A 2D fixed-sectional approach to model the coagulation of (highly) charged aerosols

Verdoold, S.; Marijnissen, J.C.M.

doi:10.1016/j.elstat.2009.01.026

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Since charge is a discrete quantity, such an approach lends itself naturally to also treating size-dependent charge distributions. Sectional methods are widely used in aerosol modeling, and have been used by a number of researchers to model bivariate distributions, where the second variable (in addition to particle size) is, for example, particle chemical composition [13][14][15], agglomerate structure [16][17][18][19][20][21], or charge [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Sectional modeling of nanoparticle size and charge distributions in dusty plasmas

Agarwal¹,

Girshick²

2012

Plasma Sources Sci. Technol.

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Sectional models of the dynamics of aerosol populations are well established in the aerosol literature but have received relatively less attention in numerical models of dusty plasmas, where most modeling studies have assumed the existence of monodisperse dust particles. In the case of plasmas in which nanoparticles nucleate and grow, significant polydispersity can exist in particle size distributions, and stochastic charging can cause particles of given size to have a broad distribution of charge states. Sectional models, while computationally expensive, are well suited to treating such distributions. This paper presents an overview of sectional modeling of nanodusty plasmas, and presents examples of simulation results that reveal important qualitative features of the spatiotemporal evolution of such plasmas, many of which could not be revealed by models that consider only monodisperse dust particles and average particle charge. These features include the emergence of bimodal particle populations consisting of very small neutral particles and larger negatively charged particles, the effects of size and charge distributions on coagulation, spreading and structure of the particle cloud, and the dynamics of dusty plasma afterglows.

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Section: Introductionmentioning

confidence: 99%

Sectional modeling of nanoparticle size and charge distributions in dusty plasmas

Agarwal¹,

Girshick²

2012

Plasma Sources Sci. Technol.

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“…The agglomeration dynamics has been widely analyzed by solving the PBE with the known analytical expression of agglomeration kernel. Since the agglomeration kernel of bipolarly charged particles was established theoretically [1,2], the PBE can be numerically solved to investigate the dynamics of the aerosol charge and size distribution of charged particles [3,4,5]. Especially, the authors have obtained theoretically the analytical expression of bipolarly charged particles with the effect of an external electric field [6], which included the results in [1] as a special case, then the corresponding numerical simulation of the PBE was analyzed [7].…”

Section: Introductionmentioning

confidence: 99%

Effect of Breakage on the Bipolarly Charged Particles

Zhang

Zhou

2013

AMR

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The population balance equation (PBE) was solved numerically by using the sectional method to investigate the effect of breakage on the agglomeration between bipolarly charged particles. Calculations showed that breakage results in the increase of small particles and the decrease of large particles bipolarly charged, compared to the case with only agglomeration effect. The breakage effects are important when simulating the agglomeration dynamics.

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Modeling a bipolar-coagulation reactor using coupled population balances

Verdoold

Marijnissen

2011

Journal of Electrostatics

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A 2D fixed-sectional approach to model the coagulation of (highly) charged aerosols

Cited by 5 publications

References 13 publications

Sectional modeling of nanoparticle size and charge distributions in dusty plasmas

Sectional modeling of nanoparticle size and charge distributions in dusty plasmas

Effect of Breakage on the Bipolarly Charged Particles

Modeling a bipolar-coagulation reactor using coupled population balances

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