Thermal Conductivity Prediction for Ethylene glycol based Nanofluids by Molecular Dynamics Simulation

• Main Authors: Lin, Yung-Sheng, 林詠勝
• Other Authors: Chieng, Ching-Chang
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/53089857777481401221

博士 === 國立清華大學 === 工程與系統科學系 === 99 === Nanofluids engineered by dispersing nanometer-scale, solid particles into base liquids such as water, ethylene glycol (EG), oils, etc.—have demonstrated much higher thermal conductivity than the base liquids themselves. Tremendous enhancement of thermal conductivity of nanofluids has been observed in the experiment, which leads to the applications for energy saving. Present study applies molecular dynamics (MD) to simulate the thermal conductivity of nanofluids and to reveal a molecular-level mechanism of the enhanced experimental thermal conductivity for copper nanoparticles suspended in ethylene glycol. For the aim of reliable model of ethylene glycol, this study constructs a force interaction model for thermal conductivity computation and to analyze the liquid properties in atomic level for liquid ethylene glycol (EG) using MD simulation. The mechanism behind the abnormally enhanced thermal conductivity of nanofluids is a hotly debated topic. Although models have been used to describe physical mechanisms for effective thermal conductivity of nanofluids, such as the Brownian motion of particles, molecular-level layering of liquid at the liquid/particle interface, the nature of heat transport in nanoparticles, and the effects of nanoparticle clustering , no final conclusions have been made because most of the prediction models were described by macroscale or macroscale with modifications on the molecular level. Molecular Dynamic (MD) Simulations are an ultimate tool to clarify and to identify the major mechanisms because they are based on the basic law of Newton and provide significant insights at the atomic level and have been applied in recent studies. Moreover, calculation of thermal conductivity and the characterization of the molecular-level mechanisms of ethylene-glycol-based copper nanofluid are conducted using the MD Simulation when the nanoparticle size ranges from 6 to 14 A. Layer–Maxwell model is developed for the calculation of effective thermal conductivity of the nanofluid with nanoparticle size up to 2000 A by the application of distinct thermal conductivity in the nanolayers around nanoparticle obtained from MD simulations. The iii comparison between computational and experimental results reveals the roles of interfacial layer and nanoparticle size in the thermal conductivity enhancement. Computed thermal conductivities of the nanofluids using Green-Kubo formalism and using Nonequilibrium MD Methods are compared. Contributions for possible heat transfer modes in molecular level are quantized, including modes of convection and interaction using Green-Kubo formalism. The simulations not only confirm that the enhancement of thermal conductivity due to the suspending nanoparticle is increased with volume fraction and the size of the nanoparticle but also identify the significant contributions from atom interaction.