Local Structure Evolution in Particle Network Formation Studied by Brownian Dynamics Simulation

Hütter, Markus

doi:10.1006/jcis.2000.7150

Cited by 86 publications

(95 citation statements)

References 37 publications

(41 reference statements)

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“…The electrostatic repulsive barrier is affected by the particles surface composition (e.g., adsorbed surfactants) and by the interaction between the particles surface and the dispersant (where pH and salt concentration may significantly affect the repulsive barrier). Monte Carlo and Brownian dynamics simulations indicated that clusters formed in the DLCA regime have a d f ≈ 1.8, while RLCA forms aggregates having d f ≈ 2.1 [34][35][36]. Experimental evidences of the transition between the two regimes as a function of the stability ratio showed how the d f monotonically increases with the stability ratio [37].…”

Section: Interaction Potentialmentioning

confidence: 95%

Fractal-like structures in colloid science

Lazzari

Nicoud

Jaquet

et al. 2016

Advances in Colloid and Interface Science

170

126

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a b s t r a c tThe present work aims at reviewing our current understanding of fractal structures in the frame of colloid aggregation as well as the possibility they offer to produce novel structured materials. In particular, the existing techniques to measure and compute the fractal dimension d f are critically discussed based on the cases of organic/inorganic particles and proteins. Then the aggregation conditions affecting d f are thoroughly analyzed, pointing out the most recent literature findings and the limitations of our current understanding. Finally, the importance of the fractal dimension in applications is discussed along with possible directions for the production of new structured materials.

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Section: Interaction Potentialmentioning

confidence: 95%

Fractal-like structures in colloid science

Lazzari

Nicoud

Jaquet

et al. 2016

Advances in Colloid and Interface Science

170

126

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“…In order to correctly model the statics and dynamics when approaching stationary states, realistic potentials are needed. The interaction between the particles is described by DLVO theory [10,11,24]. If the colloidal particles are suspended in a solvent, typically water, ions move into solution, whereas their counter ions remain in the particle due to a different resolvability.…”

Section: Molecular Dynamicsmentioning

confidence: 99%

“…A lot of effort has been invested by applying different simulation methods, which have their inherent strengths but also some disadvantages. Simplified Brownian Dynamics (BD), such as in the work of Hütter [11] does not contain long-ranged hydrodynamic interactions among particles at all. The computational cost is low, since hydrodynamics is reduced to a simple Stokes force and thus large particle numbers can be handled.…”

Section: Introductionmentioning

confidence: 99%

Simulation of claylike colloids

et al. 2005

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Abstract. We investigate properties of dense suspensions and sediments of small spherical silt particles by means of a combined Molecular Dynamics (MD) and Stochastic Rotation Dynamics (SRD) simulation. We include van der Waals and effective electrostatic interactions between the colloidal particles, as well as Brownian motion and hydrodynamic interactions which are calculated in the SRD-part. We present the simulation technique and first results. We have measured velocity distributions, diffusion coefficients, sedimentation velocity, spatial correlation functions and we have explored the phase diagram depending on the parameters of the potentials and on the volume fraction.

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“…Much more sparse are the references to the coordination number and its influence [7]. In addition to fractal exponent and coordination number, we introduce here the eccentricity index (which has some precedent in the triangle distribution function [24]). The geometric mean of the two last indices shows an unexpected regularity for different times, densities and morphologies.…”

Section: Introductionmentioning

confidence: 99%

Influence of primary-particle density in the morphology of agglomerates

2014

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Agglomeration processes occur in many different realms of science such as colloid and aerosol formation or formation of bacterial colonies. We study the influence of primary particle density in agglomerate structure using diffusion-controlled Monte Carlo simulations with realistic space scales through different regimes (DLA and DLCA). The equivalence of Monte Carlo time steps to real time scales is given by Hirsch's hydrodynamical theory of Brownian motion. Agglomerate behavior at different time stages of the simulations suggests that three indices (fractal exponent, coordination number and eccentricity index) characterize agglomerate geometry. Using these indices, we have found that the initial density of primary particles greatly influences the final structure of the agglomerate as observed in recent experimental works.

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Local Structure Evolution in Particle Network Formation Studied by Brownian Dynamics Simulation

Cited by 86 publications

References 37 publications

Fractal-like structures in colloid science

Fractal-like structures in colloid science

Simulation of claylike colloids

Influence of primary-particle density in the morphology of agglomerates

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