle.net/20.500.12712/39664
dc.identifier.volume25en_US
dc.identifier.wosWOS:001516675700001
dc.identifier.wosqualityQ3
dc.language.isoenen_US
dc.publisherWiley-V CH Verlag GmbHen_US
dc.relation.ispartofFuel Cellsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial Neural Networken_US
dc.subjectElectrical Conductivityen_US
dc.subjectFe3O4en_US
dc.subjectPolymer Electrolyte Membrane (PEM) Fuel Cellen_US
dc.subjectThermal Conductivityen_US
dc.titleA New Evaluation Strategy for Nanofluid Usage as a Coolant in PEM Fuel Cellsen_US
dc.typeArticleen_US
dspace.entity.typePublication

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