Conductivity Enhancement Of Nanofluids Research Articles

Anomalous behavior of liquid molecules near solid nanoparticles: Novel interpretation on thermal conductivity enhancement in nanofluids

HypothesisRecently, it has been reported that anomalous improvement in the thermal conductivity of nanofluid composed of base liquids and dispersed solid nanoparticles, compared to the theoretically predicted value calculated from the particle fraction. Generally, the thermal conductivity values of gases and liquids are dominated by the mean free path of the molecules during translational motion. Herein, we present solid evidence showing the possible contribution of the vibrational behavior of liquid molecules around nanoparticles to increasing these thermal conductivities. ExperimentsThe behavior of liquid molecules in nanofluids containing SiO2 particles larger than 100 nm, which were dispersed in a 50 wt% aqueous solution of ethylene glycol, was investigated by means of small-angle neutron scattering, quasi-elastic neutron scattering, wide-angle X-ray scattering, and Raman spectroscopy. FindingsThe vibrational changes in the liquid molecules caused by the interactions between the nanoparticles and liquid molecules surrounding the nanoparticles contributed majorly to the increase in the thermal conductivity values of the SiO2 nanofluids. Because the vibration of liquid molecules is equivalent to phonon conduction in solids, the increase in thermal conductivity of the suspension due to the presence of nanoparticles was inferred to be derived from the limitation of the translational diffusion, which induces a solid-like behavior in the liquid.

Contributory effect of diffusive heat conduction and Brownian motion on thermal conductivity enhancement of nanofluids

The effect of diffusive heat conduction and Brownian motion on the enhancement of thermal conductivity in nanofluids is presented here. $${\hbox {Al}}_{2} {\hbox {O}}_{3}$$ and $${\hbox {TiO}}_{2}$$ nanofluids were prepared at four different wt. fractions of 1%, 0.5%, 0.1% and 0.05% and their thermal conductivity values were measured over temperatures ranging from 25 to $$55^{\circ }\hbox {C}$$ for every $$10 ^{\circ }\hbox {C}$$ interval. The thermal conductivity of nanofluids increased with the increase in concentration and temperature. Diffusive thermal conduction and Brownian motion contribute to thermal conductivity enhancement. However, diffusive heat conduction has major contribution to thermal conductivity enhancement in nanofluids. The thermal boundary resistance was found to be increasing with wt. fraction and decreasing with temperature elevation. Finally, a correlation is presented using group method of data handling (GMDH) neural network to predict the thermal conductivity of nanofluids.

Thermo-economic performance analysis of Al2O3-water nanofluids — An experimental investigation

This paper reports an experimental investigation on the thermophysical characterization, cooling capability and economic performance of Al2O3-water nanofluid. Al2O3 (20 nm–30 nm) nanoparticles are dispersed in water to prepare nanofluids by two-step method with no application of surfactant. Thermal conductivity and viscosity of Al2O3-water nanofluids were measured at different solid weight fractions of 0.0001, 0.0005, 0.001, 0.005 and 0.01 over the temperature range of 25 °C–60 °C for every 5 °C. The effect of concentration and temperature on thermal conductivity and viscosity of nanofluids were examined thoroughly. Thermal conductivity enhancement in nanofluids was prominent with variation in concentration and temperature. However, viscosity enhancement in nanofluids was only influenced by change in concentration. New correlations of thermal conductivity and viscosity based upon the experimental results have been proposed. Cooling capacity of nanofluids based on properties enhancement ratio (PER) were investigated and finally, economic analysis of the cooling performance of nanofluids has been presented.

The Effect of the Liquid Layer Around the Spherical and Cylindrical Nanoparticles in Enhancing Thermal Conductivity of Nanofluids

In this work, the equilibrium molecular dynamics (MD) simulation combined with the Green–Kubo method is employed to calculate the thermal conductivity and investigate the impact of the liquid layer around the solid nanoparticle (NP) in enhancing thermal conductivity of nanofluid (argon–copper), which contains the liquid argon as a base fluid surrounding the spherical or cylindrical NPs of copper. First, the thermal conductivity is calculated at temperatures 85, 85.5, 86, and 86.5 K and for different volume fractions ranging from 4.33% to 11.35%. Second, the number ΔN of argon atoms is counted in the liquid layer formed at the solid–liquid interface with the thickness of Δr = 0.3 nm around the NP. Finally, the number density n of argon atoms in this layer formed is calculated in all cases. Also, the results for spherical and cylindrical NPs are compared with one another. It is observed that the thermal conductivity of the nanofluid increased with the increasing volume fraction and the number ΔN. Likewise, the thermal conductivity of nanofluid containing spherical NPs is higher than that of nanofluid containing cylindrical NPs. Furthermore, the number density n of argon atoms near the surface of spherical NPs is higher than that of argon atoms attached in the curved surface of cylindrical NPs. As a result, the liquid layer around the solid NP has been considered one of the mechanisms responsible contributing to the thermal conductivity enhancement in nanofluids.

An explanation for anomalous thermal conductivity behaviour in nanofluids as measured using the hot-wire technique

Several efforts have been made to explain thermal conductivity enhancements in fluids due to the addition of nanoparticles. However, until now, there has been no general consensus on this issue. In this work a simple experiment is described that demonstrates a possible cause of misinterpretation of the experimental data of thermal conductivity obtained when using the hot-wire technique (HWT) in these systems. It has been demonstrated that the thermal conductivity of a two-layer sample of two non-miscible phase systems determined by means of the HWT must be modelled using a series thermal resistance model with consideration of the interfacial layers between different phases. This result sheds light on the thermal conductivity enhancement in nanofluids with respect to the values corresponding to the base fluid, suggesting that this increase can be explained using the above-mentioned model and not by application of empirical formulae for effective media, as done before.

Role of Thermal-Interaction Between Aggregated Particles in Thermal Conductivity Enhancement of Nanofluids

This study investigates the role of thermal-interaction (TI) between aggregated particles (APs) on the enhanced thermal conductivity of nanofluids. With the assumption of configurations of linear chain-like aggregates in the direction transverse to the thermal flux, two-dimensional heat conduction is considered for estimation of the effective thermal conductivity of regular arrays, which is separated into three components, namely, no thermal-interaction (NTI) effect, longitudinal thermal-interaction (LTI) effect, and transverse thermal-interaction (TTI) effect. We have obtained a solution to the 1D confine case of APs, and a thermal analysis is carried out for different confine systems to investigate their relatively quantitative assessments of thermal contribution to the enhanced effective thermal conductivity using the first-order approximation. We show that these effects are represented as a function of ϕ (where ϕ is the volume fraction of APs) for engineering purposes. It is also found that TI contribution to the enhanced thermal conduction reaches up to around 87.5% when APs contact with each other and that TTI has an important role in the range 0.3785 ≤ ϕ ≤ 0.7031 due to the confine effect of field-variation caused by transversely bidirectional thermal-interactions. When ϕ > 0.7031, LTI effect again plays key role in heat conduction in nanofluid systems owing to closed packing of APs. Consequently, to achieve energy-efficient heat transfer nanofluids that are required in many industrial applications, both APs' distribution configuration and APs' volume fraction have to be considered in the thermal analysis of nanofluids.

Toward nanofluids of ultra-high thermal conductivity

The assessment of proposed origins for thermal conductivity enhancement in nanofluids signifies the importance of particle morphology and coupled transport in determining nanofluid heat conduction and thermal conductivity. The success of developing nanofluids of superior conductivity depends thus very much on our understanding and manipulation of the morphology and the coupled transport. Nanofluids with conductivity of upper Hashin-Shtrikman (H-S) bound can be obtained by manipulating particles into an interconnected configuration that disperses the base fluid and thus significantly enhancing the particle-fluid interfacial energy transport. Nanofluids with conductivity higher than the upper H-S bound could also be developed by manipulating the coupled transport among various transport processes, and thus the nature of heat conduction in nanofluids. While the direct contributions of ordered liquid layer and particle Brownian motion to the nanofluid conductivity are negligible, their indirect effects can be significant via their influence on the particle morphology and/or the coupled transport.

The limiting behavior of the thermal conductivity of nanoparticles and nanofluids

We present experimental evidence of negative thermal conductivity enhancement in nanofluids consisting of 2 nm titania nanoparticles dispersed in 50% (w/w) water+ethylene glycol. This behavior is unlike that of other nanofluids, which have been shown to exhibit positive thermal conductivity enhancements. Our results for titania nanofluids suggest that the thermal conductivity of 2 nm titania nanoparticles is smaller than the thermal conductivity of the base fluid at the same temperature, indicating a dramatic decrease in the thermal conductivity of titania particles as the particle size becomes of the same order as the phonon mean free path. Although such a decrease has been predicted for semiconductor nanoparticles by theory and simulation, experimental evidence has hitherto been lacking. Our results provide indirect experimental evidence for this decrease in metal oxide particles, and validate our previous work on alumina nanofluids that showed an exponential decrease in the thermal conductivity of alumina particles with decreasing particle size, from a limiting value for large (micron-sized) particles.

Role of microconvection induced by Brownian motion of nanoparticles in the enhanced thermal conductivity of stable nanofluids

We investigate the role of microconvection induced by Brownian motion of nanoparticles on thermal conductivity enhancement in stable nanofluids containing nanoparticles of average diameters 2.8–9.5 nm. Nanofluids with a fixed particle loading of 5.5 vol. %, the effective thermal conductivity (k/kf) increases from 1.05 to 1.25 with increasing particle diameter. Upon increasing the aspect ratio of the linear chains in nanofluids, very large enhancement of thermal conductivity is observed. These findings confirm that microconvection is not the key mechanism responsible for thermal conductivity enhancements in nanofluids whereas aggregation has a more prominent role.

Discussion of proposed mechanisms of thermal conductivity enhancement in nanofluids

Based upon Green–Kubo linear response theory, we use the exact expression for the heat flux vector of the base fluid plus nanoparticle system to estimate the contribution of nanoparticle Brownian motion to thermal conductivity. We find that its contribution is too small to account for abnormally high reported values. The possibility of convection caused by Brownian particles is also found to be unlikely. We have estimated the mean free path and the transition speed of phonons in nanofluid through density functional theory. We found a layer structure can form around the nanoparticles and the structure does not further induce fluid–fluid phase transition in the bulk fluid. By analyzing the compressibility of the fluid, we have also investigated the sound speed in the nanofluid. For the models of an asymmetric hard sphere mixture representing the single spherical nanoparticles and a mixture of rods and hard spheres representing aggregates, both suspended in the fluid, we found that for the very low volume fraction cases, the compressibility changes little. This shows that the speed of phonon transition does not change due to the addition of nanoparticles of either type. Our results indicate that, besides the enhancement due to the high thermal conductivity of nanoparticles themselves, fluid molecules make no evident contribution to the enhancement of thermal conductivity attributable to the presence of the nanoparticles at volume fractions less than 5%.

Thermal conductivity and particle agglomeration in alumina nanofluids: Experiment and theory

In recent years many experimentalists have reported an anomalously enhanced thermal conductivity in liquid suspensions of nanoparticles. Despite the importance of this effect for heat transfer applications, no agreement has emerged about the mechanism of this phenomenon, or even about the experimentally observed magnitude of the enhancement. To address these issues, this paper presents a combined experimental and theoretical study of heat conduction and particle agglomeration in nanofluids. On the experimental side, nanofluids of alumina particles in water and ethylene glycol are characterized using thermal conductivity measurements, viscosity measurements, dynamic light scattering, and other techniques. The results show that the particles are agglomerated, with an agglomeration state that evolves in time. The data also show that the thermal conductivity enhancement is within the range predicted by effective medium theory. On the theoretical side, a model is developed for heat conduction through a fluid containing nanoparticles and agglomerates of various geometries. The calculations show that elongated and dendritic structures are more efficient in enhancing the thermal conductivity than compact spherical structures of the same volume fraction, and that surface (Kapitza) resistance is the major factor resulting in the lower than effective medium conductivities measured in our experiments. Together, these results imply that the geometry, agglomeration state, and surface resistance of nanoparticles are the main variables controlling thermal conductivity enhancement in nanofluids.

Temperature-dependent thermal conductivity of nanorod-based nanofluids

In this work, the temperature dependence of thermal conductivity enhancement in nanofluids containing Bi2Te3 nanorods has been studied. The Bi2Te3 nanorods of average diameter 20nm and length 170nm are synthesized using the sonochemical technique. The 3ω-wire method has been developed to measure the thermal conductivity of nanofluids. The thermal conductivity enhancement in the nanorods-in-FC72 and the nanorods-in-oil nanofluids has been experimentally found to decrease with increasing temperature, in contrast to the trend observed in nanofluids containing spherical nanoparticles. The contrary trend is attributable mainly to the particle aspect ratio.

Enhanced Mass Transport in Nanofluids

Thermal conductivity enhancement in nanofluids, which are liquids containing suspended nanoparticles, has been attributed to localized convection arising from the nanoparticles' Brownian motion. Because convection and mass transfer are similar processes, the objective here is to visualize dye diffusion in nanofluids. It is observed that dye diffuses faster in nanofluids compared to that in water, with a peak enhancement at a nanoparticle volume fraction, phi, of 0.5%. A possible change in the slope of thermal conductivity enhancement at that same phi signifies that convection becomes less important at higher phi. The enhanced mass transfer in nanofluids can be utilized to improve diffusion in microfluidic devices.