Comments on the effect of liquid layering on the thermal conductivity of nanofluids

This article provides critical examinations of two mathematical models that have been developed in recent years to describe the impact of nano-layering on the enhancement of the effective thermal conductivity of nanofluids. Discrepancy between the two models is found to be an artefact of an incorrect derivation used in one of the models. With correct formulation, both models predict effective thermal conductivity enhancements that are not significantly greater than those predicted by classical Maxwell theory. This study indicates that nano-layering by itself is unable to account for the effective thermal conductivity enhancements observed in nanofluids.     

纳米悬浮液的有效导热系数

文中以有效介质近似理论为基础,考虑了纳米颗粒在基液中强烈的B rown ian运动对强化传热的作用和纳米颗粒的表面吸附液体层、纳米颗粒的粒径和体积分数对纳米悬浮液有效导热系数的影响,建立了预测纳米悬浮液有效导热系数的模型,通过对纳米CuO-去离子水溶液的验证,发现该模型比几种经典模型具有更高的精度,因此具有一定的参考价值。     

A cell model approach for thermal conductivity of nanofluids

This work presents a cell model for predicting the thermal conductivity of nanofluids. Effects due to the high specific surface area of the mono-dispersed nanoparticles and the micro-convective heat transfer enhancement associated with the Brownian motion of particles are addressed in detail. Novelty of the paper lies in its prediction of the non-linear dependence of thermal conductivity of nanofluids on particle volume fraction at low particle concentrations. The model is found to correctly predict the trends observed in experimental data over a wide range of particle sizes, temperatures and particle concentrations.     

The effect of particle size on the thermal conductivity of alumina nanofluids

We present new data for the thermal conductivity enhancement in seven nanofluids containing 8–282 nm diameter alumina nanoparticles in water or ethylene glycol. Our results show that the thermal conductivity enhancement in these nanofluids decreases as the particle size decreases below about 50 nm. This finding is consistent with a decrease in the thermal conductivity of alumina nanoparticles with decreasing particle size, which can be attributed to phonon scattering at the solid–liquid interface. The limiting value of the enhancement for nanofluids containing large particles is greater than that predicted by the Maxwell equation, but is predicted well by the volume fraction weighted geometric mean of the bulk thermal conductivities of the solid and liquid. This observation was used to develop a simple relationship for the thermal conductivity of alumina nanofluids in both water and ethylene glycol.     

Dispersibility dependence of thermal conductivity of carbon nanotube based nanofluids

A differential effective medium theory together with Brownian motion is used to predict Effective Thermal Conductivity (ETC) of CNT nanofluids. ETC was influenced significantly by Brownian motion and enhancement was higher in dilute nanofluids. A theoretical model employing an effective volume fraction with dispersibility factor agrees well with experimental data.     

Understanding of temperature and size dependences of effective thermal conductivity of nanotubes

The anomalous thermal transport properties of nanotubes may lead to many important applications, but the mechanisms are still unclear. In this work, we present new governing equations for non-Fourier heat conduction in nanomaterials based on the concept of thermomass. The effective thermal conductivities of nanotubes are therefore predicted which agree very well with the available experimental data. Analysis suggests that the inertial effect of heat and the confined heat flux by nanostructured surfaces are two key mechanisms causing the anomalous temperature and size dependences of effective thermal conductivity of nanotubes.     

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.     

Thermal conductivity of nanofluids and size distribution of nanoparticles by Monte Carlo simulations

Nanofluids, a class of solid–liquid suspensions, have received an increasing attention and studied intensively because of their anomalously high thermal conductivites at low nanoparticle concentration. Based on the fractal character of nanoparticles in nanofluids, the probability model for nanoparticle’s sizes and the effective thermal conductivity model are derived, in which the effect of the microconvection due to the Brownian motion of nanoparticles in the fluids is taken into account. The proposed model is expressed as a function of the thermal conductivities of the base fluid and the nanoparticles, the volume fraction, fractal dimension for particles, the size of nanoparticles, and the temperature, as well as random number. This model has the characters of both analytical and numerical solutions. The Monte Carlo simulations combined with the fractal geometry theory are performed. The predictions by the present Monte Carlo simulations are shown in good accord with the existing experimental data.     

Effective conductivity and skew Brownian motion

We consider heat conduction in a periodic body which is composed of finitely many different components. The effective conductivity is represented in terms of skew Brownian motion. The representation formula is a fluctuation-dissipation relation. The dissipation term in this formula is related to the transmission of heat through the surface separating the different components of the body; it is described by the skew reflections of Brownian motion at these surfaces. The problems caused by the discontinuity of the microscopic conductivity are handled in the framework of Dirichlet forms.     

Investigation on characteristics of thermal conductivity enhancement of nanofluids

It has been shown that a nanofluid consisting of nanoparticles dispersed in base fluid has much higher effective thermal conductivity than pure fluid. In this study, four kinds of nanofluids such as multiwalled carbon nanotube (MWCNT) in water, CuO in water, SiO₂ in water, and CuO in ethylene glycol, are produced. Their thermal conductivities are measured by a transient hot-wire method. The thermal conductivity enhancement of water-based MWCNT nanofluid is increased up to 11.3% at a volume fraction of 0.01. The measured thermal conductivities of MWCNT nanofluids are higher than those calculated with Hamilton–Crosser model due to neglecting solid–liquid interaction at the interface. The results show that the thermal conductivity enhancement of nanofluids depends on the thermal conductivities of both particles and the base fluid.     

Fractal analysis for effective thermal conductivity of random fibrous porous materials

In this Letter, a fractal series-parallel model, which included numerous capillary channels both parallel and perpendicular to the heat flow direction, was established to predict the effective thermal conductivity of fibrous porous material (FPM). The prediction results from the proposed model are compared with calculated values from other theoretical models and experimental data.     

On the role of structural disjoining pressure to boiling heat transfer of thermal nanofluids

Research on nanofluids has progressed rapidly since their enhanced thermal conductivities were identified about a decade ago. For boiling heat transfer with nanofluids, however, many contradictory results have been reported, which cannot be explained by conventional theories developed for pure fluids. Recent progress in colloidal science shows that the presence of nanoparticles could enhance the spreading and wettability of base fluids through a long-range structural disjoining pressure. This article explores theoretically the influence of structural disjoining pressure to the nucleate boiling heat transfer through a four-zoned microlayer evaporation model. The influence of particle size, particle concentration, and heat flux on the structural disjoining pressure and the interfacial shape of the microlayer are investigated. The calculated equilibrium interfacial shape shows that the meniscus is displaced toward the vapor phase in the presence of nanoparticles, an implication of enhanced wettability. Such an improved wettability affects the number of active nucleate sites and bubble dynamics significantly, which could be one of the important parameters that is responsible for the controversy of boiling heat transfer with nanofluids reported in the literature.     

金属纳米颗粒对水合物的导热影响

使用分子动力学模拟方法,在温度为200－280K的NVT系综下,对纳米粒子－CO2水合物复合体系进行模拟计算,研究了不同种类（Ag, Cu, Fe）、不同粒径 (1.0nm, 1.5nm, 2.0nm) 的球形纳米粒子对水合物导热性能的影响,从体系构型、导热系数、纳米粒子运动速度等方面探究纳米粒子对水合物导热性能的强化机理。 模拟结果表明,纳米粒子的加入,不影响水合物导热率与温度的相关性;与同温度下纯质CO2体系相比,粒径相同时,Ag、Cu、Fe的复合体系导热增长率分别为25.6%－43.8%、19.4%－31.9%、6.9%－17.6%,纳米Ag导热增强效果最好;对于同一粒子,粒径越小,整体的导热能力越强,粒径1.0nm、1.5nm、2.0nm的复合体系导热增长率分别为28.2%－39.8%、19.4%－31.9%和7.5%－17.1%。     

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.     

动态法测定良导体热导率的实验研究

对“用动态法测定良导体热导率”实验的数据处理方法进行了探索，提出两种改进方法并在实际应用中得到了较好的效果，对实验涉及到的准一维热传导方程及其波动解作了理论分析（引入了散热修正）和解释。     

Study of thermal conductivity and thermal rectification in exponential mass graded lattices

Concept of exponential mass variation of oscillators along the chain length of N oscillators is proposed in the present Letter. The temperature profile and thermal conductivity of one-dimensional (1D) exponential mass graded harmonic and anharmonic lattices are studied on the basis of Fermi-Pasta-Ulam (FPU) β model. Present findings conclude that the exponential mass graded chain provide higher conductivity than that of linear mass graded chain. The exponential mass graded anharmonic chain generates the thermal rectification of 70-75% which is better than linear mass graded materials, so far. Thus instead of using linear mass graded material, the use of exponential mass graded material will be a better and genuine choice for controlling the heat flow at nano-scale.     

带电粒子形成胶体晶体的有效硬球模型判据的计算机模拟验证

在对胶体晶体的研究中,带电粒子胶体晶体的形成机理比硬球胶体晶体更加复杂,对其形成条件目前还缺少有效的判断依据. 有效硬球模型判据提出以有效直径作为判断参数. 为了验证该判据的有效性,利用布朗动力学模拟研究了不同有效直径下带电粒子胶体晶体的特性. 为了更加定量地研究单因素对带电胶体晶体形成的影响,取有效直径为2.8至0.8,并对一定的有效直径,研究了粒子几何直径和排斥力不同情况下的结晶行为. 在布朗动力学模拟过程中,采用径向分布函数和键序参数方法检测体系的结构变化,并分析所形成的晶体结构. 结果表明,在判断带电粒子胶体体系能否形成有序结构方面,有效硬球模型判据有一定的合理性. 但是,并不能将有效直径作为唯一的判别参数,而是需要综合其他参数的影响,这显示出该判据的片面性. 关键词： 布朗动力学模拟 带电胶体晶体 有效硬球模型     

CO_2水合物导热特性的分子动力学模拟

使用分子动力学模拟方法在NVT系综下对结构完整CO_2水合物以及结构缺陷CO_2水合物进行了导热模拟计算.对于结构完整的CO_2水合物,在200-230 K温度区间内,体系导热系数由0.4684 W·m~(-1)·K~(-1)变化到0.4836 W·m~(-1)·K~(-1),温度相关性较弱;而在230-280 K温度区间内,体系导热系数由0.4836 W·m~(-1)·K~(-1)变化到0.7494 W·m~(-1)·K~(-1),温度相关性变强;另外,通过计算功率图谱发现主体分子对水合物体系的导热贡献更大.对于结构缺陷CO_2水合物,发现晶穴占有率和笼形结构缺陷对体系导热均有一定影响,空笼晶胞导热系数约为完整晶胞导热系数的86.67%,体系的导热能力主要取决于主体结构的性质.     

A micro-convection model for thermal conductivity of nanofluids

Increase in the specific surface area as well as Brownian motion are supposed to be the most significant reasons for the anomalous enhancement in thermal conductivity of nanofluids. This work presents a semi-empirical approach for the same by emphasizing the above two effects through micro-convection. A new way of modeling thermal conductivity of nanofluids has been explored which is found to agree excellently with a wide range of experimental data obtained by the present authors as well as the data published in literature