Fractal Dimension Of Agglomerates Research Articles

Impact of nanoparticle agglomeration on thermal conductivity of molten salt based nanofluids: Insights from molecular dynamics and lattice Boltzmann methods

The nanoparticle aggregation has significant influence on heat transfer properties. The contradictions between different researches exist and the underlying mechanisms of heat conduction remain unclear. To address these issues, the thermal conductivity of solar salt-SiO2 nanofluids in the non-aggregated and aggregated states was investigated, based on the combination of the advantages of molecular dynamics (MD) in revealing physical insights and lattice Boltzmann method (LBM) in simulating properties for complex structures. LBM models were simplified on the basic of MD results. Different heat transfer physics in nanofluids at nanoscale and mesoscale were compared. The results show that the thermal conductivity of aggregated nanofluid is higher than the non-aggregated nanofluid. By analyzing the diffusion coefficient, number density and vibrational density of states, we found that the previous hypotheses (such as Brownian motion, interfacial layer and interfacial thermal resistance) cannot explain the enhanced thermal conductivity induced by the nanoparticle agglomeration. The heat transfer mechanisms of aggregated nanofluid were further analyzed from new perspectives, i.e., the contributions of different material components and fluctuation modes to heat flux. It is found that the nanoparticle aggregation leads to the nanoparticle contribution increase, indicating the formation of low thermal resistance channels within the aggregates. The heat conduction contributed by collision decreases in the aggregated state, while that contributed by potential energy increases. Moreover, the thermal conductivity of aggregated nanofluid is negatively correlated with temperature, aggregate size and fractal dimension of agglomerates, and positively correlated with mass fraction of nanoparticles, degree of agglomeration, and backbone length of each aggregate.

Langevin dynamics simulation and collision frequency modification in population balance model of nanoparticle coagulation during simultaneous agglomeration and sintering

Coagulation of nanoparticles from the free-molecular to the transition regime under a high-temperature environment is investigated by coupling Langevin Dynamics (LD) model with agglomeration and finite-rate sintering. The effect of temperature on the evolution of particle size and structure is investigated, variations in agglomeration-sintering dynamics are obtained. The fractal dimension of agglomerates at different temperatures can be expressed as a function of the ratio between the characteristic collision time and sintering time. The overall collision frequency (β) is enhanced by the polydispersity and fractal properties of agglomerates compared to the monodisperse collision kernel functions. Finally, the classic function of β is modified based on the LD simulations and used in a one-dimensional population balance equation, which reproduces a better prediction of the evolution of particle size distribution during particle coagulation with agglomeration and sintering.

Study on the fractal structure of carbon nanomaterials’ smokescreen

In the diffusion of carbon nanomaterials’ smokescreen, the condensates generated by the collision of particles have fractal structures. In order to research this process, this paper is based on DLA condensation model programmed by MATLAB. Using DLA model, the geometrical structure of agglomerate formed by spherical nanoparticles is simulated and the fractal dimensions of agglomerates were computed by using the cyclotron radius method. Large numbers of simulations indicated the fractal dimension of agglomerates on two-dimensional plane distributed between 1.4 and 1.7. And with the increasing number of the particles, the fractal dimension displayed in intensive range. The research in this paper has laid a foundation for the study of the aerodynamic characteristics of condensed particles in the next stage.

Effect of sintering on the fractal prefactor of agglomerates

In a previous study different agglomerates composed by a variable number of primary particles corresponding to extreme and intermediate values of fractal dimension (Df=1, 2 and 3) were characterized to be used as reference shapes in a method for the determination of the fractal dimension of actual agglomerates. In that work, primary particles were assumed to be spherical and with no sintering or necking effects. In this work, the geometrical effect of processes such as coalescence, sintering, flattening, or surface growth is considered to evaluate the impact of these phenomena in the morphological parameters of fractal-like agglomerates. A sintering coefficient is firstly defined. Afterwards, the moment of inertia and radius of gyration of the agglomerate are determined and finally the prefactor of the power–law relationship is obtained as a function of the number of primary particles and the sintering coefficient. The equations proposed are used in a geometrical method to determine the fractal dimension of soot agglomerates, showing that sintering increases the prefactor significantly, which leads to a slight decrease in the fractal dimension of the agglomerates.

Coagulation Coefficient of Agglomerates with Different Fractal Dimensions

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.

A TEM-based method as an alternative to the BET method for measuring off-line the specific surface area of nanoaerosols

At the present time, no stabilised method exists allowing an estimation of the specific surface area for airborne nanostructured particles (nanoaerosols). Recent toxicological studies have, however, revealed biological effects linked to the surface area of these particles. Only the BET method, which can determine the specific mass surface area of a powder, constitutes a reference both in toxicology and in the materials domain. However, this technique is not applicable to nanostructured aerosols given the mass quantities of particles required (between approximately some mg to hundreds of mg taking into account the limit of quantification of existing BET instruments). To characterise the specific surface area of airborne nanostructured particles, a method based on analysing transmission electron microscopy (TEM) images is proposed. This has recourse in particular to previous work carried out in the area of nanoparticles originating from combustion (soot), and takes into account structural parameters of nanostructured particles including the number distribution of primary particles, their overlap coefficient and the fractal dimension of agglomerates and aggregates. The approach proposed in this work was applied to five commercially-available nanostructured powders of differing natures (SiO 2, ZrO 2, Al 2O 3, Fe 2O 3 and Fe 3O 4). This first involved their prior analysis by the BET method and then being placed in suspension in aerosol form using a vortex-type shaker system. The procedure to calculate the specific surface area using image analysis was then applied to the sampled aerosols and compared to the BET measurements. The experimental results obtained on the five nanostructured powders cover a range of specific surface areas from 20 to 200 m 2/g, the primary particles having mean diameters varying from 7 to 47 nm. Close agreement was observed between the two approaches which, taking into account measurement uncertainties, are statistically equivalent at significance level α = 0.05.