A new semi-analytical model for effective thermal conductivity of nanofluids

A new theoretical model for thermal conductivity of nanofluids is developed incorporating effective medium theory, interfacial layer, particle aggregation and Brownian motion-induced convection from multiple nanoparticles/aggregates. The predicated result using aggregate size, which represents the particle size in the actual condition of nanofluids, fits well with the experimental data for water-, R113- and ethylene glycol (EG)-based nanofluids. The present model also gives much better predictions compared to the existing models. A parametric analysis, particularly particle aggregation, is conducted to investigate the dependence of effective thermal conductivity of nanofluids on the properties of nanoparticles and fluid. Aggregation is the main factor responsible for thermal conductivity enhancement. The dynamic contribution of Brownian motion on thermal conductivity enhancement is surpassed by that of static mechanisms, particularly at high volume fraction. Predication also indicated that the viscosity increases faster than the thermal conductivity, causing the highly aggregated nanofluids to become unfavourable, especially for d_f = 1.8.     

The thermal conductivity of alumina nanoparticles dispersed in ethylene glycol

The thermal conductivities of several nanofluids (dispersions of alumina nanoparticles in ethylene glycol) were measured at temperatures ranging from 298 to 411 K using a liquid metal transient hot wire apparatus. Our measurements span the widest range of temperatures that have been investigated to date for any nanofluid. A maximum in the thermal conductivity versus temperature behavior was observed at all mass fractions of nanoparticles, closely following the behavior of the base fluid (ethylene glycol). Our results confirm that additional temperature contributions inherent in Brownian motion models are not necessary to describe the temperature dependence of the thermal conductivity of nanofluids. Our results also show that the effect of mass or volume fraction of nanoparticles on the thermal conductivity of nanofluids can be correlated using the Hamilton and Crosser or Yu and Choi models with one adjustable parameter (the shape factor in the Hamilton and Crosser model, or the ordered liquid layer thickness in the Yu and Choi model).     

A comprehensive investigation in determination of nanofluids thermophysical properties

In recent years, research on heat transfer and related equipment has been one of the topics of interest in many different industries. The use of conventional fluids in heat transfer due to their low thermal properties has created problems in this area, so the use of nanofluids in many cases has been a solution to overcome this problem. The parameters affecting the thermophysical and thermal properties of nanofluids are temperature, concentration, size, shape, pH, surfactant and ultrasonic time, among which temperature and concentration have the greatest effect. Existing models and studies in the field of nanofluids are limited to the type of nanoparticles and base fluids and their operating range, and there is no comprehensive model for predicting thermal properties. In the present study, models and theories regarding the determination of thermal conductivity of nanofluids and other thermophysical properties have been comprehensively compiled and the mechanisms for increasing the thermal properties as well as the effective parameters and the effect of each of them on improving the properties are presented. In general, the results showed that thermal properties improve with increasing concentration and temperature. Finally, the role of nanofluids effect on thermal performance in the heat exchangers is studied and the results are summarized.     

A review on molten-salt-based and ionic-liquid-based nanofluids for medium-to-high temperature heat transfer

Molten-salt-based nanofluids and ionic-liquid-based nanofluids are developed for thermal storage and heat transfer at relatively high temperatures, in the past few years. Preparation and stabilization techniques are briefly introduced firstly, and then, thermal properties, e.g., specific heat, thermal conductivity and viscosity, are summarized and discussed in detail. The properties are not only affected by the characteristics of nanomaterials and base fluids, but also affected by the synthesis method, such as the sonication intensity and duration. Some of the thermophysical property data are still incomplete, especially the thermal conductivity of molten-salt-based nanofluids, and properties of ionic-liquid-based nanofluids at high temperatures. While several literature works show that the Krieger–Dougherty model can well predict the viscosity, no general models for thermal conductivity and specific heat have been developed yet for both types of nanofluids.

     

A model of nanofluids effective thermal conductivity based on dimensionless groups

Thermal conductivity is an important parameter in the field of nanofluid heat transfer. This article presents a novel model for the prediction of the effective thermal conductivity of nanofluids based on dimensionless groups. The model expresses the thermal conductivity of a nanofluid as a function of the thermal conductivity of the solid and liquid, their volume fractions, particle size and interfacial shell properties. According to this model, thermal conductivity changes nonlinearly with nanoparticle loading. The results are in good agreement with the experimental data of alumina-water and alumina-ethylene glycol based nanofluids.     

Viscosity of nanofluids: particle shape and fractal aggregates

Colloidal dispersions of nanoparticles in thermal base fluids are known to alter their spherical shapes thereby affecting their surface properties. This aspect has been investigated with respect to the effective viscosity of nanofluids presuming the particles to acquire the shape of prolate spheroid. Also, the contributions of the interfacial layer formed around these particles and their possible agglomeration has been taken in to account. The analysis has been carried out by modifying the Krieger and Dougherty model. The relative viscosity of these nanofluids has been computed as a function of volume fraction, particle size and the eccentricity of the particle. The model also incorporates the concept of fractal dimensions. The results thus obtained compare significantly well with the available experimental data and reaffirms an improvement over earlier models.     

Thermal performance of stable SiO2 nanofluids and regression correlations to estimate their thermophysical properties

The present work investigates the best mix ratio of Glycerol in Water as a medium to prepare a stable nanofluid. Increasing the proportion of glycerol enhances the aqueous mix's dynamic viscosity and improves the prepared nanofluid's stability. The thermal conductivity and viscosity of the Glycerol and Water mixtures determination were undertaken at various Glycerol ratios. The best percentage of glycerol in the mixture is found to have the least amount of thermal conductivity loss and the optimum viscosity gain. Silica (SiO₂) nanofluid of 0.25%, 0.5%, 1%, and 1.5% weight concentrations was prepared with this optimal mixture of Glycerol and Water. The stability of these SiO₂ nanofluids is evaluated by determining the zeta potential at different time intervals. The nanofluids prepared were observed to be stable for one month. The thermal conductivity and viscosity of the nanofluids are measured between the temperature limits of 30°–70°C. A peak increment of 32.1%and 46.3% in thermal conductivity and viscosity is observed. Furthermore, when the percentage enhancement ratio (PER) and Mouromtseff ratio of these nanofluids is examined, it is observed that they have more excellent thermal performance at higher temperatures. Regression correlations are developed to estimate the thermal conductivity and viscosity of the prepared nanofluids with a maximum deviation of 9%.     

Ionic-Liquid-Based Nanofluids and Their Heat-Transfer Applications: A Comprehensive Review

Due to the improved thermophysical characteristics of ionic liquids (ILs), such as their strong ionic conductivity, negligible vapor pressure, and thermal stability at high temperatures, they are being looked at viable contender for future heat transfer fluids. Additionally, the dispersing nanoparticles can further improve the thermophysical characteristics and thermal performance of ionic liquids, which is one of the emerging research interests to increase the heat transfer rates of the thermal devices. The latest investigations about the utilization of ionic liquid nanofluids as a heat transfer fluid is summarized in this work. These summaries are broken down into three types: (a) the thermophysical parameters including thermal conductivity, viscosity, density, and specific heat of ionic liquids (base fluids), (b) the thermophysical properties like thermal conductivity, viscosity, density, and viscosity of ionic liquids based nanofluids (IL nanofluids), and (iii) utilization of IL nanofluids as a heat transfer fluid in the thermal devices. The techniques for measuring the thermophysical characteristics and the synthesis of IL nanofluids are also covered. The suggestions for potential future research directions for IL nanofluids are summarized.     

Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network

The application of nanofluids in energy systems is developing day by day. Before using a nanofluid in an energy system, it is necessary to measure the properties of nanofluids. In this paper, first the results of experiments on the thermal conductivity of MgO/ethylene glycol (EG) nanofluids in a temperature range of 25–55 °C and volume concentrations up to 5 % are presented. Different sizes of MgO nanoparticles are selected to disperse in EG, including 20, 40, 50, and 60 nm. Based on the results, an empirical correlation is presented as a function of temperature, volume fraction, and nanoparticle size. Next, the model of thermal conductivity enhancement in terms of volume fraction, particle size, and temperature was developed via neural network based on the measured data. It is observed that neural network can be used as a powerful tool to predict the thermal conductivity of nanofluids.     

Determination of nanolayer thickness and effective thermal conductivity of nanofluids

Nanofluids having high thermal conductivity enhancement relative to conventional pure fluids are fluids engineered by suspending solid nanoparticles into base fluids. In the present study, calculating the Van der Waals interaction energy between a nanoparticle and an ordered liquid nanolayer around it, the nanolayer thickness was determined, the average velocity of the Brownian motion of nanoparticles in a fluid was estimated, and by taking into account both the aggregation of nanoparticles and the presence of a nanolayer a new thermal conductivity model for nanofluids was proposed. It has been shown that the nanolayer thickness in nanofluids is independent on the radius of nanoparticles when the radius of the nanoparticles is much greater than the nanolayer thickness and determines by the specific interaction of the given liquid and solid nanoparticle through the Hamaker constant, the surface tension and the wetting angle. It was proved that the frequency of heat exchange by fluid molecules is two orders of magnitude higher than the frequency of heat transfer by nanoparticles, so that the contribution due to the Brownian motion of nanoparticles in the thermal conductivity of nanofluids can be neglected. The predictions of the proposed model of thermal conductivity were compared with the experimental data and a good correlation was achieved.     

Thermal analysis for heat transfer enhancement in electroosmosis-modulated peristaltic transport of Sutterby nanofluids in a microfluidic vessel

Viscosity plays a crucial role in the flow and heat transfer process of nanofluids. To effectively calculate and predict the changing characteristics of nanofluids viscosity, this study presents a theoretical model combining the static interface layer and dynamic Brownian motion mechanisms of spherical nanoparticles for water-based Newtonian nanofluids. The model describes the reasonable dependences of nanofluids viscosity on physical properties of nanoparticles (density, volume fraction, size) and base fluid (temperature, viscosity, density). Taking four kinds of typical water-based Newtonian nanofluids containing spherical oxide nanoparticles (Al₂O₃, CuO, SiO₂ and TiO₂) as examples, the prediction performance of different viscosity models is analyzed in detail. From the comparison studies, it is demonstrated that the new viscosity model developed in this paper can exhibit better prediction performance than many well-known theoretical models and empirical correlations. Not only do the predicted results of model agree well with the experimental data from various studies, but also the effects of different factors are reflected effectively.

     

Synthesis of metal-based nanofluids and their thermo-hydraulic performance in compact heat exchanger with multi-louvered fins working under laminar conditions

Present experimental investigation incorporates characterization of Al nanopowder, synthesis of Al/water nanofluids, and effect of these nanofluids on thermal performance of compact heat exchanger. Al nanoparticles are characterized using TEM and XRD. Al/water nanofluid is prepared by dispersing metal basis aluminium nanoparticles of average 100 nm size into double distilled water at two different particle volume concentrations of 0.1 and 0.2%. The nanofluids are prepared by two-step method and cetyl trimethyl ammonium bromide surfactant is used to stabilize the nanofluid. Thermo-physical properties of nanofluids at two different concentrations and their variation with fluid temperature are measured experimentally. It is examined that thermal conductivity, viscosity, and density of the nanofluid increased with the increase of volume concentrations. Furthermore, by increasing the fluid temperature, thermal conductivity is intensified, while the viscosity and density are decreased. Heat transfer parameters are strong functions of these thermo-physical properties. Therefore, comprehensive findings on heat transfer coefficient, Nusselt number, colburn factor, friction factor, and effectiveness are determined experimentally for prepared nanofluids passing under laminar conditions through single-pass cross-flow compact heat exchanger attached with multi-louvered fins.

     

Effect of Reynolds number on heat transfer and flow for multi-oxide nanofluids using numerical simulation

A numerical simulation model for laminar flow of nanofluids in a pipe with constant heat flux at the wall has been built to study the effect of Reynolds number on heat transfer and pressure loss. The investigation was performed for metallic oxide and multi-oxide nanoparticles suspended in water. The thermal conductivity and dynamic viscosity were measured for a range of temperature (10–60 °C) and volume fraction of multi-oxide nanofluid. Comparison of the thermal conductivity for monocular oxide and multi-oxide nanofluids reveals a new way to control the enhancement in nanofluid conductivity. The numerical results obtained were compared with existing well-established correlations. The predictions of the Nusselt number for nanofluids are in agreement with the Shah correlation, and the deviation in the results is less than 1 %. It is found that the pressure loss increases with the Reynolds number, nanoparticle density, and volume fraction for multi-oxide nanoparticles. However, the flow demonstrates enhancement in heat transfer which improves with increasing Reynolds number of the flow.     

油基-金纳米流体的制备及热稳定性

分别采用N-十六烷基-N-(羟乙基)-N,N-二甲基溴化铵(CHDAB)和丁烷-1,4-二(N-十六烷基-N,N-二甲基溴化铵)(G16-4-16)2种阳离子表面活性剂作为金属表面修饰剂, 在石油醚/正丁醇/水混合体系中用KBH₄ 还原HAuCl₄制备出亲油性纳米金. 其中, 双子表面活性剂G16-4-16显示出更好的包裹分散作用, 其包裹的纳米金粒径分布范围较窄, 平均粒径为5.2 nm. 将该纳米金颗粒分散在液态烷烃、 甲苯和长链烷基醇等溶剂中可制成稳定的油基纳米流体. 采用紫外-可见光谱法跟踪热稳定性随时间的变化, 结果表明, 该纳米流体显示了较好的热稳定性, 在130 ℃稳定时间达20 h. 采用点热源法测定了该纳米流体的导热系数, 结果表明, 50 ℃时添加质量分数1.5%的纳米金可以使其导热系数增大约17%.     

Thermal conductivity and specific heat capacity measurements of Al2O3 nanofluids

Thermal conductivities and specific heat capacities of nanoparticles of Al₂O₃ dispersed in water and ethylene glycol as a function of the particle volume fraction and at temperatures between 298 and 338 K were measured. The steady-state coaxial cylinders method, using a C80D microcalorimeter (Setaram, France) equipped with special calorimetric vessels, was used for the thermal conductivities measurements. The heat capacities were measured with a Micro DSC II microcalorimeter (Setaram, France) with batch cells designed in our laboratory and the “scanning or continuous method.” The Hamilton–Crosser model properly accounts for the thermal conductivity of the studied nanofluids. Assuming that the nanoparticles and the base fluid are in thermal equilibrium, the experimental specific heat capacities of nanofluids are correctly justified.     

Synthesis and thermo-physical properties of water-based novel Ag/ZnO hybrid nanofluids

The comparative study on the thermo-physical properties of water-based ZnO nanofluids and Ag/ZnO hybrid nanofluids is reported in the present study. The outer surface of ZnO nanoparticles was modified with a thin coating of Ag nanoparticles by a wet chemical method for improved stability and heat transfer properties. The ZnO and Ag/ZnO nanofluids were prepared with varying volume concentration (??=?0.02–0.1%). The synthesized nanoparticles and nanofluids were characterized with different characterization methods viz., scanning electron microscopy, X-ray diffraction, dynamic light scattering, thermal conductivity measurement, and viscosity measurement. Results show that thermal conductivity of Ag/ZnO hybrid nanofluids is found to be significantly higher compared to ZnO nanofluids. The maximum thermal conductivity an enhancement for Ag/ZnO nanofluid (??=?0.1%) is found to 20% and 28% when it compared with ZnO nanofluid (??=?0.1%) and water, respectively.     

The noble effect of aging on the thermal conductivity of modified CNTs-ethylene glycol nanofluids

In order to improve the heat transfer process by using nanofluids, different nanoparticles and base fluids have been studied. In this work, stability and effect of aging and temperature on the thermal conductivity of CNTs-ethylene glycol (EG) nanofluids were investigated. Chemical functionalisation was used to oxidise the surface of CNTs. The functionalised CNTs were used to prepare the nanofluids by a two-step method. The stability of nanofluids was measured by UV-vis spectroscopy and the results showed that the nanofluids had a good stability over several days. Immediately after nanofluid preparation not too much increase was observed for thermal conductivity but the nanofluid aging had a great influence on the improvement of the thermal conductivity, as after 65 days, about 50% increase was observed. The increase has been attributed to forming an ordered nanolayer of EG molecules around the CNTs. Also no significant temperature dependence of thermal conductivity was observed up to 50°C possibly due to the lack of temperature dependence of CNTs Brownian motions.     

The Specific Heat Capacity,Effective Thermal Conductivity,Density, and Viscosity of Coolants Containing Carboxylic Acid Functionalized Multi-Walled Carbon Nanotubes

Obviously, the behavior of thermophysical properties of covalently functionalized CNT-based water and -based ethylene glycol (EG) nanofluids cannot be predicted from the predicted models. We present a study of the specific heat capacity, effective thermal conductivity, density, and viscosity of coolants containing functionalized multi-walled carbon nanotubes (CNT-COOH) with carboxylic acid groups at different temperatures. After synthesizing of CNT-COOH-based water and CNT-COOH-based EG nanofluids, measurements on the prepared coolant were made at various concentrations by different experimental methods. While the thermal conductivity of both nanofluids illustrated a significant increase, the specific heat capacity of both samples showed a downward behavior with increasing temperature. Although the thermal conductivity of CNT-COOH-based water nanofluids is bigger than CNT-COOH-based EG nanofluids, CNT-COOH-based water has weaker temperature dependence than that of the CNT-COOH-based EG nanofluids. The viscosity was investigated in different shear rates and temperatures. It is noteworthy that CNT-COOH-based EG nanofluids show relatively a non-Newtonian behavior. Interestingly, specific heat capacities of both prepared nanofluids were decreased with increasing concentration. Also, the density of the CNT-COOH-based water and -based EG nanofluids increased and decreased smoothly with increasing CNT-COOH concentration and temperature, respectively.     

Experimental determination of thermal conductivity and viscosity of different nanofluids and its effect on a hybrid solar collector

In this research, three different volume concentrations (??=?0.05, 0.1 and 0.2%) of Al₂O₃/water, CuO/water and Al₂O₃–CuO/water (50:50) nanofluids are prepared by adopting a two-step nanofluid preparation method. Al₂O₃ and CuO nanoparticles with the average diameter of 50 nm and 27 nm were dispersed in distilled water. The thermal conductivity and viscosity of prepared nanofluids are measured for different temperatures by using KD2 Pro thermal property analyzed and Brookfield viscometer, respectively. The effects of nanofluids on the thermal, electrical and overall efficiency of photovoltaic thermal (PVT) solar collector are also studied. The experimental results revealed that the thermal conductivity and viscosity increase with the increase in percentage volume concentration and viscosity decreases with the increase in temperature. Furthermore, the obtained maximum thermal and electrical efficiencies of a PVT solar collector for 0.2% volume concentration of hybrid nanofluids are 82% and 15%, respectively, at peak solar radiation. The highest overall efficiency of a PVT collector with .2% volume concentration of hybrid nanofluid was 97% at peak solar radiation. Results recommend that nanofluids can be used as a heat transfer in PVT solar collector.

     

A new parameter to control heat transport in nanofluids: surface charge state of the particle in suspension

Although various conjectures have been proposed to explain the abnormal increase in thermal conductivity of nanofluids, the detailed mechanism has not been fully understood and explained. The main reason is due to the lack of knowledge of the most fundamental factor governing the mechanisms such as Brownian motion, liquid layering, phonon transport, surface chemical effects, and agglomeration. Applying a surface complexation model for the measurement data of hydrodynamic size, zeta potential, and thermal conductivity, we have shown that surface charge states are mainly responsible for the increase in the present condition and may be the factor incorporating all the mechanisms as well.