Comparison between Experimental and Theoretical Thermal Conductivity of Nanofluids Containing Multi-walled Carbon Nanotubes Decorated with TiO2 Nanoparticles

This article reports the thermal conductivity modeling of nanofluids containing decorated multi-walled carbon nanotubes with TiO₂ nanoparticles. TiO₂ nanoparticles and decorated multi-walled carbon nanotubes are synthesized with different amounts of TiO₂ nanoparticles. The experimental results show that the measured thermal conductivities of TiO₂ nanofluids and multi-walled carbon nanotube nanofluids are higher than the predicted values by theoretical models. The comparison results of multi-walled carbon nanotube nanofluids and multi-walled carbon nanotube–TiO₂ nanofluids reveal that the predicted values by the Xue model are closer to the measured values. In addition, the results show that the thermal conductivity of nanofluids containing multi-walled carbon nanotube–TiO₂ increases with respect to TiO₂ content of hybrid.     

Investigation of Laminar Convective Heat Transfer of a Novel Tio2–Carbon Nanotube Hybrid Water-Based Nanofluid

The current study was conducted to investigate the convective heat transfer coefficient of a novel TiO₂–CNT hybrid nanofluid through the shell-and-tube heat exchanger under a laminar flow and the effects of temperature and mass fraction on it. TiO₂–CNT hybrid nanofluids were prepared using a new and modified hydrolysis technique. The thermal conductivity of the TiO₂–CNT hybrid nanofluid and other thermo-physical properties were assessed. Results indicate that the effective thermal conductivity and heat transfer coefficient of the base fluid was influenced significantly and increased by the 0.2 wt% of this novel hybrid nanofluid in distilled water.     

Novel nanofluids based on mesoporous silica for enhanced heat transfer

Nanofluids, which are liquids with engineered nanometer-sized particles suspensions, have drawn remarkable attraction from the researchers because of their enormous potential to enhance the efficiency in heat-transfer fluids. In the present study, water-based calcined mesoporous silica nanofluids were prepared and characterized. The commercial mesoporous silica (MPSiO₂) nanoparticles were dispersed in deionized water by means of pH adjustment and ultrasonic agitation. MPSiO₂ nanoparticles were observed to have an average particle size of 350 ± 100 nm by SEM analysis. The concentration of MPSiO₂ was varied between 1 and 6 wt%. The physicochemical properties of nanofluids were characterized using various techniques, such as particle size analyzer, zeta-potential meter, TEM, and FT-IR. The thermal conductivity was measured by Transient Plane Source (TPS) method, and nanofluids showed a higher thermal conductivity than the base liquid for all the tested concentrations.     

Fabrication, characterization and measurement of thermal conductivity of Fe3O4 nanofluids

Magnetite Fe₃O₄ nanoparticles were synthesized by a co-precipitation method at different pH values. The products were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, and transmission electronic microscopy. Their magnetic properties were evaluated on a vibrating sample magnetometer. The results show that the shape of the particles is cubic and they are superparamagnetic at room temperature. Magnetic nanofluids were prepared by dispersing the Fe₃O₄ nanoparticles in water as a base fluid in the presence of tetramethyl ammonium hydroxide as a dispersant. The thermal conductivity of the nanofluids was measured as a function of volume fraction and temperature. The results show that the thermal conductivity ratio of the nanofluids increases with increase in temperature and volume fraction. The highest enhancement of thermal conductivity was 11.5% in the nanofluid of 3 vol% of nanoparticles at 40 °C. The experimental results were also compared with the theoretical models.     

Preparation and heat transfer properties of nanoparticle-in-transformer oil dispersions as advanced energy-efficient coolants

Three kinds of nanofluids are prepared by dispersing Al₂O₃ and AlN nanoparticles-in-transformer oil. The thermal conductivity of the nanoparticle–oil mixtures increases with particle volume fraction and thermal conductivity of the solid particle itself. The AlN nanoparticles at a volume fraction of 0.5% can increase the thermal conductivity of the transformer oil by 8% and the overall heat transfer coefficient by 20%. From the natural convection test using a prototype transformer, the cooling effect of Al₂O₃/AlN-oil nanofluids on the heating element and oil itself is confirmed. However, the excess quantity of surfactant has a harmful effect on viscosity, thermal property, chemical stability, and thus it is strongly recommended to control the addition of the surfactant with great care.     

Studies on Al<Subscript>2</Subscript>O<Subscript>3</Subscript>, CuO,and TiO<Subscript>2</Subscript> water-based nanofluids: A comparative approach in laminar and turbulent flow

The Prandtl number, Reynolds number and Nusselt number are functions of thermophysical properties of nanofluids, and these numbers strongly influence the convective heat transfer coefficient. The thermophysical properties vary with volumetric concentration of nanofluids. Therefore, a comprehensive analysis was performed to evaluate the effects on the performance of nanofluids due to variations of density, specific heat, thermal conductivity and viscosity, which are functions of nanoparticle volume concentration. Three metallic oxides, aluminum oxide (Al₂O₃), copper oxide (CuO), and titanium dioxide (TiO₂), dispersed in water as the base fluid were studied. A convenient figure of merit, known as the Mouromtseff number, is used as a base of comparisonfor laminar and turbulent flows. The results indicated that the considered nanofluids can successfully replace water in specific applications for a single-phase forced convection flow in a tube.     

Dispersion stability and thermal conductivity of propylene glycol-based nanofluids

The dispersion stability and thermal conductivity of propylene glycol-based nanofluids containing Al₂O₃ and TiO₂ nanoparticles were studied in the temperature range of 20–80 °C. Nanofluids with different concentrations of nanoparticles were formulated by the two-step method and no dispersant was used. In contrast to the common belief, the average particle size of nanofluids was observed to decrease with increasing temperature, and nanofluids showed an excellent stability over the temperature range of interest. Thermal conductivity enhancement for both studied nanofluids was a nonlinear function of concentration and was temperature independent. Theoretical analyses were also performed using existing models compared with experimental results. The model based on the aggregation theory appears to be the best.     

Analytical prediction of forced convective heat transfer of fluids embedded with nanostructured materials (nanofluids)

Nanofluids are a new class of heat transfer fluids developed by suspending nanosized solid particles in liquids. Larger thermal conductivity of solid particles compared to the base fluid such as water, ethylene glycol, engine oil etc. significantly enhances their thermal properties. Several phenomenological models have been proposed to explain the anomalous heat transfer enhancement in nanofluids. This paper presents a systematic literature survey to exploit the characteristics of nanofluids, viz., thermal conductivity, specific heat and other thermal properties. An empirical correlation for the thermal conductivity of Al₂O₃ + water and Cu + water nanofluids, considering the effects of temperature, volume fraction and size of the nanoparticle is developed and presented. A correlation for the evaluation of Nusselt number is also developed and presented and compared in graphical form. This enhanced thermophysical and heat transfer characteristics make fluids embedded with nanomaterials as excellent candidates for future applications.      

Application of SAXS to the study of particle-size-dependent thermal conductivity in silica nanofluids

Knowledge of the size and distribution of nanoparticles in solution is critical to understanding the observed enhancements in thermal conductivity and heat transfer of nanofluids. We have applied small-angle X-ray scattering (SAXS) to the characterization of SiO₂ nanoparticles (10–30 nm) uniformly dispersed in a water-based fluid using the Advanced Photon Source at Argonne National Laboratory. Size distributions for the suspended nanoparticles were derived by fitting experimental data to an established model. Thermal conductivity of the SiO₂ nanofluids was also measured, and the relation between the average particle size and the thermal conductivity enhancement was established. The experimental data contradict models based on fluid interfacial layers or Brownian motion but support the concept of thermal resistance at the liquid–particle interface.     

Intriguingly high convective heat transfer enhancement of nanofluid coolants in laminar flows

We reported on investigation of the convective heat transfer enhancement of nanofluids as coolants in laminar flows inside a circular copper tube with constant wall temperature. Nanofluids containing Al₂O₃, ZnO, TiO₂, and MgO nanoparticles were prepared with a mixture of 55 vol.% distilled water and 45 vol.% ethylene glycol as base fluid. It was found that the heat transfer behaviors of the nanofluids were highly depended on the volume fraction, average size, species of the suspended nanoparticles and the flow conditions. MgO, Al₂O₃, and ZnO nanofluids exhibited superior enhancements of heat transfer coefficient, with the highest enhancement up to 252% at a Reynolds number of 1000 for MgO nanofluid. Our results demonstrated that these oxide nanofluids might be promising alternatives for conventional coolants.     

Influence of pH on Nanofluids' Viscosity and Thermal Conductivity

Aiming at the dispersion stability of nanopartieles regarded as the guide of heat transfer enhancement, we investigate the viscosity and the thermal conductivity of Cu and Al2O3 nanoparticles in water under different pH values. The results show that there exists an optimal pH value for the lowest viscosity and the highest thermal conductivity, and that at the optimal pH value the nanofluids containing a small amount of nanoparticles have noticeably higher thermal conductivity than that of the base fluid without nanoparticles. For the two nanofluids the enhancements of thermal conductivity are observed up to 13% （Al2O3-water） or 15% （Cu-water） at 0.4 wt%, respectively. Therefore, adjusting the pH values is suggested to improve the stability and the thermal conductivity for practical applications of nanofluid.     

Physics and mechanics of heat exchange processes in nanofluid flows

Nanofluids present a new type of dispersed fluids consisting of a carrier fluid and solid nanoparticles. Unusual properties of nanofluids, particularly high thermal conductivity, make them eminently suitable for many thermophysical applications, e.g., for cooling of equipment, designing of new heat energy transportation and production systems and so on. This requires a systematic study of heat exchange properties of nanofluids. The present paper contains the measurement results for the heat transfer coefficient of the laminar and turbulent flow of nanofluids on the basis of distilled water with silica, alumina and copper oxide particles in a minichannel with circular cross section. The maximum volume concentration of particles did not exceed 2%. The dependence of the heat transfer coefficient on the concentration and size of nanoparticles was studied. It is shown that the use of nanofluids allows a significant increase in the heat transfer coefficient as compared to that for water. However, the obtained result strongly depends on the regime of flow. The excess of the heat transfer coefficient in the laminar flow is only due to an increase in the thermal conductivity coefficient of nanofluid, while in the turbulent flow the obtained effect is due to the ratio between the viscosity and thermal conductivity of nanofluid. The viscosity and thermal conductivity of nanofluids depend on the volume concentration of nanoparticles as well as on their size and material and are not described by classical theories. That is why the literature data are diverse and contradictory; they do not actually take into account the influence of the mentioned factors (size and material of nanoparticles). It has been shown experimentally and by a molecular dynamics method that the nanofluid viscosity increases while the thermal conductivity decreases with the decreasing dispersed particle size. It is found experimentally for the first time that the nanofluid viscosity coefficient depends on the particle material. The higher is the density of particles, the higher is the thermal conductivity coefficient of nanofluid.     

Effect of Nanoparticles on Thermal Properties Enhancement in Different Oils – A Review

The development of stable dispersion of nanoparticles in different oils is gaining momentum for close circuit applications as most of the mineral oils used are not very good thermal conductors. The enhancement of thermal conductivity with optimum enhancement of viscosity of oil with nanoparticles poses a serious challenge for use of such fluids in cooling. Transformer oil, mineral oil, silicon oil, hydrocarbon fuels, biodiesel, and some organic solutions have been used as the base fluids for studying the effect of nanoparticles for improving thermal efficiency. Innovative heat transfer fluids are produced by suspending metallic or nonmetallic nanometer-sized solid particles. Although a large number of sources are available on water-based nanofluids, the number of such reports on oil-based nanofluids is rather limited. The aim of this article is to summarize recent developments on the preparation methods of nanofluids based on oil, its stability, thermal conductivity enhancement, nanoparticle effect on viscosity, heat transfer characteristics, breakdown voltage, dielectric properties, and applications of such nanofluids.     

Effect of Brownian motion on flow and heat transfer of nanofluids over a backward-facing step with and without adiabatic square cylinder

A mathematical model to predict large enhancement of thermal conductivity of nanofluids by considering the Brownian motion is proposed. The effect of the Brownian motion on the flow and heat transfer characteristics is examined. The computations were done for various types of nanoparticles such as CuO, Al₂O₃, and ZnO dispersed in a base fluid (water), volume fraction of nanoparticles ? in the range of 1 % to 6 % at a fixed Reynolds number Re = 450 and nanoparticle diameter d_np = 30 nm. Our results demonstrate that Brownian motion could be an important factor that enhances the thermal conductivity of nanofluids. Nanofluid of Al₂O₃ is observed to have the highest Nusselt number Nu among other nanofluids types, while nanofluid of ZnO nanoparticles has the lowest Nu. Effects of the square cylinder on heat transfer characteristics are significant with considering Brownian motion. Enhancement in the maximum value of Nu of 29 % and 26 % are obtained at the lower and the upper walls of the channel, respectively, by considering the Brownian effects, with square cylinder, compared with that in the case without considering the Brownian motion. On the other hand, results show a marked improvement in heat transfer compared to the base fluid, this improvement is more pronounced on the upper wall for higher ?.     

Experimental comparison of Triton X-100 and sodium dodecyl benzene sulfonate surfactants on thermal performance of TiO2–deionized water nanofluid in a thermosiphon

This study investigates how TiO₂/deionized water nanofluids affect the thermal performance of a two-phase closed thermosiphon (TPCT) at various states of operation, according to the surfactant types. A straight copper tube with an inner diameter of 13 mm, outer diameter of 15 mm, and length of 1 m was used as the TPCT, i.e., heat pipe. The nanofluid utilizing in experiments was prepared by mixing the TiO₂ nano-particles at the rate of 1.3% and a surfactant at the rate of 0.5% with deionized water. The surfactants used for lowering the surface tension give rise to prevent the flocculation in nanofluids. In order to see the influences of the surfactants on the nanofluid properties, two types surfactants, Triton X-100 and sodium dodecyl benzene sulfonate (SDBS), were selected as nonionic and ionic surfactants and used in this study. The nanofluid was charged with in the ratio of 33.3% (equals to 44.2 ml) of the volume of the TPCT. To be able to make experimental comparisons, three different working fluids prepared under the same conditions in the same heat pipe were tested at three different heating powers (200, 300, and 400W) and three different coolant water flow rates (5, 7.5, and 10 g/s). The experiments were conducted for both TiO₂ and Triton X 100–deionized water nanofluid and TiO₂ and SDBS–deionized water nanofluid. The findings obtained from the tests were also compared to each other for showing off to what extent a surfactant affects the nanofluid properties. The maximum improvement in the thermal resistance was achieved by 43.26% in the experiment realized at 200 W input power and 7.5 g/s cooling water mass flow rate, in which the working fluid is TiO₂ and SDBS–deionized water nanofluid.     

A thermal conductivity model for nanofluids including effect of the temperature-dependent interfacial layer

The interfacial layer of nanoparticles has been recently shown to have an effect on the thermal conductivity of nanofluids. There is, however, still no thermal conductivity model that includes the effects of temperature and nanoparticle size variations on the thickness and consequently on the thermal conductivity of the interfacial layer. In the present work, the stationary model developed by Leong et al. (J Nanopart Res 8:245–254, 2006) is initially modified to include the thermal dispersion effect due to the Brownian motion of nanoparticles. This model is called the ‘Leong et al.’s dynamic model’. However, the Leong et al.’s dynamic model over-predicts the thermal conductivity of nanofluids in the case of the flowing fluid. This suggests that the enhancement in the thermal conductivity of the flowing nanofluids due to the increase in temperature does not come from the thermal dispersion effect. It is more likely that the enhancement in heat transfer of the flowing nanofluids comes from the temperature-dependent interfacial layer effect. Therefore, the Leong et al.’s stationary model is again modified to include the effect of temperature variation on the thermal conductivity of the interfacial layer for different sizes of nanoparticles. This present model is then evaluated and compared with the other thermal conductivity models for the turbulent convective heat transfer in nanofluids along a uniformly heated tube. The results show that the present model is more general than the other models in the sense that it can predict both the temperature and the volume fraction dependence of the thermal conductivity of nanofluids for both non-flowing and flowing fluids. Also, it is found to be more accurate than the other models due to the inclusion of the effect of the temperature-dependent interfacial layer. In conclusion, the present model can accurately predict the changes in thermal conductivity of nanofluids due to the changes in volume fraction and temperature for various nanoparticle sizes.     

Effect of multipolar interaction on the effective thermal conductivity of nanofluids

Nanofluids or liquids with suspended nanoparticles are likely to be the future heat transfer media, as they exhibit higher thermal conductivity than those of liquids. It has been proposed that nanoparticles are apt to congregate and form clusters, and hence the interaction between nanoparticles becomes important. In this paper, by taking into account the interaction between nearest-neighbour inclusions, we adopt the multiple image method to investigate the effective thermal conductivity of nanofluids. Numerical results show that then the thermal conductivity ratio between the nanoparticles and fluids is large, and the two nanoparticles are close up and even touch, and the point-dipole theory such as Maxwell--Garnett theory becomes rough as many-body interactions are neglected. Our theoretical results on the effective thermal conductivity of CuO/water and Al$_{2}$O$_{3}$/water nanofluids are in good agreement with experimental data.     

Preparation of alkaline solid polymer electrolyte based on PVA-TiO2-KOH-H2O and its performance in Zn-Ni battery

A novel composite alkaline polymer electrolyte based on poly(vinyl alcohol) (PVA) polymer matrix, titanium dioxide (TiO₂) ceramic fillers, KOH, and H₂O was prepared by a solution casting method. The properties of PVA-TiO₂-KOH alkaline polymer electrolyte films were studied by X-ray diffraction (XRD), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and AC impedance techniques. DSC and XRD results showed that the domain of amorphous region in the PVA polymer matrix augmented when TiO₂ filler was added. The SEM result showed that TiO₂ particles dispersed into the PVA matrix although some TiO₂ aggregates of several micrometers were formed. The alkaline polymer electrolyte showed excellent electrochemical properties. The room temperature (20 °C) ionic conductivity values of typical samples were between 0.102 and 0.171 S cm⁻¹. The Zn-Ni secondary battery with the alkaline polymer electrolyte PVA-TiO₂-KOH had excellent electrochemical property at the low charge-discharge rate.     

A new thermal conductivity model for nanofluids

In a quiescent suspension, nanoparticles move randomly and thereby carry relatively large volumes of surrounding liquid with them. This micro-scale interaction may occur between hot and cold regions, resulting in a lower local temperature gradient for a given heat flux compared with the pure liquid case. Thus, as a result of Brownian motion, the effective thermal conductivity, k_eff, which is composed of the particles conventional static part and the Brownian motion part, increases to result in a lower temperature gradient for a given heat flux. To capture these transport phenomena, a new thermal conductivity model for nanofluids has been developed, which takes the effects of particle size, particle volume fraction and temperature dependence as well as properties of base liquid and particle phase into consideration by considering surrounding liquid traveling with randomly moving nanoparticles.The strong dependence of the effective thermal conductivity on temperature and material properties of both particle and carrier fluid was attributed to the long impact range of the interparticle potential, which influences the particle motion. In the new model, the impact of Brownian motion is more effective at higher temperatures, as also observed experimentally. Specifically, the new model was tested with simple thermal conduction cases, and demonstrated that for a given heat flux, the temperature gradient changes significantly due to a variable thermal conductivity which mainly depends on particle volume fraction, particle size, particle material and temperature. To improve the accuracy and versatility of the k_effmodel, more experimental data sets are needed.