Brownian Motion Of Nanoparticles Research Articles

Lattice Boltzmann analysis of MHD natural convection of CuO-water nanofluid in inclined C-shaped enclosures under the effect of nanoparticles Brownian motion

In this study, Magneto-Hydro-Dynamic (MHD) natural convection heat transfer has been analyzed for an inclined C-shaped cavity filled with nanofluid. The Lattice Boltzmann Method (LBM) is used to solve the governing equations. The effective thermal conductivity and viscosity of nanofluid are calculated by KKL (Koo-Kleinstreuer-Li) correlation. The influence of pertinent parameters such as Rayleigh number, Hartmann number, the cavity inclination angle, nanoparticle volume concentration and the cavity aspect ratio on the flow and heat transfer characteristics have been examined. From this work, it is found that the heat transfer enhances when considering the Brownian motion effect of nanoparticles, whereas presence of magnetic field tries to retard convection. Moreover, the numerical results demonstrate that the average Nusselt is increased when increasing cavity aspect ratio, cavity angle and volume fraction of nanofluid. Also, the results demonstrate that the enclosure with an inclination angle of γ=π/2, has the maximum heat transfer coefficient.

On the nanoparticulate flow

Nanoparticulate flows occur in a wide range of natural and engineering applications hence have received much attention. The purpose of the present paper is to provide a brief review on the research on the nanoparticulate flow in some aspects which consist of the method of moment for solving the particle population balance equation, penetration efficiency, pressure drop and heat transfer in the turbulent nanoparticulate pipe flow, fluctuating-lattice Boltzmann model for Brownian motion of nanoparticles.

An analytical model for the determination of effective heat conduction of nanofluids

In this study, we use Maxwell’s homogenization method followed by mesoscopic analysis to study heat transfer in nanofluids. It is explored how microconvection resulting from the Brownian motion of nanoparticles and the nanolayer formation around nanoparticles are impacting the effective thermal conductivity of nanofluids. The heat transfer within the nanolayer is addressed by direct solution of the Boltzmann transport equation. The results obtained from experimental observations agree with model predictions.

Boundary Layer Flow and Heat Transfer in Nanofluid over a Stretching Sheet using Buongiorno Model and Thermophysical Properties of Nanoliquids

The boundary layer flow and heat transfer in nanofluid over a stretching sheet using Buongiorno model and thermophysical properties of nanoliquids is numerically studied. The governing partial differential equations are transformed into nonlinear ordinary differential equations by using the similarity variables and been solved numerically using shooting method for nanoparticles, namely silver Ag, copper Cu, alumina Al 2 O 3 and titania TiO 2 in water as based fluid with Prandtl number Pr = 6.2. The numerical results obtained for the local Nusselt number and the local Sherwood number as well as velocity, temperature and nanoparticle concentration profiles are presented graphically and discussed. The effects of Brownian motion Nb , thermophoresis Nt and nanoparticle volume fraction φ on the flow and heat transfer behaviours are discussed in detail. This study has shown that the stretching sheet is an unique solutions. Otherwise, when the nanoparticle volume fraction parameter increases, Brownian motion and thermophoresis parameters decrease, the local Nusselt number increases, but decreases the local Sherwood number.

Effects of nanoparticles Brownian motion in a linearly/sinusoidally heated cavity with MHD natural convection in the presence of uniform heat generation/absorption

In this numerical work, natural convection of CuO–water nanofluid and pure water in a cavity submitted to different heating modes on its vertical walls, is analyzed using the Lattice Boltzmann Method (LBM). The effective thermal conductivity and viscosity of nanofluid are calculated by KKL (Koo–Kleinstreuer–Li) correlation. The influence of pertinent parameters such as Rayleigh number (Ra=103–106), Hartmann number (Ha=0–80), heat generation or absorption coefficient (q=−10, −5, 0, 5, 10) and nanoparticle volume concentration (ϕ=0–0.04) on the flow and heat transfer characteristics has been examined. In general, by considering the role of Brownian motion, the enhancement in heat transfer is observed at any Hartman and Rayleigh numbers. In addition, the heat generation or absorption influences the heat transfer in the cavity at Ra=103 more than other Rayleigh numbers as the least effect is observed at Ra=106.

Generalized Scaling and the Master Variable for Brownian Magnetic Nanoparticle Dynamics.

Understanding the dynamics of magnetic particles can help to advance several biomedical nanotechnologies. Previously, scaling relationships have been used in magnetic spectroscopy of nanoparticle Brownian motion (MSB) to measure biologically relevant properties (e.g., temperature, viscosity, bound state) surrounding nanoparticles in vivo. Those scaling relationships can be generalized with the introduction of a master variable found from non-dimensionalizing the dynamical Langevin equation. The variable encapsulates the dynamical variables of the surroundings and additionally includes the particles’ size distribution and moment and the applied field’s amplitude and frequency. From an applied perspective, the master variable allows tuning to an optimal MSB biosensing sensitivity range by manipulating both frequency and field amplitude. Calculation of magnetization harmonics in an oscillating applied field is also possible with an approximate closed-form solution in terms of the master variable and a single free parameter.

Mixed convective thermally radiative micro nanofluid flow in a stretchable channel with porous medium and magnetic field

A numerical study is carried out for two dimensional steady incompressible mixed convective flow of electrically conductive micro nanofluid in a stretchable channel. The flow is generated due to the stretching walls of the channel immersed in a porous medium. The magnetic field is applied perpendicular to the walls. The impact of radiation, viscous dissipation, thermophoretic and Brownian motion of nanoparticles appear in the energy equation. A numerical technique based on Runge-Kutta-Fehlberg fourth-fifth order (RFK45) method is used to express the solutions of velocity, microrotation, temperature and concentration fields. The dimensionless physical parameters are discussed both in tabular and graphical forms. The results are also found in a good agreement with previously published literature work.

Finite Element Analysis of Unsteady Natural Convective Heat Transfer and Fluid Flow of Nanofluids inside a Tilted Square Enclosure in the Presence of Oriented Magnetic Field

In this paper, the problem of unsteady natural convective heat transfer flow of nanofluids having various sizes of nanoparticles inside an inclined square enclosure in the presence of oriented magnetic field is investigated numerically. The Brownian motion of nanoparticles is taken into consideration in the thermal conductivity model construction. Two opposite walls of the enclosure are insulated and the other two walls are kept at different temperatures. Galerkin weighted residual finite element technique has been employed to solve the governing nonlinear dimensionless equations. In order to ensure the accuracy of the present numerical code, comparisons with previously published works are performed and excellent agreement is obtained. The effects of model parameters such as Rayleigh number, Hartmann number, nanoparticles volume fraction, inclination angle of magnetic field, inclination angle of the geometry, diameter and Brownian motion of the nanoparticles on the fluid flow and heat transfer are investigated. The results indicate that an increment in Rayleigh number and nanoparticle volume fraction increases the heat transfer rate in a significant way, whereas, an increment in Hartmann number decreases the overall heat transfer rate. It is also observed that the heat transfer enhancement strongly depends on the diameter of the nanoparticles as well as the types of the nanofluids. It is observed that the time taken to reach the steady state is controlled by the different model parameters and in particular, it is longer for low Rayleigh number and shorter for high Rayleigh number. A comparison between the two studies of with and without Brownian motion shows that when Brownian motion is considered, the solid volume fraction has more significant effects on the heat transfer rate at all Rayleigh numbers considered in the square cavity. Finally, the distribution of average heat transfer rate for different cavity inclination angle along with various model parameters has been found as almost parabolic shape.

Thermal Performance Analysis of Nanofluid Thermal Conductivity Models in a Cooling Chamber

This study focused on the numerical modeling of mixed convection heat transfer in two-dimensional double lid-driven cavity filled with alumina–water nanofluid. Four different thermal conductivity models as well as experimental thermal conductivity data of Das et al. are used to estimate nanofluid thermal conductivity that incorporates the effects of nanoparticles concentration, Brownian motion, temperature, nanoparticle size, and interfacial-layer thickness. These models are used to evaluate the heat transfer enhancement and the increase of the average Nusselt number on a hot wall. The governing stream-vorticity equations are solved using a second-order central finite-difference scheme, coupled to the conservation of mass and energy. The main sensitive parameters of interest selected to investigate the thermal conductivity models are volume fraction of the nanoparticles (), Richardson number , and Reynolds number . The performance study of the thermal conductivity models and the interpretation of the corresponding results of isothermal lines, temperature profile, and average Nusselt number on a hot wall are done in a different range of , Richardson number, and Reynolds number for forced, mixed, and natural convections. As a result, it found that higher heat transfer is produced when the effects of nanoparticle size and interfacial-layer thickness are considered.

Combined effect of physical properties and convective heat transfer coefficient of nanofluids on their cooling efficiency

The advantages of using Al2O3, TiO2, SiO2 and CeO2 nanofluids as coolants have been investigated by analysing the combined effect of nanoparticles on thermophysical properties and heat transfer coefficient. The thermal conductivity and viscosity of these nanofluids were measured at two leading European universities to ensure the accuracy of the results. The relative thermal conductivity of nanofluids agreed with the prediction of the Maxwell model within +/−10% even at elevated temperature of 50°C indicating that the Brownian motion of nanoparticles does not affect thermal conductivity of nanofluids. The viscosity of nanofluids is well correlated by the modified Krieger–Dougherty model providing that the effect of nanoparticle aggregation is taken into account. It was found that at the same Reynolds number the advantage of using a nanofluid increases with increasing nanofluid viscosity which is counterintuitive. At the same pumping power nanofluids do not offer any advantage in terms of cooling efficiency over base fluids since the increase in viscosity outweighs the enhancement of thermal conductivity.

Rotation and migration of nanoparticles for heat transfer augmentation in nanofluids by molecular dynamics simulation

Nanofluids are a new generation of high-efficiency refrigerant with abnormal increased thermal conductivity and convective heat transfer properties. In view of the paucity of research work on the contribution of nanoparticle Brownian motion for the thermal conductivity augmentation, the present paper carries out a series of MD simulations to explorer the order of magnitude of nanoparticle Brownian motion and discusses the effect of nanoparticle Brownian motion for thermal conductivity enhancement of nanofluids. Various influence factors including nanoparticle shapes, sizes, and materials are considered. The Brownian motion of nanoparticles is decomposed into rotation and migration and calculated by MD simulation. By means of Peclet number, the effect of nanoparticle Brownian motion for thermal conductivity enhancement of nanofluids is discussed.

A theoretical model for nucleate boiling of nanofluids considering the nanoparticle Brownian motion in liquid microlayer

The forming of a porous layer of deposited nanoparticles on the heater surface is one of the unique phenomena in nucleate boiling of nanofluids. As the deposition of nanoparticles is induced by the evaporation of liquid microlayer, the average nanoparticle concentration in the microlayer is much higher than that in the bulk liquid. Therefore, the Brownian motion of nanoparticles in the microlayer may play an important role in dissipating heat from the heater surface. In this study, a new heat flux partitioning (HFP) model was proposed, in which a new heat flux component was incorporated to account for the heat transfer by nanoparticle Brownian motion in the liquid microlayer. The new heat flux component was formulated based on the latest experimental and theoretical research outcomes of microlayer evaporation. Comparison of the numerical results against the experimental data available in the literature proved that the new HFP model performs better than the classic HFP model. This study also demonstrated that the importance of nanoparticle Brownian motion is mainly controlled by the applied heat flux as it directly affects the number density of active sites on the heater surface. Finally, the effects of nanoparticle concentration, size and materials were also analyzed.

The influence of silica nanoparticles on hydrodynamics and mass transfer in spray liquid–liquid extraction column

In this research, the influence of silica nanoparticles on hydrodynamics and mass transfer of a spray liquid–liquid extraction column was studied experimentally. The chemical system of toluene−acetic acid–water was used, and the drops were toluene-based nanofluids containing 0.0005–0.01vol% silica nanoparticles. In addition to nanoparticles fraction in nanofluids, the effects of dispersed phase drop sizes were evaluated making use of three different distributors with different hole diameters. The experiments were performed at fixed volumetric flow rates of dispersed and continuous phases and mass transfer direction was from dispersed to continuous phase. The results showed that silica nanoparticles have no significant influence on the hydrodynamic parameters, while maximum enhancement of 47% in overall mass transfer coefficient was achieved using 0.001vol% silica nanoparticles for drops generated by the distributor with the largest hole diameter. At higher and lower nanoparticle concentrations, smaller overall mass transfer coefficient was observed. Brownian motion of nanoparticles and induced microconvection are dominant in low concentrations of nanoparticles resulting in enhanced mass transfer. Nanoparticle aggregation and reduction in free volume because of solid nanoparticles presence can be responsible for deteriorated mass transfer in higher nanoparticle concentrations.

Analytic-Numerical Modeling and Investigation of Nanostructures' Dynamics on Material Surfaces After Laser Irradiation

<p class="R-AbstractKeywords">The work is devoted to modeling the formation and behavior of solid nano-sized particles on the surface of materials. In the simulation, it is assumed that the main processing technology of surface nanostructures is laser irradiation, which causes the Brownian motion of nanoparticles, due mainly to thermal fluctuations: if the temperature around the nanoparticles is uniformly distributed, the time average of the Brownian fluctuations is zero; however, if there is a temperature gradient around the nanoparticles, the thermal fluctuations affect the nanoparticle in different ways from different sides, and there is a force like the thermophoretic force, biasing the average position of the nanoparticle. When building a 1D model of the formation and flow behavior of nanoparticles, three important assumptions are introduced: the impact of nanoparticles on the process of irradiation is negligible; the impact of nanoparticles on each other as compared to the effect of laser irradiation on them is also negligible; and nanoparticles after laser irradiation can move both forward and backward and at every fixed period of time, moving the nanoparticles does not impose any steric constraints. Under the above assumptions, a 1D continuous model is built, implicit and explicit finite difference schemes to solve it are developed; their convergence and order of convergence are studied; an output condition ensuring the stability of the explicit difference scheme is obtained, the unconditional stability of implicit difference scheme is proven, and software for computer implementation of some of the obtained analytical and numerical results developed. </p>

Thermal conductivity of nanofluids: Effect of Brownian motion of nanoparticles

The model of Xuan et al. (2003) for the thermal conductivity of nanofluids in which Brownian motion effect is added to the classical Maxwell's equation is discussed. The model is revised. Also, a different model is given and found to yield the same expression for the effective thermal conductivity after amending Xuan et al.'s model. The findings do not support the claim that Brownian motion of nanoparticles has a significant impact on thermal conductivity. Also, nanoparticles clustering is found to have a very minor effect on the effective thermal conductivity of nanofluids; however, the analysis may not be appropriate to draw conclusions about the impact of clustering. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2368–2369, 2015

Effect of temperature on the effective thermal conductivity of n-tetradecane-based nanofluids containing copper nanoparticles

Nanofluids were prepared by dispersing Cu nanoparticles (∼20nm) in n-tetradecane by a two-step method. The effective thermal conductivity was measured for various nanoparticle volume fractions (0.0001–0.02) and temperatures (306.22–452.66K). The experimental data compares well with the Jang and Choi model. The thermal conductivity enhancement was lower above 391.06K than for that between 306.22 and 360.77K. The interfacial thermal resistance increased with increasing temperature. The effective thermal conductivity enhancement was greater than that obtained with a more viscous fluid as the base media at 452.66K because of nanoconvection induced by nanoparticle Brownian motion at high temperature.

The biophysical properties of Basal lamina gels depend on the biochemical composition of the gel.

The migration of cells within a three-dimensional extracellular matrix (ECM) depends sensitively on the biochemical and biophysical properties of the matrix. An example for a biological ECM is given by reconstituted basal lamina gels purified from the Engelbreth-Holm-Swarm sarcoma of mice. Here, we compare four different commercial variants of this ECM, which have all been purified according to the same protocol. Nevertheless, in those gels, we detect strong differences in the migration behavior of leukocyte cells as well as in the Brownian motion of nanoparticles. We show that these differences correlate with the mechanical properties and the microarchitecture of the gels which in turn arise from small variations in their biochemical composition.

Statistical optimization of microchannel heat sink (MCHS) geometry cooled by different nanofluids using RSM analysis

In this work, an analytical investigation of the heat transfer for the microchannel heat sink (MCHS) cooled by different nanofluids (Cu, Al2O3, Ag, TiO2 in water and ethylene glycol as base fluids) is studied by the porous media approach and the Galerkin method and results are compared with numerical procedure. Response surface methodology (RSM) is applied to obtain the desirability of the optimum design of the channel geometry. The effective thermal conductivity and viscosity of the nanofluid are calculated by the Patel et al. and Khanafer et al. model, respectively, and MCHS is considered as a porous medium, as proposed by Kim and Kim. In addition, to deal with nanofluid heat transfer, a model based on the Brownian motion of nanoparticles is used. The effects of the nanoparticles volume fraction, nanoparticle type and size, base fluid type, etc., on the temperature distribution, velocity and Nusselt number are considered. Results show that, by increasing the nanoparticles volume fraction, the Brownian movement of the particles, which carries the heat and distributes it to the surroundings, increases and, consequently, the difference between coolant and wall temperature becomes less.

3D Numerical Investigation of Thermal Characteristics of Nanofluid Flow through Helical Tubes Using Two-Phase Mixture Model

This article presents numerical investigation of the heat transfer behavior of Al2O3/water nanofluid flow through helical tubes. Temperature-dependent thermal conductivity and the Brownian motion of nanoparticles in the nanofluid have also been taken into account. The results obtained indicate that the addition of nanoparticles into the base fluid will enhance the overall heat transfer coefficient in helical tubes. It was also concluded that the amount of increase in overall heat transfer coefficient with the addition of nanoparticles to the base fluid in a helical tube with smaller pitch circle diameter is more than a helical tube with higher pitch circle diameter.

Experimental and numerical investigation of turbulent nanofluid flow in helically coiled tubes under constant wall heat flux using Eulerian–Lagrangian approach

In the present study, turbulent flow in helically coiled tubes under constant wall heat flux is numerically and experimentally investigated. Pressure drop and convective heat transfer behavior of water and water–silver nanofluid are studied. In experimental section, the pressure drop measurements as well as the average convective heat transfer coefficient calculations are carried out. The numerical computations are performed by Eulerian–Lagrangian two-phase approach in connection with an RNG k–ε turbulence model accounting for four-way coupling collisions using ANSYS CFX software. The Brownian motion of nanoparticles is taken into account. Single-phase approach (homogeneous model with constant effective properties) is also used. Two-phase approach predicted much more accurate results than the homogeneous model. More enhanced heat transfer was observed for tubes with greater curvature ratio. The results showed that the nanoparticles did not change the axial velocity and turbulent kinetic energy significantly, while the micrometer-sized particles increased mean axial velocity and suppressed turbulence. It was found that the utilization of the base fluid in helical pipe with greater curvature ratio compared to the use of nanofluid in straight tubes increased heat transfer more effectively. Based on the numerical results validated by the experimental ones, two correlations were developed to predict the ratio of the mean heat transfer coefficient and the pressure drop of nanofluid to water in helical tubes.