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Numerical Modeling of Magnetic Nanoparticle and Carrier Fluid Interactions Under Static and Double-Shear Flows.
- Source :
- IEEE Transactions on Nanotechnology; Sep2017, Vol. 16 Issue 5, p798-805, 8p
- Publication Year :
- 2017
-
Abstract
- Magnetic nanoparticles are widely utilized in smart materials, the most well-known application being magnetorheological fluids. In this paper, a comprehensive numerical model of magnetic nanoparticles and the carrier fluid interactions is presented. The soft sphere model approach is adopted to simulate the nanoparticle interactions at a coarse molecular level, with the consideration of both contact and noncontact particle interactions. Magnetic dipole theory is used to simulate the particle behavior under external magnetic fields. The carrier fluid flow is solved using the computational fluid dynamics approach with a two-way coupling with the nanoparticles. Based on the present model, simulations have been conducted for both static fluid and dynamic double-shear flow cases. Without the presence of an external magnetic field, local particle clusters are formed as a result of van der Waals attraction between the particles. When the external magnetic field is present, chain-like structures of nanoparticles are observed for both the static and dynamic cases parallel to the direction of the applied magnetic field. For the static case, the formation of the chain-like structures is rapid, and “steady state” is reached within a short time (∼1 ms). In the double-shear flow case, the chain-like structures are found to be much thinner and shorter than the static case. The developed model provides a fundamental understanding of the real physics of magnetic nanoparticles and carrier fluid interactions. It also enables future investigations in optimizing physical and transport properties of smart materials. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 1536125X
- Volume :
- 16
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Nanotechnology
- Publication Type :
- Academic Journal
- Accession number :
- 125027742
- Full Text :
- https://doi.org/10.1109/TNANO.2017.2691018