Simulating (electro)hydrodynamic effects in colloidal dispersions: smoothed profile method

Previously, we have proposed a direct simulation scheme for colloidal dispersions in a Newtonian solvent [Phys.Rev.E 71,036707 (2005)]. An improved formulation called the ``Smoothed Profile (SP) method'' is presented here in which simultaneous time-marching is used for the host fluid and colloids. The SP method is a direct numerical simulation of particulate flows and provides a coupling scheme between the continuum fluid dynamics and rigid-body dynamics through utilization of a smoothed profile for the colloidal particles. Moreover, the improved formulation includes an extension to incorporate multi-component fluids, allowing systems such as charged colloids in electrolyte solutions to be studied. The dynamics of the colloidal dispersions are solved with the same computational cost as required for solving non-particulate flows. Numerical results which assess the hydrodynamic interactions of colloidal dispersions are presented to validate the SP method. The SP method is not restricted to particular constitutive models of the host fluids and can hence be applied to colloidal dispersions in complex fluids

Efficient simulations of charged colloidal dispersions: A density functional approach

A numerical method is presented for first-principle simulations of charged colloidal dispersions in electrolyte solutions. Utilizing a smoothed profile for colloid-solvent boundaries, efficient mesoscopic simulations are enabled for modeling dispersions of many colloidal particles exhibiting many-body electrostatic interactions. The validity of the method was examined for simple colloid geometries, and the efficiency was demonstrated by calculating stable structures of two-dimensional dispersions, which resulted in the formation of colloidal crystals.Comment: 6 pages, 4 figure

A direct numerical simulation method for complex modulus of particle dispersions

We report an extension of the smoothed profile method (SPM)[Y. Nakayama, K. Kim, and R. Yamamoto, Eur. Phys. J. E {\bf 26}, 361(2008)], a direct numerical simulation method for calculating the complex modulus of the dispersion of particles, in which we introduce a temporally oscillatory external force into the system. The validity of the method was examined by evaluating the storage $G'(\omega)$ and loss $G"(\omega)$ moduli of a system composed of identical spherical particles dispersed in an incompressible Newtonian host fluid at volume fractions of $\Phi=0$, 0.41, and 0.51. The moduli were evaluated at several frequencies of shear flow; the shear flow used here has a zigzag profile, as is consistent with the usual periodic boundary conditions

Direct Numerical Simulations of Electrophoresis of Charged Colloids

We propose a numerical method to simulate electrohydrodynamic phenomena in charged colloidal dispersions. This method enables us to compute the time evolutions of colloidal particles, ions, and host fluids simultaneously by solving Newton, advection-diffusion, and Navier--Stokes equations so that the electrohydrodynamic couplings can be fully taken into account. The electrophoretic mobilities of charged spherical particles are calculated in several situations. The comparisons with approximation theories show quantitative agreements for dilute dispersions without any empirical parameters, however, our simulation predicts notable deviations in the case of dense dispersions.Comment: 4pages, 3figures, to appear in Phys. Rev. Let

A Numerical Model for Brownian Particles Fluctuating in Incompressible Fluids

We present a numerical method that consistently implements thermal fluctuations and hydrodynamic interactions to the motion of Brownian particles dispersed in incompressible host fluids. In this method, the thermal fluctuations are introduced as random forces acting on the Brownian particles. The hydrodynamic interactions are introduced by directly resolving the fluid motions with the particle motion as a boundary condition to be satisfied. The validity of the method has been examined carefully by comparing the present numerical results with the fluctuation-dissipation theorem whose analytical form is known for dispersions of a single spherical particle. Simulations are then performed for more complicated systems, such as a dispersion composed of many spherical particles and a single polymeric chain in a solvent.Comment: 6 pages, 8 figure

Simulation of colloidal suspension systems

The research work is focused on the development of a simulation platform for colloidal suspension. Based on discrete element method (DEM), the model developed takes into account the crucial interactions, i.e. the electrostatic repulsion, van der Waals attraction, Brownian force, hydration effects and hydrodynamic force. The mechanism of colloid particle diffusion in confined space and the combined influences of fluid flow field, geometrical confinement, and the interparticle interactions on the self-assembly process are investigated

Multiscale modelling of nanoparticle distribution in a realistic tumour geometry following local injection

Radiosensitizers have proven to be an effective method of improving radiotherapy outcomes, with the distribution of particles being a crucial element to delivering optimal treatment outcomes due to the short range of effect of these particles. Here we present a computational model for the transport of nanoparticles within the tumour, whereby the fluid velocity and particle deposition are obtained and used as input into the convection-diffusion equation to calculate the spatio-temporal concentration of the nanoparticles. The effect of particle surface charge and injection locations on the distribution of nanoparticle concentration within the interstitial fluid and deposited onto cell surfaces is assessed. The computational results demonstrate that negatively charged particles can achieve a more uniform distribution throughout the tumour as compared to uncharged or positively charged particles, with particle volume within the fluid being 100% of tumour volume and deposited particle volume 44.5%. In addition, varying the injection location from the end to the middle of the tumour caused a reduction in particle volume of almost 20% for negatively charged particles. In conclusion, radiosensitizing particles should be negatively charged to maximise their spread and penetration within the tumour. Choosing an appropriate injection location can further improve the distribution of these particles

Large Scale Dynamic Molecular Modelling of Metal Oxide Nanoparticles in Engineering and Biological Fluids

Nanoparticles (NP) offer great merits over controlling thermal, chemical and physical properties when compared to their micro-sized counterparts. The effectiveness of the dispersion of the NP is the key aspect of the applications in nanotechnology. The project studies the characterization and modification of functional NPs aided by the means of large scale molecular thermal dynamic computerized dispersing simulations, in the level of Nanoclusters (NC). Carrying out NP functionality characterisation in fluids can be enhanced, and analysed through computational simulation based on their interactions with fluidic media; in terms of thermo-mechanical, dynamic, physical, chemical and rheological properties. From the engineering perspective, effective characterizations of the nanofluids have also been carried out based on the particles sizes and particle-fluids Brownian motion (BM) theory. The study covered firstly, investigation of the pure CuO NP diffusion in water and hydrocarbon fluids, secondly, examination of the modified CuO NP diffusion in water. In both cases the studies were put under experiments and simulations for data collection and comparison. For simulation the COMPASS forcefield, smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD) were implemented through the system. Excellent prediction of BM, Van der Waals interaction, electrostatic interaction and a number of force-fields in the system were exploited. The experimental results trend demonstrated high coherence with the simulation results. At first the diffusion coefficient was found to be 1.7e-8m2/s in the study of CuO NC in water based fluidic system. Secondly highly concurrent simulation results (i.e. data for viscosity and thermal conductivity) have been computed to experimental coherence. The viscosity trend of MD simulation and experimental results show a high level of convergence for temperatures between 303-323K. The simulated thermal conductivity of the water-CuO nanofluid was between 0.6—0.75W•m−1•K−1, showing a slight increase following a rise in temperature from 303 to 323 K. Moreover, the alkane-CuO nanofluid experimental and simulated work was also carried out, for analysing the thermo-physical quantities. The alkane-CuO nanofluid viscosity was found 0.9—2.7mpas and thermal conductivity is between 0.1—0.4W•m−1•K−1. Finally, the successful modification of the NPs on experimental and simulation platform has been analysed using different characterization variables. Experimental modification data has been quantified by using Fourier Transformation Infrared (FTIR) peak response, from particular ranges of interest i.e. 1667-1609cm-1 and 1668-1557cm-1. These FTIR peaks deduced Carboxylate attachment on the surface of NPs. Later, MD simulation was approached to mimic experimental setup of modification chemistry and similar agglomerations were observed as during experimental conditions. However, this approach has not been presented before; therefore this study has a significant impact on describing the agglomeration of modified NPs on simulation and experimental basis. Henceforth, the methodology established for metal oxide nanoparticle dispersion simulation is a novelty of this work