Effect of Sonication Time and Particle Volume Fraction on Thermal Conductivity of Alumina Nanofluids

2014 ◽  
Author(s):  
Nigil S. Jeyashekar
Author(s):  
Jing Fan ◽  
Liqiu Wang

The recent first-principle model shows a dual-phase-lagging heat conduction in nanofluids at the macroscale. The macroscopic heat-conduction behavior and the thermal conductivity of nanofluids are determined by their molecular physics and microscale physics. We examine numerically effects of particle-fluid thermal conductivity ratio, particle volume fraction, shape, aggregation, and size distribution on macroscale thermal properties for nine types of nanofluids, without considering the interfacial thermal resistance and dynamic processes on particle-fluid interfaces and particle-particle contacting surfaces. The particle radius of gyration and non-dimensional particle-fluid interfacial area in the unit cell are two very important parameters in characterizing the effect of particles’ geometrical structures on thermal conductivity of nanofluids. Nanofluids containing cross-particle networks have conductivity which practically reaches the Hashin-Shtrikman bounds. Moreover, particle aggregation influences the effective thermal conductivity only when the distance between particles is less than the particle dimension. Uniformly-sized particles are desirable for the conductivity enhancement, although to a limited extent.


Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang

Particle laden polymers are one of the most prominent thermal interface materials (TIM) used in electronics cooling. Most of the research groups have primarily dealt with the understanding of the thermal conductivity of these types of TIMs. Thermal resistance is not only dependent on the thermal conductivity but also on the bond line thickness (BLT) of these TIMs. It is not clear that which material property(s) of these particle laden TIMs affects the BLT. This paper discusses the experimental measurement of rheological parameters such as non-Newtonian strain rate dependent viscosity and yield stress for 3 different particle volume fraction and 3 different base polymer viscosity materials. These rheological and BLT measurements vs. pressure will be used to model the BLT of particle-laden systems for factors such as volume fraction.


2021 ◽  
Author(s):  
Ruifeng CAO ◽  
Taotao WANG ◽  
Yuxuan ZHANG ◽  
Hui WANG

Improved heat transfer in composites consisting of guar gel matrix and randomly distributed glass microspheres is extensively studied to predict the effective thermal conductivity of composites using the finite element method. In the study, the proper and probabilistic three-dimensional random distribution of microspheres in the continuous matrix is automatically generated by a simple and efficient random sequential adsorption algorithm which is developed by considering the correlation of three factors including particle size, number of particles, and particle volume fraction controlling the geometric configuration of random packing. Then the dependences of the effective thermal conductivity of composite materials on some important factors are investigated numerically, including the particle volume fraction, the particle spatial distribution, the number of particles, the nonuniformity of particle size, the particle dispersion morphology and the thermal conductivity contrast between particle and matrix. The related numerical results are compared with theoretical predictions and available experimental results to assess the validity of the numerical model. These results can provide good guidance for the design of advanced microsphere reinforced composite materials.


Author(s):  
Toru Yamada ◽  
Yutaka Asako ◽  
Mohammad Faghri ◽  
Chungpyo Hong

The effective thermal conductivity of Al2O3/water and CuO/water nanofluids were modeled by numerically solving steady heat flow in one-dimensional channels. This was accomplished by using energy conserving dissipative particle dynamics (DPDe). The effects of the interfacial thermal resistance and the Brownian motion of nanoparticles were incorporated in the model by modifying the conductive interaction parameter in the energy equation. The results were presented in the form of the thermal conductivity of nanofluids as functions of particle volume fraction and temperature, and were compared with the available experimental and analytical results. The present model agreed well with the experimental results for Al2O3/water nanofluid while there were discrepancies between the model and the results for CuO/water nanofluid.


Author(s):  
Ravi S. Prasher ◽  
Jim Shipley ◽  
Suzana Prstic ◽  
Paul Koning ◽  
Jin-Lin Wang

Currently there are no models to predict the thickness or the bondline thickness (BLT) of particle laden polymeric thermal interface materials (TIM) for parameters such as particle volume fraction and pressure. TIMs are used to reduce the thermal resistance. Typically this is achieved by increasing the thermal conductivity of these TIMs by increasing the particle volume fraction, however increasing the particle volume fraction also increases the BLT. Therefore, increasing the particle volume fraction may lead to an increase in the thermal resistance after certain volume fraction. This paper introduces a model for the prediction of the BLT of these particle laden TIMs. Currently thermal conductivity is the only metric for differentiating one TIM formulation from another. The model developed in this paper introduces another metric: the yield stress of these TIMs. Thermal conductivity and the yield stress together constitute the complete set of material parameters needed to define the thermal performance of particle laden TIMs.


2015 ◽  
Vol 766-767 ◽  
pp. 348-354 ◽  
Author(s):  
M. Arulprakasajothi ◽  
K. Elangovan ◽  
K. Hemachandra Reddy ◽  
S. Suresh

This paper presents the preparation, characterisation and thermal behavior of TiO2/water Nanofluids with different concentration. The presence of Nanosized particles in the conventional heat transfer fluids enhances its thermo physical character. In the present work, TiO2/water Nanofluids with various volume concentrations were prepared by dispersing a specified amount of spherical sized TiO2 Nanoparticles in distilled water without any surfactant. To get a uniform dispersion and stable suspension, the Nanofluids were kept under ultrasonic vibration continuously for 3 hours. Zeta potential measurement brought detailed insight into the causes of dispersion, aggregation of Nanofluids. The KD2 Pro, fully portable thermal properties analyser, was used to measure thermal conductivity of nanofluids. The viscosity of the nanofluid was measured using a Brookfield Viscometer. The experimental results show that the thermal conductivity increases with an increase of particle volume fraction and the enhancement was observed to be 9.22% over the base fluid for volume concentration of 0.75%. From the experimental observations, enhancement in thermal conductivity is larger than the enhancement in viscosity.


2003 ◽  
Vol 125 (3) ◽  
pp. 386-391 ◽  
Author(s):  
Ravi S. Prasher ◽  
Paul Koning ◽  
James Shipley ◽  
Amit Devpura

This paper reports the measurement of the thermal conductivity of particle-laden polymeric thermal interface materials for three different particle volume fractions. The experimental data are further compared with the percolation model and effective medium theory. We then introduce a method of obtaining the contact resistance between the particles and the polymeric matrix by a combination of percolation modeling and experimental data. We also discuss the dependence of the mechanical response of these particle-laden polymers for different filler or particle loading. A novel mechanical length scale is defined to understand the mechanical response of these materials, and is correlated to the viscosity of these materials.


Author(s):  
Reza H. Khiabani ◽  
Yogendra Joshi ◽  
Cyrus Aidun

Particle laden Thermal Interface Materials (TIMs) are used extensively in thermal packaging of electronic components to enhance the heat transfer between heat dissipating components and the thermal management layers. In this paper, the thermal performance of particle laden TIMs is studied numerically, using the Lattice Boltzmann method. The effect of particle volume fraction, particle size and the thermal conductivity ratio on the thermal performance of particle laden TIMs are examined. The results for the effective thermal conductivity of particle laden greases are in agreement with the existing analytical and experimental results reported in the literature.


Author(s):  
X. Zhang ◽  
S. Kanuparthi ◽  
G. Subbarayan ◽  
B. Sammakia ◽  
S. Tonapi

Particle laden polymer composites are widely used as thermal interface materials in the electronics cooling industry. The projected small chip-sizes and high power applications in the near future demand higher values of effective thermal conductivity of the thermal interface materials (TIMs) used between the chip and the heat-spreader and the heat-spreader and heat-sink. However, over two decades of research has not yielded materials with significantly improved effective thermal conductivities. A critical need in developing these TIMs is apriori modeling using fundamental physical principles to predict the effect of particle volume fraction and arrangements on effective behavior. Such a model will enable one to optimize the structure and arrangement of the material. The existing analytical descriptions of thermal transport in particulate systems under predict (as compared to the experimentally observed values) the effective thermal conductivity since these models do not accurately account for the effect of inter-particle interactions, especially when particle volume fractions approach the percolation limits of approximately 60%. Most existing theories are observed to be accurate when filler material volume fractions are less than 30–35%. In this paper, we present a hierarchical, meshless, computational procedure for creating complex microstructures, explicitly analyzing their effective thermal behavior, and mathematically optimizing particle sizes and arrangements. A newly developed object-oriented symbolic, java language framework termed jNURBS implementing the developed procedure is used to generate and analyze representative random microstructures of the TIMs.


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