Effect of carbon nanotubes on the thermal conductivity enhancement of synthesized hydroxyapatite filled with water for dental applications: experimental characterization and numerical study

被引:21
作者
Malekahmadi, Omid [1 ]
Kalantar, Mahdi [1 ]
Nouri-Khezrabad, Mohsen [1 ]
机构
[1] Yazd Univ, Dept Min & Met Engn, Yazd, Iran
基金
英国科研创新办公室;
关键词
Heat transfer; Multi-walled carbon nanotube; Hydroxyapatite; Water; Artificial neural network;
D O I
10.1007/s10973-021-10593-w
中图分类号
O414.1 [热力学];
学科分类号
摘要
The hydroxyapatite is one of the biocompatible and insulating bioceramics, while the carbon nanotube has a high thermal conductivity potential. This study aims to find an optimal combination and temperature of synthesized hydroxyapatite-carbon nanotube-water hybrid nanofluid achieving both the biocompatibility and the thermal conductivity for dental implant coating. In this study, first, the hydroxyapatite was synthesized, and then, the prepared carbon nanotube was added to the mono-nanofluid of hydroxyapatite (0.2, 0.4, 0.6, 0.8, and 1.0 vol%), obtaining a hybrid nanofluid with the volume ratio of 1:1 for hydroxyapatite/CNT. X-ray powder diffraction, Fourier-transform infrared spectroscopy, Raman spectroscopy, field emission scanning electron microscope, and energy-dispersive X-ray spectroscopy-map tests were used to characterize raw materials and composite products. Zeta potential test and thermal conductivity measurement were used to characterize the hydroxyapatite water (mono-nanofluid) and the composite-water (hybrid nanofluid) in the temperature ranges from 20 to 50 degrees C. The obtained results show that the highest enhancement of thermal conductivity is 25.83% for the composite sample containing 1.0 vol% of carbon nanotube and temperature of 50 degrees C compared with mono nanofluids. Also, a numerical study was done to find the best fit correlations for both the mono and the hybrid nanofluids. An artificial neural network was trained to predict the other volume fractions and temperatures.
引用
收藏
页码:2109 / 2126
页数:18
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