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).     

Nonequilibrium molecular dynamics simulation of coupling between nanoparticles and base-fluid in a nanofluid

The intent of this study is to examine nonequilibrium heat transfer in a copper-argon nanofluid by molecular dynamics simulation. Two different methods, the physical definition method and the curve fitting method, are introduced to calculate the coupling factor between nanoparticles and base fluid. The results show that the coupling factors obtained by these two methods are consistent. The coupling factor is proportional to the volume fraction of the nanoparticle and inversely proportional to nanoparticle diameter. In the temperature range of 90-200 K, the coupling factor is not affected by temperature. The nanoparticle aggregation results in a decrease of the coupling factor.     

Biosynthesized CuO nano-platelets: Physical properties & enhanced thermal conductivity nanofluidics

This contribution reports for the first time, room temperature biosynthesis of p-type CuO nanoparticles carried out using Callistemon viminalis’ flower extracts as a chelating agent in a process that is entirely green. Room temperature X-ray diffraction, attenuated IR total reflection spectroscopy, X-ray photoelectron and Raman spectroscopy investigations confirmed the formation of single phase Tenorite bcc monoclinic CuO nanocrystals post annealing in air, at 500 °C. Photoluminescence spectroscopy with UV emissions at 356 nm (3.47 eV) and broad visible emissions at 418 nm, 561 nm, and 664 nm, support the formation in air, at 200 °C, of CuO nanoparticles with high surface-to-volume ratios and defects. As a direct application, the biosynthesized CuO nanoplatelet-containing powder dispersed in de-ionized water showed an enhancement of the thermal conductivity from 6% to 34% and a significant stability of the PVP stabilized CuO-water nanofluid.     

矩形微槽道纳米流体饱和沸腾临界热流密度特性

针对纳米流体在微小尺度传热领域的应用,在常压下对微槽道中纳米流体的流动沸腾临界热流密度进行实验研究。分别以体积浓度为0.2%、0.5%的水基Al2O3纳米流体为工质进行试验,研究不同质量流速、槽道尺寸以及体积浓度等因素对沸腾CHF的影响。对比水为工质实验结果,表明:槽道尺寸、质量流速对于水-Al2O3纳米流体和纯水的CHF影响一致。其它参数一定的工况下,纳米流体CHF比纯水大,且随着纳米流体体积浓度增大,出口壁面过热度会增大。最后介绍一个微槽道沸腾CHF的预测模型,在评价其不足的基础上提出一个关于CHF的预测公式,与实验数据进行对比,验证该公式的适用性。     

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.     

Thermal conductance of nanofluids: is the controversy over?

Over the last decade nanofluids (colloidal suspensions of solid nanoparticles) sparked excitement as well as controversy. In particular, a number of researches reported dramatic increases of thermal conductivity with small nanoparticle loading, while others showed moderate increases consistent with the effective medium theories on well-dispersed conductive spheres. Accordingly, the mechanism of thermal conductivity enhancement is a hotly debated topic. We present a critical analysis of the experimental data in terms of the potential mechanisms and show that, by accounting for linear particle aggregation, the well established effective medium theories for composite materials are capable of explaining the vast majority of the reported data without resorting to novel mechanisms such as Brownian motion induced nanoconvection, liquid layering at the interface, or near-field radiation. However, particle aggregation required to significantly enhance thermal conductivity, also increases fluid viscosity rendering the benefit of nanofluids to flow based cooling applications questionable.     

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.     

Numerical simulations on the formation of laser speckles with nanofluids

Our recent work revealed that speckles can be formed when nanofluids containing a proper volume fraction of nanoparticles are illuminated by a monochromatic laser beam [Qian M, Liu J, Yan M-S, Shen Z-H, Lu J, Ni XW, et al. Investigation on utilizing laser speckle velocimetry to measure the velocities of nanoparticles in nanofluids. Opt Express 2006; 14: 7559–66]. In this paper, two different physical models are established to figure out the speckle-formation mechanism. The photon–nanoparticle-collision model emphasizes the random collisions between photons and nanoparticles, and Monte Carlo method is used to simulate how the incident photons move in the vessel containing nanofluids. However, in the electric-dipole model, each illuminated nanoparticle becomes an electric dipole and sends out scattering lights, and the coherent addition of the scattering lights from nanoparticles is numerically calculated. Finally, from the numerical results, the speckle-formation mechanism is figured out.     

Simultaneous spreading and evaporation: Recent developments

The recent progress in theoretical and experimental studies of simultaneous spreading and evaporation of liquid droplets on solid substrates is discussed for pure liquids including nanodroplets, nanosuspensions of inorganic particles (nanofluids) and surfactant solutions. Evaporation of both complete wetting and partial wetting liquids into a nonsaturated vapour atmosphere are considered. However, the main attention is paid to the case of partial wetting when the hysteresis of static contact angle takes place. In the case of complete wetting the spreading/evaporation process proceeds in two stages. A theory was suggested for this case and a good agreement with available experimental data was achieved. In the case of partial wetting the spreading/evaporation of a sessile droplet of pure liquid goes through four subsequent stages: (i) the initial stage, spreading, is relatively short (1–2 min) and therefore evaporation can be neglected during this stage; during the initial stage the contact angle reaches the value of advancing contact angle and the radius of the droplet base reaches its maximum value, (ii) the first stage of evaporation is characterised by the constant value of the radius of the droplet base; the value of the contact angle during the first stage decreases from static advancing to static receding contact angle; (iii) during the second stage of evaporation the contact angle remains constant and equal to its receding value, while the radius of the droplet base decreases; and (iv) at the third stage of evaporation both the contact angle and the radius of the droplet base decrease until the drop completely disappears. It has been shown theoretically and confirmed experimentally that during the first and second stages of evaporation the volume of droplet to power 2/3 decreases linearly with time. The universal dependence of the contact angle during the first stage and of the radius of the droplet base during the second stage on the reduced time has been derived theoretically and confirmed experimentally. The theory developed for pure liquids is applicable also to nanofluids, where a good agreement with the available experimental data has been found. However, in the case of evaporation of surfactant solutions the process deviates from the theoretical predictions for pure liquids at concentration below critical wetting concentration and is in agreement with the theoretical predictions at concentrations above it.     

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.