The dynamic viscosity and rheological properties of two different non-aqueous graphene nano-plates-based nanofluids are experimentally investigated in this paper, focusing on the effects of solid volume fraction and shear rate. For each nanofluid, four solid volume fractions have been considered ranging from 0.1% to 1%. The rheological characterization of the suspensions was performed at 20 ∘C, with shear rates ranging from 10−1s−1 to 103s−1, using a cone-plate rheometer. The Carreau–Yasuda model has been successfully applied to fit most of the rheological measurements. Although it is very common to observe an increase of the viscosity with the solid volume fraction, we still found here that the addition of nanoparticles produces lubrication effects in some cases. Such a result could be very helpful in the domain of heat extraction applications. The dependence of dynamic viscosity with graphene volume fraction was analyzed using the model of Vallejo et al.
We report, in this work, our study of the thermal conductivity of high-viscosity nanofluids based on glycerol. Three nanofluids have been prepared with different thermal contrasts, by suspending graphene flakes, copper oxides, or silica nanoparticles in pure glycerol. The nanofluids were thermally characterized at room temperature with the 3ω technique, with low amplitudes of the temperature oscillations. A significant enhancement of the thermal conductivity is found in both the glycerol/copper oxide and the glycerol/graphene flake nanofluids. Our results question the role played by the Brownian motion in the microscopic mechanisms of the thermal conductivity of high-viscosity glycerol-based nanofluids. A similar behavior of the thermal conductivity as a function of the nanoparticle volume fraction was found for all three glycerol-based nanofluids presently investigated. These results could be explained on the basis of fractal aggregation in the nanofluids.
In this chapter, we present a study on the electronic properties of diamond carbon, using band structure and density of states calculations. The calculations are based on the use of the grid-based projector-augmented wave (GPAW) and atomic simulation environment (ASE) methods. The main results of our work are the optimization of diamond energy (to −17.57 eV) and the calculation of the gap with the PBE (Perdew, Burke, and Ernzerhof) and the functional hybrid PBE0 hybrid functional, which is about 5.368 eV (the closest value to the value found in the literature). We were also able to reproduce the experimental value of the lattice constant of diamond to within 0.2% for PBE0 and 0.4% for PBE. Our results contribute to the study of the electronic properties of diamond using GPAW and ASE simulation, which is a set of Python modules, designed to facilitate the setup, execution, and analysis of atomic/electronic calculations. This tight integration of ASE and GPAW should be exploited in future research of the electronic properties of diamond, which is one of the most promising materials for the integrated electronic and photonic, radio, optoelectronic, and quantum devices industry. This chapter provides interesting information for the theoretical and experimental communities working in this field.
Taking into account the Basset force (memory term), in the balance of the forces exerted on a colloidal particle (CP) suspended in a fluid, results in an equation of motion of integrodifferential form. This type of equation allows for example to modeling a colloidal particle settling in an quiescent fluid or in a fluid flowing at low particle’s Reynolds number. It also allows to study the transport of pathogens via aerosols, thus giving access to important information on the airborne propagation of respiratory viruses, such as COVID-19 and its variants for example. Most studies of the PCs motion in a fluid are usually simplified by not taking into account the Basset memory force, as it considerably complicates the numerical solution of the equations of motion of these PCs. This simplification can lead to considerable errors in the evaluation of the trajectory and velocity of the PCs, which can subsequently lead to errors in the calculation of the physical and rheological properties of colloidal suspensions. The present study deals with the numerical solution of Basset’s integro-differential equation, by two significantly different approaches, namely : a piecewise linear approximation (PLA) and the method of Basset numerical filters (BNF). These methods are first exposed and compared on test cases, they are then applied to the study of the sedimentation of spherical PCs with micrometer radii. This study has shown that the usual dynamics of PCs, which does not take into account the Basset memory term, can be very different from the exact dynamics using the Basset force. The BNF approach is finally applied to the study of the motion of PCs driven by flows through complex geometries (pipes, porous media, …).
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