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Green Synthesis, Characterization, and Empirical Thermal Conductivity Assessment of ZnO Nanofluids for High-Efficiency Heat-Transfer Applications.
Jebali, Meriem; Colangelo, Gianpiero; Gómez-Merino, Ana Isabel.
Afiliação
  • Jebali M; Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy.
  • Colangelo G; Department of Engineering for Innovation, University of Salento, 73100 Lecce, Italy.
  • Gómez-Merino AI; Department of Applied Physics II, University of Málaga, 29071 Málaga, Spain.
Materials (Basel) ; 16(4)2023 Feb 12.
Article em En | MEDLINE | ID: mdl-36837172
ZnO nanoparticles were synthesized using lemon juice and zinc nitrate (1:1) through the green method. The structure of the biosynthesized ZnO nanoparticles was analyzed by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA). The morphology and the size of ZnO nanoparticles were elucidated by transmission electron microscopy (TEM) and scanning electron microscopy (SEM). The powder was highly dispersed and irregularly shaped and the size of the nanoparticles ranged from 28 to 270 nm, depending on the shape of the particles. Thermal conductivity of the biosynthesized ZnO PG/W mixture 40:60 (v/v) nanofluids was measured within the temperature range of 20-70 °C. Experimental results revealed a linear increase in thermal conductivity with the rise of temperature and volume fraction. The enhancement of this parameter with temperature was probably due to the different shapes of the former agglomerates. They were broken by the thermal energy in aggregates of different forms. A correlation of these structures with temperature was established. Finally, an empirical model was developed for predicting thermal conductivity with particle volume fraction and temperature.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2023 Tipo de documento: Article