The fractal scaling of fluidized nanoparticle agglomerates

Martín, Lilian de; Fabre, Andrea; Ommen, J. Ruud van

doi:10.1016/j.ces.2014.03.024

Cited by 60 publications

(58 citation statements)

References 42 publications

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“…It is defined by (de Martín et al, 2014b). As shown in Figure 2, as increases, increases with increasing slope, while the drag force increases nearly linearly.…”

Section: Drag Force Scale Factormentioning

confidence: 95%

“…For simulating nanoparticle fluidization, as the particle element we use fragments of the large, complex agglomerates present in the bed: the so-called simple agglomerates. Our idea came from the viewpoint of agglomerates presented by de Martín et al (2014a), which is based on a series of previous studies (de Martín et al, 2014b;Gundogdu et al, 2007;Hakim et al, 2005;Valverde and Castellanos, 2008;Wang et al, 2006;Wang et al, 2002). Nanoparticles agglomerates have a multi-stage structure: aggregates of nanoparticles sintered during production (~200 nm), the simple agglomerates, and complex agglomerate.…”

Section: Introductionmentioning

confidence: 99%

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An adhesive CFD‐DEM model for simulating nanoparticle agglomerate fluidization

et al. 2016

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Nanoparticle fluidization is an efficient technique to disperse and process nanoparticles. Previous studies show that nanoparticles are not fluidized individually, but as agglomerates with hierarchical fractal structures. In this study, an adhesive CFD-DEM (Computational Fluid Dynamics -Discrete Element Modelling) model is developed, in which we use the simple agglomerate as the discrete element, which are the building blocks of the larger complex agglomerates found in a fluidized bed. We show that both the particle contact model and drag force interaction in the conventional CFD-DEM model need modification for properly simulating fluidization of nanoparticle agglomerates. The contact model includes collision mechanisms of elastic-plastic, cohesive and viscoelastic forces, and the drag force is approximately corrected by a scale factor resulting from particle agglomeration. The model is tested for different cases, including the normal impact, response of angle, and fluidization. The simulation results are promising. With increasing particle cohesive force, the fluidized bed goes from a uniform fluid-like regime, to an agglomerate bubbling regime, and finally to defluidization. The current study provides a tool for gaining insights into the characteristics of nanoparticle fluidization.

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“…It is defined by (de Martín et al, 2014b). As shown in Figure 2, as increases, increases with increasing slope, while the drag force increases nearly linearly.…”

Section: Drag Force Scale Factormentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

An adhesive CFD‐DEM model for simulating nanoparticle agglomerate fluidization

et al. 2016

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“…The agglomerates are formed by sub-agglomerates. The cohesive forces between these sub-agglomerates play an important role in producing the agglomerate [8]. Also, the number of these sub-agglomerates (N) and the porosity of agglomerate should be taken into account.…”

Section: International Conference On Modelling Simulation and Appliementioning

confidence: 99%

Effect of Temperature on the Nanoparticles Agglomerates Fluidization

Esmailpour¹,

Zarghami²,

Mostoufi³

2015

Proceedings of the 2015 International Conference on Modeling, Simulation and Applied Mathematics

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Abstract-The effect of temperature on the fluidization behavior of nanoparticles agglomerates in a fluidized bed was investigated. Moreover, a model was developed based on the force balance between drag, collision, buoyancy and gravitational forces as separation forces and van der Waals force as the attractive force. Results showed that the size of agglomerates decrease by increasing the gas velocity at constant temperature. In addition, the minimum fluidization velocity and the agglomerate size increase with increasing the temperature due to increasing the van der Waals cohesive force. The agglomerate size calculated by the present model is in good agreement with the experimental data.

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“…These agglomerates are (highly) porous, and their complex geometries have been commonly described as fractal for their self-similarity under different length scales. [8][9][10] Typical fractal dimensions have been found to range from 1.8 to 2.7. When applying ALD to such agglomerates of nanoparticles, the precursor molecules need to be transported into the porous agglomerates and then react with the particle surfaces.…”

Section: Introductionmentioning

confidence: 99%

Simulation of atomic layer deposition on nanoparticle agglomerates

Jin

Kleijn

Ommen

2016

Journal of Vacuum Science &Amp; Technology A: Vacuum, Surfaces, and Films

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Coated nanoparticles have many potential applications; production of large quantities is feasible by atomic layer deposition (ALD) on nanoparticles in a fluidized bed reactor. However, due to the cohesive interparticle forces, nanoparticles form large agglomerates, which influences the coating process. In order to study this influence, the authors have developed a novel computational modeling approach which incorporates (1) fully resolved agglomerates; (2) a self-limiting ALD half cycle reaction; and (3) gas diffusion in the rarefied regime modeled by direct simulation Monte Carlo. In the computational model, a preconstructed fractal agglomerate of up to 2048 spherical particles is exposed to precursor molecules that are introduced from the boundaries of the computational domain and react with the particle surfaces until these are fully saturated. With the computational model, the overall coating time for the nanoparticle agglomerate has been studied as a function of pressure, fractal dimension, and agglomerate size. Starting from the Gordon model for ALD coating within a cylindrical hole or trench [Gordon et al., Chem. Vap. Deposition 9, 73 (2003)], the authors also developed an analytic model for ALD coating of nanoparticles in fractal agglomerates. The predicted coating times from this analytic model agree well with the results from the computational model for Df = 2.5. The analytic model predicts that realistic agglomerates of O(109) nanoparticles require coating times that are 3–4 orders of magnitude larger than for a single particle.

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The fractal scaling of fluidized nanoparticle agglomerates

Cited by 60 publications

References 42 publications

An adhesive CFD‐DEM model for simulating nanoparticle agglomerate fluidization

An adhesive CFD‐DEM model for simulating nanoparticle agglomerate fluidization

Effect of Temperature on the Nanoparticles Agglomerates Fluidization

Simulation of atomic layer deposition on nanoparticle agglomerates

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