Predicting physical properties of nanofluids by computational modeling
Natalia Sizochenko , Michael Syzochenko , Agnieszka Gajewicz , Jerzy Leszczynski , Tomasz Puzyn
AbstractThe focal point of the current contribution was to develop global quantitative structure − property relationship (QSPR) models for nano fl uids. Two target properties, thermal conductivity and viscosity of nano fl uids, were thoroughly investigated. Under this investigation, a new database of thermal conductivity and viscosity of nano fl uids (more than 150 data points) was created. A hierarchical system of molecular representation re fl ecting features of nanoparticle ’ s structure at the di ff erent levels of organization was introduced. Also, size-dependent, volume-dependent, and intensive parameters were calculated. The model for thermal conductivity is characterized by determination coe ffi cient R 2 = 0.81 and root-mean-squared error RMSE = 0.055; the model for viscosity is characterized by R 2 = 0.79 and RMSE = 0.234. Developed models are in agreement with modern theories of nano fl uids behavior. Size- and concentration-related behavior of target properties were discussed. Findings suggest that the increase in surface area ratio and interfacial layer thickness and decrease in nanoparticles size lead to thermal conductivity and viscosity increase. Thermal conductivity and viscosity increase with an increase in weighted fraction-dependent parameters. Up-to-date, reliable theoretical models were created only for a single type of nanoparticles. In this article, developed models can simultaneously predict the thermal conductivity and viscosity in an e ff ective way using both size and volume concentration of nano fl uid.
|Journal series||The Journal of Physical Chemistry Part C: Nanomaterials, Interfaces and Hard Matter, ISSN 1932-7447|
|Publication size in sheets||0.5|
|Score|| = 35.0, 20-12-2017, ArticleFromJournal|
= 35.0, 20-12-2017, ArticleFromJournal
|Publication indicators||: 2016 = 4.536 (2) - 2016=4.796 (5)|
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