Computational and Experimental Study on the Stability of Nanofluids
Nanofluids, which are suspensions of nanoparticles dispersed in a base fluid, have remarkable potential in a wide range of applications. However, the stability of the nanofluid has remained a challenge and a matter of concern. A lot of research, development work and reviews have been conducted on th...
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| Veröffentlicht in: | Diffusion and defect data. Solid state data. Pt. A, Defect and diffusion forum Defect and diffusion forum, 2020-02, Vol.399, p.21-25 |
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| container_title | Diffusion and defect data. Solid state data. Pt. A, Defect and diffusion forum |
| container_volume | 399 |
| creator | Zaid, Hasnah Mohd Shukur, Muhammad Fadhlullah Abd Umar, M. Guan, Beh Hoe Kuah, Y.C. Roslan, A.A. |
| description | Nanofluids, which are suspensions of nanoparticles dispersed in a base fluid, have remarkable potential in a wide range of applications. However, the stability of the nanofluid has remained a challenge and a matter of concern. A lot of research, development work and reviews have been conducted on the preparation and stability of nanofluids. In this study, calculation of solubility parameter values using a molecular modelling software were performed to aid the screening of nanoparticles that are compatible with the base fluid. The solubility parameter is the numerical representation of the solvency behavior between two molecules. A molecular modelling software was used to study the solubility parameter values of nanoparticles to determine their compatibility with the base fluids. To validate the model, the computed values were compared against published literature and it was shown that the model has achieved more than 95% accuracy. The simulations were verified with experimental work with varying concentration of nanoparticles in brine solution and deionized water. Experimental results showed that zinc oxide nanoparticles demonstrated the best compatibility with the base fluid, which tally with the simulation. |
| doi_str_mv | 10.4028/www.scientific.net/DDF.399.21 |
| format | Article |
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However, the stability of the nanofluid has remained a challenge and a matter of concern. A lot of research, development work and reviews have been conducted on the preparation and stability of nanofluids. In this study, calculation of solubility parameter values using a molecular modelling software were performed to aid the screening of nanoparticles that are compatible with the base fluid. The solubility parameter is the numerical representation of the solvency behavior between two molecules. A molecular modelling software was used to study the solubility parameter values of nanoparticles to determine their compatibility with the base fluids. To validate the model, the computed values were compared against published literature and it was shown that the model has achieved more than 95% accuracy. The simulations were verified with experimental work with varying concentration of nanoparticles in brine solution and deionized water. 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To validate the model, the computed values were compared against published literature and it was shown that the model has achieved more than 95% accuracy. The simulations were verified with experimental work with varying concentration of nanoparticles in brine solution and deionized water. 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A lot of research, development work and reviews have been conducted on the preparation and stability of nanofluids. In this study, calculation of solubility parameter values using a molecular modelling software were performed to aid the screening of nanoparticles that are compatible with the base fluid. The solubility parameter is the numerical representation of the solvency behavior between two molecules. A molecular modelling software was used to study the solubility parameter values of nanoparticles to determine their compatibility with the base fluids. To validate the model, the computed values were compared against published literature and it was shown that the model has achieved more than 95% accuracy. The simulations were verified with experimental work with varying concentration of nanoparticles in brine solution and deionized water. 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| ispartof | Diffusion and defect data. Solid state data. Pt. A, Defect and diffusion forum, 2020-02, Vol.399, p.21-25 |
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| subjects | Compatibility Computational fluid dynamics Computer simulation Deionization Fluids Mathematical models Model accuracy Nanofluids Nanoparticles Saline water Software Solubility parameters Stability Zinc oxide |
| title | Computational and Experimental Study on the Stability of Nanofluids |
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