Ansón-Casaos A, Ciria J C, Sanahuja-Parejo O, Víctor-Román S, González-Domínguez J M, García-Bordejé E, Benito A M, Maser W K
Instituto de Carboquímica, ICB-CSIC, Miguel Luesma Castán 4, 50018 Zaragoza, Spain.
Phys Chem Chem Phys. 2020 May 28;22(20):11474-11484. doi: 10.1039/d0cp00468e. Epub 2020 May 11.
Controlling the physicochemical properties of nanoparticles in fluids directly impacts on their liquid phase processing and applications in nanofluidics, thermal engineering, biomedicine and printed electronics. In this work, the temperature dependent viscosity of various aqueous nanofluids containing carbon nanotubes (CNTs) or graphene oxide (GO), i.e. 1D and 2D nanoparticles with extreme aspect ratios, is analyzed by empirical and predictive physical models. The focus is to understand how the nanoparticle shape, concentration, motion degrees and surface chemistry affect the viscosity of diluted dispersions. To this end, experimental results from capillary viscosimeters are first examined in terms of the energy of viscous flow and the maximum packing fraction applying the Maron-Pierce model. Next, a comparison of the experimental data with predictive physical models is carried out in terms of nanoparticle characteristics that affect the viscosity of the fluid, mostly their aspect ratio. The analysis of intrinsic viscosity data leads to a general understanding of motion modes for carbon nanoparticles, including those with extreme aspect ratios, in a flowing liquid. The resulting universal curve might be extended to the prediction of the viscosity for any kind of 1D and 2D nanoparticles in dilute suspensions.
控制流体中纳米颗粒的物理化学性质直接影响其在纳米流体学、热工程、生物医学和印刷电子学中的液相处理及应用。在这项工作中，通过经验和预测物理模型分析了各种含有碳纳米管（CNT）或氧化石墨烯（GO）的水性纳米流体的温度依赖性粘度，即具有极高纵横比的一维和二维纳米颗粒。重点是了解纳米颗粒的形状、浓度、运动程度和表面化学如何影响稀释分散体的粘度。为此，首先根据粘性流动能量和应用马龙 - 皮尔斯模型的最大填充率来检验毛细管粘度计的实验结果。接下来，根据影响流体粘度的纳米颗粒特性，主要是它们的纵横比，将实验数据与预测物理模型进行比较。对特性粘度数据的分析有助于全面了解碳纳米颗粒在流动液体中的运动模式，包括那些具有极高纵横比的颗粒。由此得到的通用曲线可能会扩展到预测稀悬浮液中任何类型的一维和二维纳米颗粒的粘度。
