Molecular Dynamics Study of Aggregation in Nanofluid Flow: Effects of Liquid–Nanoparticle Interaction Strength and Particles Volume Fraction

Aminfar, Habib; Razmara, Naiyer; Mohammadpourfard, Mousa

doi:10.1142/s1758825115400104

Cited by 11 publications

(2 citation statements)

References 35 publications

(40 reference statements)

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“…For nanoparticle–polymer hybrid systems, certain solids loading levels cannot be realized in experiments due to the extremely high viscosity of the suspensions . Computer simulation allows for the study of well‐defined nanoparticle size, steric layer thickness, different particle content in total solids, and different total solids loading without the experimental constraints . These computational methods include all‐atom (AA) and coarse‐grained (CG) molecular dynamics (MD) simulations and Monte Carlo (MC) simulations …”

Section: Introductionmentioning

confidence: 99%

Simulation Study of Nanoparticle–Polymer Organic Suspension Stability

Gervasio

2019

Advcd Theory and Sims

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This study uses a Monte Carlo simulation method to evaluate the agglomeration behaviors of different ZnO nanoparticle and polymethacrylate hybrid suspensions in an organic solvent. Interaction energies are primarily from the steric layer on the particle surfaces. The effects of nanoparticle size, steric layer thickness, particle content, and total solids loading are evaluated based on the average agglomerate size and agglomeration rate. Smaller particle, thicker steric layer, lower particle content, and higher solids loading are desirable factors to stabilize a suspension. Agglomerate size and agglomeration rate increase continuously with increasing particle content in the hybrids from 1 to 50 vol%. A drastic transition from an unstable suspension to a stable suspension occurs when the total solids loading of the suspension increases to greater than 10 vol%. This work provides important guidance for co-dispersing nanoparticles and dissolved polymer chains in organic solvents.

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Section: Introductionmentioning

confidence: 99%

Simulation Study of Nanoparticle–Polymer Organic Suspension Stability

Gervasio

2019

Advcd Theory and Sims

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“…It is a mesoscopic numerical technique based on statistical physics, which simulates the fluid movement at the microscopic particle level. The method has been used in many different fields as a novel numerical method for computational fluid dynamics [Chen and Doolen, 1998;Moeendarbary et al, 2009;Bég et al, 2013;Aminfar et al, 2015]. At the end of the 20th century, because of the unique features in the LBM, such as parallel computation, algorithmic simplicity, some researchers proposed extended theories of the LBM for non-linear partial differential equations and applied to river engineering.…”

Section: Introductionmentioning

confidence: 99%

A Double-Distribution-Function Lattice Boltzmann Method for Bed-Load Sediment Transport

Cai

Luo

2017

Int. J. Appl. Mechanics

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The governing equations of bed-load sediment transport are the shallow water equations and the Exner equation. To embody the advantages of the lattice Boltzmann method (e.g. simplicity, efficiency), the three-velocity (D1Q3) and five-velocity (D1Q5) doubledistribution-function lattice Boltzmann models (DDF-LBMs), which can present the numerical solution for one-dimensional bed-load sediment transport, are proposed here based on the quasi-steady approach. The so-called DDF-LBM means we use two distribution functions to describe the movement of the two components, respectively. By using the Chapman-Enskog expansion, the governing equations can be recovered correctly from the DDF-LBMs. To illustrate the efficiency of these, two benchmark tests are used, and excellent agreements between the numerical and analytical solutions are demonstrated. In addition, we show that the D1Q5 DDF-LBM has better accuracy compared to the Hudson's method.

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