the thermal conductivity of OH functionalized multiwalled carbon nanotube and its composites with Ag, Au and Pd in water, ethylene glycol and ethylene glycol-water (60,40 vol%) mixtures is studied using a combined experimental and theoretical approach. The experimental study was carried out in the 0.01 to 0.20 solid mass fraction range from 10 °C to 60 °C. The results show a large effect of the considered solvent on the thermal conductivity as well as increasing values with solid mass fraction and temperature. Artificial neural network (ANN) methods were successfully applied for the prediction of thermal conductivity of the considered nanofluids. The nanoscopic structuring of the studied nanofluids was analyzed by using molecular dynamics simulations, with particular attention to the nanotubes' solvation as well as the changes in the base fluids by the presence of the nanomaterials.

结合实验和理论方法研究了OH功能化多壁碳纳米管及其与Ag，Au和Pd在水，乙二醇和乙二醇-水（60,40 vol％）混合物中的复合材料的导热性。在10至60°C的0.01至0.20固体质量分数范围内进行了实验研究。结果表明考虑的溶剂对热导率有很大影响，并且随着固体质量分数和温度的增加而增加。人工神经网络（ANN）方法已成功应用于预测所考虑的纳米流体的热导率。通过使用分子动力学模拟来分析研究的纳米流体的纳米结构，尤其要注意纳米管的