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Estimating Al2O3–CO2 nanofluid viscosity: a molecular dynamics approach

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TLDR
In this article, the effects of temperature and nanoparticle size on viscosity using molecular dynamics simulations (MD) were investigated for CO2-Al2O3 interaction. But the authors did not consider the effect of Brownian motion and its contribution to changes in viscosities.
Abstract
High-viscosity CO2 is of interest to the oil and gas industry in enhanced oil recovery and well-fracturing applications. Dispersing nanoparticles in CO2 is one way of achieving increased viscosity. However, parametric studies on viscosity estimation of CO2 nanofluids is not found in the open literature. A comparison of various interatomic potentials for their accuracy in predicting viscosity is also missing. In this work, we studied Al2 O3 nanoparticles in CO2 base fluid. We screened the inter-molecular interaction potential models available for CO2 –CO2 interactions and found that the TraPPE-flexible model (with MORSE potential) to be most suitable for conditions used in this work. We estimated the CO2 –Al2 O3 interaction potential using quantum mechanical simulations. Using this combination for CO2 –CO2 and CO2 –Al2 O3 interactions, we explored the effects of temperature and nanoparticle size on viscosity using molecular dynamics simulations (MD). We predicted that the viscosity would increase with increase in temperature and particle size. We also calculated the base fluid self-diffusion coefficient to investigate the effect of Brownian motion and its contribution to changes in viscosity. We found that it decreases with increase in particle size and temperature, thereby indicating that Brownian motion does not contribute to the increased viscosity. Further, the nanolayer formed at the Al2 O3 –CO2 interface is studied through density distributions around the nanoparticle; the thickness of this nanolayer is found to increase with nanoparticle diameter. Finally, we examined the structures of CO2 fluid in presence of nanoparticles at different thermodynamic states through radial distribution functions. The current work sheds light on the viscosity enhancement by the addition of nanoparticles; it is hoped that such studies will lead to tools that help tailor fluid properties to specific requirements.

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Citations
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Fast parallel algorithms for short-range molecular dynamics

TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
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TL;DR: In this article, a molecular dynamics simulation approach was used to investigate the structure and thickness of the interfacial layer and obtain values for radial distribution function, g(r), viscosity, and thermal conductivity of Cu/water nanofluids with volume fractions and temperatures ranging from 0.5-2 vol% and 293-333 K, respectively.
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Interfacial thermal conductance between TiO2 nanoparticle and water: A molecular dynamics study

TL;DR: In this article, the interfacial thermal conductance (Kapitza conductance) between a TiO2 nanoparticle and water is investigated using transient non-equilibrium molecular dynamics.
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Interfacial thermal conductance between TiO2 nanoparticle and water: A molecular dynamics study

TL;DR: In this article , the interfacial thermal conductance (Kapitza conductance) between a TiO2 nanoparticle and water is investigated using transient non-equilibrium molecular dynamics.
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Determination of heat transport mechanism using nanoparticle property and interfacial nanolayer in a nanofluidic system

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References
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TL;DR: This work reports a gradient-corrected exchange-energy functional, containing only one parameter, that fits the exact Hartree-Fock exchange energies of a wide variety of atomic systems with remarkable accuracy, surpassing the performance of previous functionals containing two parameters or more.
Journal ArticleDOI

Fast parallel algorithms for short-range molecular dynamics

TL;DR: In this article, three parallel algorithms for classical molecular dynamics are presented, which can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors.

Fast parallel algorithms for short-range molecular dynamics

TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
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