Cluster Shape Anisotropy in Irreversibly Aggregating Particulate Systems

Fry, D.; Mohammad, Ameera F.; Chakrabarti, and A.; Sorensen, C. M.

doi:10.1021/la0494369

Cited by 34 publications

(26 citation statements)

References 42 publications

(59 reference statements)

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“…Agglomerate shape is described by the inertia tensor (Fry et al 2004). For a three-dimensional (3d) body of N discrete and equal masses the inertia tensor is…”

Section: Relationship Between the Small Angle Structure Factor And Agmentioning

confidence: 99%

“…Anisotropy is used as a measure of cluster "stringiness" and can be defined by the ratio of the squares of principal radii of gyration (Fry et al 2004):…”

Section: Relationship Between the Small Angle Structure Factor And Agmentioning

confidence: 99%

“…Clusters used in this work were obtained from an off-lattice diffusion limited cluster aggregation (DLCA) algorithm (Fry et al 2004) using an efficient link-list method (Allen and Tildesly 1987). DLCA simulations successfully model aggregates formed in aerosols and colloids which yield D f = 1.8 (Family and Landau 1984;Jullien and Botet 1987;Meakin 1999).…”

Section: Simulationmentioning

confidence: 99%

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Light Scattering Shape Diagnostics for Nano-Agglomerates

Mulholland

Zhou

Zachariah

et al. 2013

Aerosol Science and Technology

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Motivated by light scattering experiments showing enhanced intensity of electric field aligned nano-agglomerates versus randomly oriented nano-agglomerates, we address the theoretical basis for this effect by applying the theory of small angle RayleighGans-Debye light scattering to oriented nano-clusters generated by classical diffusion-limited cluster-cluster aggregation (DLCA). We show that the shape anisotropy of these clusters is related to the ratio of small angle light scattering for partially aligned and randomly oriented clusters. It is also shown that state-of-the-art small-angle aerosol scattering measurements would have the angular resolution required to measure the shape anisotropy of clusters with 30 to 1000 nano-monomers. For large q, it is shown from the simulations that S(q) for the partially aligned nano-clusters is not proportional to q − D f , where D f is the fractal dimension, as it is for randomly oriented clusters. Nano-clusters with a fixed orientation are shown to result in a structure factor with multiple peaks, which might be used to obtain more detailed information about particle structure than shape anisotropy. The measurements reported in the literature showing enhanced scattering for partially aligned soot agglomerates were for angle integrated measurements. Calculation of the integrated light scattering cross-section for the same range of angles and polarization direction as the experiments indicate a significant enhancement of 70% and 120% for two representative aspect ratios. The smaller value overlaps with measured values of the scattering enhancement for oriented soot agglomerates in an electric field.

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“…Agglomerate shape is described by the inertia tensor (Fry et al 2004). For a three-dimensional (3d) body of N discrete and equal masses the inertia tensor is…”

Section: Relationship Between the Small Angle Structure Factor And Agmentioning

confidence: 99%

“…Anisotropy is used as a measure of cluster "stringiness" and can be defined by the ratio of the squares of principal radii of gyration (Fry et al 2004):…”

Section: Relationship Between the Small Angle Structure Factor And Agmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

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Light Scattering Shape Diagnostics for Nano-Agglomerates

Mulholland

Zhou

Zachariah

et al. 2013

Aerosol Science and Technology

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“…Image analysis is commonly used to obtain the size distribution of nanoparticles (Fisker et al 2000;Reetz et al 2000) and fractal dimensions in 2D and 3D images (Köylü et al 1995;Hayashi et al 1999). Other parameters, such as the radius of gyration, linearity coefficient, aspect ratio, and particle chain length are also used to characterize the geometry of fractal nanoparticle structures (Fry et al 2004). …”

Section: Combustion Generated Nanoparticlesmentioning

confidence: 99%

“…The density of each particle is assumed constant. From Fry et al (2004), the shape of any object can be characterized by the moment of inertia tensor, T I , with components…”

Section: Image Analysismentioning

confidence: 99%

Image Analysis and Computer Simulation of Nanoparticle Clustering in Combustion Systems

Chen

Bakrania

Wooldridge

et al. 2010

Aerosol Science and Technology

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The current work presents a new method to model and characterize the formation and growth of nanoparticles clusters which includes the three dimensional geometric properties of the clusters, such as aspect ratios, main chain length, radius of gyration, fractal dimension and fractal prefactor. In the model, semi-stochastic mathematics is used to represent varying levels of Coulomb and van der Waals forces during clustering of monodisperse particles. Parametric studies of the relative particle interactions are conducted to evaluate the effects on cluster geometry. Radius of gyration and main chain length were identified as the geometric properties with the greatest sensitivity to changes in the interparticle forces. To demonstrate the analytical capability of the approach, clusters of combustion-generated tin dioxide (SnO 2 ) nanoparticles were imaged and evaluated to identify the dominant forces controlling cluster morphology. The results show the geometry of the SnO 2 clusters is a result of strong Coulomb interactions.

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Tensor virial equation of evolving surfaces in sintering of aggregates of particles by diffusion

Wakai¹,

Brakke²

2013

Acta Materialia

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The moment of inertia tensor is a quantity that characterizes the morphology of aggregates of particles. The deviatoric components indicate the anisotropy of the aggregate, and its compactness is described by the isotropic component, i.e. the second moment of inertia, which is related to the radius of gyration. The equation of motion of the moment of inertia tensor is proposed for the sintering and coalescence of crystalline particles by bulk diffusion and surface diffusion. Simulations of the evolution of aggregates of particles (linear chains, rings and branched chains) show that the aggregates become more compact and more isotropic structures, driven by the surface energy tensor or the surface force density. The tensor virial equation for diffusion is applicable also to evolution of pores, precipitates and inclusions embedded in a surrounding matrix.

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Cluster Shape Anisotropy in Irreversibly Aggregating Particulate Systems

Cited by 34 publications

References 42 publications

Light Scattering Shape Diagnostics for Nano-Agglomerates

Light Scattering Shape Diagnostics for Nano-Agglomerates

Image Analysis and Computer Simulation of Nanoparticle Clustering in Combustion Systems

Tensor virial equation of evolving surfaces in sintering of aggregates of particles by diffusion

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