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宏观参数对基于AlO和TiO的水基纳米流体界面纳米层厚度的影响。

Effects of Macroparameters on the Thickness of an Interfacial Nanolayer of AlO- and TiO-Water-Based Nanofluids.

作者信息

Fan Wenhui, Zhong Fengquan

机构信息

State Key Laboratory of High Temperature Gas Dynamics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China.

School of Engineering Science, University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

ACS Omega. 2020 Oct 24;5(43):27972-27977. doi: 10.1021/acsomega.0c03452. eCollection 2020 Nov 3.

DOI:10.1021/acsomega.0c03452
PMID:33163780
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7643158/
Abstract

In this paper, thicknesses of interfacial nanolayers of alumina-deionized water (DW) and titanium dioxide-deionized water (DW) nanofluids are studied. Thermal conductivities of both nanofluids were measured in a temperature range of 298 to 353 K at particle volume ratios of 0.2 to 1.5% by experiments. A theoretical model considered both the effects of the interfacial nanolayer and Brownian motion is developed for thermal conductivity. A relational expression between nanolayer thickness and bulk temperature and volume fraction of particles of nanofluids is derived from the theoretical model. With the experimental data of thermal conductivity, changes of nanolayer thickness with nanofluids macroscopic properties (bulk temperature and particle volume ratio) are obtained. The present results show that nanolayer thickness increases with fluid temperature almost linearly and decreases with particle volume fraction in a power law. Based on the present results, simple formulas of interfacial nanolayer thickness as a function of fluid temperature and particle volume fraction are proposed for both water-based nanofluids.

摘要

本文研究了氧化铝-去离子水(DW)和二氧化钛-去离子水(DW)纳米流体界面纳米层的厚度。通过实验在298至353 K的温度范围内、颗粒体积比为0.2%至1.5%的条件下测量了两种纳米流体的热导率。建立了一个考虑界面纳米层和布朗运动影响的热导率理论模型。从该理论模型推导出纳米层厚度与纳米流体的本体温度和颗粒体积分数之间的关系式。利用热导率的实验数据,得到了纳米层厚度随纳米流体宏观性质(本体温度和颗粒体积比)的变化情况。目前的结果表明,纳米层厚度随流体温度几乎呈线性增加,随颗粒体积分数呈幂律减小。基于目前的结果,针对两种水基纳米流体,提出了作为流体温度和颗粒体积分数函数的界面纳米层厚度的简单公式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/6a657bb939ac/ao0c03452_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/59fee7d244f9/ao0c03452_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/e854563050e3/ao0c03452_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/6a657bb939ac/ao0c03452_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/59fee7d244f9/ao0c03452_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/e854563050e3/ao0c03452_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2efc/7643158/6a657bb939ac/ao0c03452_0004.jpg

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本文引用的文献

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Prediction of Thermo-Physical Properties of TiO-AlO/Water Nanoparticles by Using Artificial Neural Network.利用人工神经网络预测TiO-AlO/水纳米颗粒的热物理性质
Nanomaterials (Basel). 2020 Apr 7;10(4):697. doi: 10.3390/nano10040697.
2
Effect of aggregation kinetics on the thermal conductivity of nanoscale colloidal solutions (nanofluid).聚集动力学对纳米级胶体溶液(纳米流体)热导率的影响。
Nano Lett. 2006 Jul;6(7):1529-34. doi: 10.1021/nl060992s.
3
Thermal conductivity of nanoscale colloidal solutions (nanofluids).纳米级胶体溶液(纳米流体)的热导率。
Phys Rev Lett. 2005 Jan 21;94(2):025901. doi: 10.1103/PhysRevLett.94.025901. Epub 2005 Jan 18.