Cluster models for random particle aggregates—Morphological statistics and collision distance

Teichmann, Jakob; Boogaart, K. Gerald van den

doi:10.1016/j.spasta.2015.03.002

Cited by 8 publications

(7 citation statements)

References 17 publications

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“…For example, Teichmann et al found that, as aggregate size grows, most particles are attached to two other particles. 50 While this is the case for homoaggregation, the models could be adapted to heteroaggregation and with a large enough sample of aggregates deriving mean values of n i for smaller aggregates.…”

Section: ■ Discussionmentioning

confidence: 99%

Statistical Thermodynamic Description of Heteroaggregation between Anthropogenic Particulate Matter and Natural Particles in Aquatic Environments

Wheeler

Lower

2021

ACS Earth Space Chem.

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Aggregation is a key process in understanding the fate and transport of anthropogenic particulate matter, namely, nanoparticles and microplastics, in aquatic environments. Recent research has subdivided aggregation into two processes: homoaggregation, where two like particles aggregate, such as two fragments of microplastic, and heteroaggregation, where two unlike particles aggregate, such as a nanoparticle and sediment. Of the two processes, heteroaggregation is generally assumed to be more important because anthropogenic particles are much less concentrated than their naturally occurring counterparts. This assumption remains largely untested in many natural settings, and most aggregation models discount the process of disaggregation entirely. To address these deficiencies, we created a statistical thermodynamic aggregation model to predict the steady-state size distribution of any two-particle system, accounting for homoaggregation, heteroaggregation, and disaggregation. The results of the model confirm that homoaggregation is likely a negligible process for the fate of nanoparticles and microplastics. However, the model predicts that heteroaggregation will be incomplete, with at least 10% of the nanoparticles or microplastics remaining unaggregated (i.e., monomeric form) even under favorable bonding conditions and large concentration disparities (i.e., surrounded by a far greater concentration of secondary particles). Our model also predicts that heteroaggregation is influenced by the magnitude of the enthalpy of bonding (H b) between the anthropogenic particle and the larger natural particle. While these predictions require experimental verification, the implications of this study highlight the critical need to consider and carefully examine disaggregation in the context of heteroaggregation (and homoaggregation) of anthropogenic and natural (in)organic particles.

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Section: ■ Discussionmentioning

confidence: 99%

Statistical Thermodynamic Description of Heteroaggregation between Anthropogenic Particulate Matter and Natural Particles in Aquatic Environments

Wheeler

Lower

2021

ACS Earth Space Chem.

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“…Hence, the aggregate system achieves its SPSD faster with a decreasing Df [42]. For agglomerates, the primary particles stick upon inter-particle collision, forming fractal-like agglomerates with Df =1.9 [42][43][44]. When the volume fractions are higher, the Df of aggregates formed by collision is closer to 1.9.…”

Section: Cluster Analysis Of Collision Particlesmentioning

confidence: 99%

“…Lower Df exhibits an increased cross surface area, which leads to a faster collision among aggregates and monomers. Hence, the aggregate system achieves its SPSD faster with a decreasing Df [42]. For agglomerates, the primary particles stick upon inter-particle collision, forming fractal-like agglomerates with Df =1.9 [42][43][44].…”

Section: Cluster Analysis Of Collision Particlesmentioning

confidence: 99%

Polymerization and Collision in High Concentrations for Brownian Coagulation

Wang

Liu

et al. 2021

Applied Sciences

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Aggregation always occurs in industrial processes with fractal-like particles, especially in dense systems (the volume fraction, ϕ>1%). However, the classic aggregation theory, established by Smoluchowski in 1917, cannot sufficiently simulate the particle dynamics in dense systems, particularly those of generat ed fractal-like particles. In this article, the Langevin dynamic was applied to study the collision rate of aggregations as well as the structure of aggregates affected by different volume fractions. It is shown that the collision rate of highly concentrated particles is progressively higher than that of a dilute concentration, and the SPSD (self-preserving size distribution) is approached (σg,n≥1.5). With the increase in volume fraction, ϕ, the SPSD broadens, and the geometric standard is 1.54, 1.98, and 2.73 at ϕ= 0.1, 0.2, and 0.3. When the volume fraction, ϕ, is higher, the radius of gyration is smaller with the same cluster size (number-based), which means the particle agglomerations are in a tighter coagulation. The fractal-like property Df is in the range of 1.60–2.0 in a high-concentration system. Knowing the details of the collision progress in a high-concentration system can be useful for calculating the dynamics of coagulating fractal-like particles in the industrial process.

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“…Another quantity of interest is the fractal dimension which can be calculated from a two dimensional image obtained from theory or experiment. [33,34,35] Both the pair correlation and fractal dimension gain more value as the number of particles in the system becomes larger and so, we focus on the normalized length and angular order parameters. We did calculate the fractal dimension for all agglomerates following the methods of Refs.…”

Section: Characterization Of Agglomeratesmentioning

confidence: 99%

Why do magnetic nanoparticles form messy clumps? Taking into account the bridging or sticking of ligands in simulations

Anderson¹,

Louie²,

Serantes³

et al. 2016

Preprint

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Experiments on magnetic nanoparticles in a viscous medium have shown that agglomerates form that display complex shapes. However, most theoretical results predict more simple, ordered shapes, such as single-particle width chains. To account for this discrepancy we have created a theoretical model that phenomenologically includes the bridging or "stickiness" between ligands on nearby nanoparticles. This interaction is accounted for through a unitless stickiness parameter c that can be varied between 0 (no bridging between ligands) and 1 (irreversible bridging or sticking together on impact). An analytic estimate for the value of c is provided based on a comparison between the time for a particle to diffuse to an agglomerate compared to the time for it to reorient into the local magnetic field direction. Numerical Langevin simulations are performed using ferromagnetic, 50 nm and 25 nm diameter magnetite nanoparticles with various ligand coating lengths in hexane in order to support the analytic estimate. The simulations produce agglomerates that are qualitatively and quantitatively similar to experimental results.

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Cluster models for random particle aggregates—Morphological statistics and collision distance

Cited by 8 publications

References 17 publications

Statistical Thermodynamic Description of Heteroaggregation between Anthropogenic Particulate Matter and Natural Particles in Aquatic Environments

Statistical Thermodynamic Description of Heteroaggregation between Anthropogenic Particulate Matter and Natural Particles in Aquatic Environments

Polymerization and Collision in High Concentrations for Brownian Coagulation

Why do magnetic nanoparticles form messy clumps? Taking into account the bridging or sticking of ligands in simulations

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