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In addition, a new method is developed for calculating the extinction coefficient of the binary nanofluids based on the classical electromagnetic theory.
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In the present study, salt-based nanofluids based on eutectic mixtures of nitrate with SiO2 nanoparticles were studied.
Fig. 8 FoMs of GOnP/ EG + W) nanofluids based on thermophysical properties.
PEG and SDS were found to be good dispersants for the nanofluids based on TiO2 and SWCNHs, respectively.
Kulkarni et al. [16] investigated the thermal properties of aluminum oxide nanofluids based on the mixture of EG and water.
Quantitative analysis of the heat transfer capabilities of nanofluids based on experimental methods has been a topic of current interest.
Therefore, it is necessary to develop novel nanofluids based on the fluids other than these conventional fluids.
In this work, the thermophysical properties of nanofluids based on solar salt and graphene nanoplatelets (GNPs) were investigated.
Only the nanofluid based on TiO2 produced an increment of 5%.
This regression is a binary classifier based on one or more input variables.
Thus, in the proposed approach, we specially develop a binary classifier based on sparse representation.
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