Abstract
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.
Highlights
Carbon nanotubes (CNTs) and graphene have found a number of applications in electronics, sensors, energy devices, catalysis and biomedicine.[1,2,3,4,5,6,7] Very often, these nanostructures need to be dispersed in liquid media
It is demonstrated that the experimental viscosity of dilute CNT and graphene oxide (GO) dispersions can be fitted to the empirical Maron–Pierce model, as a function of the particle concentration and temperature
Experimental data for GOs and CNTs agree with theoretical predictions by first principles, which evaluate fm and the intrinsic viscosity (w) as a function of the aspect ratio
Summary
Carbon nanotubes (CNTs) and graphene have found a number of applications in electronics, sensors, energy devices, catalysis and biomedicine.[1,2,3,4,5,6,7] Very often, these nanostructures need to be dispersed in liquid media. The complete set of measurements was first analyzed as a function of the temperature and the nanoparticle concentration, according to the empirical equation of Maron and Pierce.[45] size distributions for each sample were determined, and the viscosity was evaluated in terms of the aspect ratio (rp) using predictive physical models. The r values of all the measured CNT and GO dispersions are nearly that of pure water (Table S4, ESI†).
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