On the relevance of accounting for the evolution of the fractal dimension in aerosol process simulations

Artelt, C.; Schmid, Hans‐Joachim; Peukert, Wolfgang

doi:10.1016/s0021-8502(03)00005-3

Cited by 73 publications

(47 citation statements)

References 28 publications

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“…As the ratio increased, the fractal dimension started to increase from 1.8 up to 2.6. This trend was similar to previous reports (Artelt et al 2003;Schmid et al 2004). Owing to the melting point of titania and the limitation of the initial particle size on the BD simulation, the fractal dimension of fully sintered agglomerates could not be obtained, unlike in the MC simulation (Schmid et al 2004).…”

Section: Resultssupporting

confidence: 93%

“…The coagulation coefficient (K) of agglomerates is very different from that of spherical particles, depending on their fractal dimension (Mulholland et al 1988;Matsoukas and Friedlander 1991;Rogak and Flagan 1992;Seinfeld and Pandis 1998). The fractal dimension can vary with respect to the ratio of the collision and sintering characteristic times (Artelt et al 2003). The relationship between the fractal dimension of agglomerates and the characteristic times of collision, sintering, and surface growth has been obtained by performing Monte Carlo (MC) simulations (Schmid et al 2004(Schmid et al , 2006Al Zaitone et al 2009).…”

Section: Introductionmentioning

confidence: 99%

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Coagulation Coefficient of Agglomerates with Different Fractal Dimensions

Cho

Chung

Biswas

2011

Aerosol Science and Technology

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A coagulation coefficient of agglomerates with different fractal dimensions has not been considered in the past, even though there is a possibility of variations in the fractal dimension of agglomerates at any instant. In this study, a Brownian dynamics simulation was performed with simultaneous collision and sintering, and variations in the fractal dimension of agglomerates were observed. A coagulation coefficient expression for agglomerates with two different fractal dimensions was proposed. The coagulation coefficient based on the different fractal dimensions was at most 140% higher than that based on the average fractal dimension. To determine an accurate coagulation coefficient of agglomerates, the fractal dimension of each agglomerate has to be considered.

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Section: Resultssupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Coagulation Coefficient of Agglomerates with Different Fractal Dimensions

Cho

Chung

Biswas

2011

Aerosol Science and Technology

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“…The varying fractal dimension method proposed by Artelt et al (2003) is used here as shown in Equation (10), in which D f is updated at each point based on the characteristic fusion time (t f ) and collision time (t c )…”

Section: Cfd Simulationmentioning

confidence: 99%

“…It simplified the influence of fractal structure on the collision kernel, which is both an advantage and a disadvantage of this model. A more recent study (Artelt et al 2003) has shown that it is important to use non-constant fractal dimension for simultaneous coagulation and coalescence. That model incorporated the evolution of the mean value of the fractal dimension based on physical and process parameters, that is, a single fractal dimension was assumed to be valid for all particles at one instance.…”

Section: Introductionmentioning

confidence: 99%

Computational Modeling of Silicon Nanoparticle Synthesis: II. A Two-Dimensional Bivariate Model for Silicon Nanoparticle Synthesis in a Laser-Driven Reactor Including Finite-Rate Coalescence

Dang

Swihart

2009

Aerosol Science and Technology

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In this work, a two-dimensional model was developed for silicon nanoparticle synthesis by silane thermal decomposition in a sixway cross laser-driven aerosol reactor. This two-dimensional model incorporates fluid dynamics, laser heating, gas phase and surface phase chemical reactions, and aerosol dynamics, with particle transport and evolution by convection, diffusion, thermophoresis, nucleation, surface growth, coagulation, and coalescence processes. Because of the complexity of the problem at hand, the simulation was carried out via several sub-models. First, the chemically reacting flow inside the reactor was simulated in three dimensions in full geometric detail, but with no aerosol dynamics and with highly simplified chemistry. Second, the reaction zone was simulated using an axisymmetric two-dimensional CFD model, whose boundary conditions were obtained from the first step. Last, a twodimensional aerosol dynamics model was used to study the silicon nanoparticle formation using more complete silane decomposition chemistry, together with the temperature and velocities extracted from the reaction zone CFD simulation. A bivariate model was used to describe the evolution of particle size and morphology. The aggregates were modeled by a moment method, assuming a lognormal distribution in particle volume. This was augmented by a single balance equation for primary particles that assumed locally equal number of primary particles per aggregate and fractal dimension. The model predicted the position and size at which the primary particle size is frozen in, and showed that increasing the peak temperature was a more effective means of improving particle yield than increasing silane concentration or flowrate.

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“…As a consequence one may expect elevated local precursor concentrations and longer residence times within the temperature region relevant for particle formation. This favours surface growth, but also coagulation and sintering [29]. At p chamber,Ar = 100 mbar, this leads to enhanced primary particle growth and to the formation of compact aggregates, which do not contain more than a few primary particles with diameters of around 70 nm.…”

Section: Counter-and Injection Pressurementioning

confidence: 99%

Particle generation in pulsed plasmas

Artelt

Rott

Höschen

et al. 2008

Plasma Devices and Operations

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A new pulsed coaxial plasma generator (PCPG) has been developed in order to allow for investigating particle generation in the quench of a propagating jet. The related process provides an extremely transient environment which is characterised by initially high energy and charge densities, steep temperature gradients and short particle residence times. The combination of high quench rates and high charge densities, which can not be obtained in conventional reactors such as in flames or quasi stationary plasmas, provide in fact a potential for "freezing" of non-equilibrium phases and for tailoring particle characteristics by means of controlling particle-particle interactions. The pulsed plasma is characterised by means of determining the energy coupling, the charge density, the expansion behaviour, and the evolution of temperature. Particle properties such as primary particle size and aggregate structure are determined for varying process parameters, namely energy coupling, precursor injection, and ambient pressure.

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On the relevance of accounting for the evolution of the fractal dimension in aerosol process simulations

Cited by 73 publications

References 28 publications

Coagulation Coefficient of Agglomerates with Different Fractal Dimensions

Coagulation Coefficient of Agglomerates with Different Fractal Dimensions

Computational Modeling of Silicon Nanoparticle Synthesis: II. A Two-Dimensional Bivariate Model for Silicon Nanoparticle Synthesis in a Laser-Driven Reactor Including Finite-Rate Coalescence

Particle generation in pulsed plasmas

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