The fluidization of cohesive powders has been extensively researched over the years. When looking at literature on the fluidization of cohesive particles, one will often find papers concerned with only micro- or only nano-sized powders. It is, however, unclear whether they should be treated differently at all. In this paper, we look at differences and similarities between cohesive powders across the size range of several nanometres to 10s of micrometres. Classification of fluidization behaviour based on particle size was found to be troublesome since cohesive powders form agglomerates and using the properties of these agglomerates introduces new problems. When looking at inter-particle forces, it is found that van der Waals forces dominate across the entire size range that is considered. Furthermore, when looking into agglomeration and modelling thereof, it was found that there is a fundamental difference between the size ranges in the way they agglomerate. Where the transition between the types of agglomeration is located is, however, unknown. Finally, how models are made and agglomerate sizes are measured is currently insufficient to accurately predict or measure their sizes consistently.

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Nature-inspired self-cleaning surfaces have attracted considerable attention from both fundamental research and practical applications. This review adopts a chemical-engineering point of view and focuses on mechanisms, modelling, and manufacturing (M3) of nature-inspired self-cleaning surfaces. We will introduce six nature-inspired self-cleaning mechanisms: The Lotus-effect, superhydrophobic-induced droplet jumping, superhydrophobic-induced unidirectional movement of water droplet, underwater-superoleophobic-based self-cleaning, slippery-based self-cleaning, and dry self-cleaning. These mechanisms of nature self-cleaning examples are popular and well-known as well as have been widely applied or exhibited potential applications in our daily life and industrial productions. The mathematical and numerical modelling of the identified self-cleaning mechanisms will be carefully introduced, which will contribute to the rational design and reproducible construction of these functional self-cleaning surfaces. Finally, we will discuss how these materials can be produced, with a focus on scalable manufacturing. We hope this review will strengthen the understanding on nature-inspired self-cleaning surfaces and stimulate interdisciplinary collaboration of material science, biology and engineering.

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We develop a novel coarse-grained contact model for Discrete Element Method simulations of TiO 2 nanoparticle films subjected to mechanical stress. All model elements and parameters are derived in a self-consistent and physically sound way from all-atom Molecular Dynamics simulations of interacting particles and surfaces. In particular, the nature of atomic-scale friction and dissipation effects is taken into account by explicit modelling of the surface features and water adsorbate layers that strongly mediate the particle-particle interactions. The quantitative accuracy of the coarse-grained model is validated against all-atom simulations of TiO 2 nanoparticle agglomerates under tensile stress. Moreover, its predictive power is demonstrated with calculations of force-displacement curves of entire nanoparticle films probed with force spectroscopy. The simulation results are compared with Atomic Force Microscopy and Transmission Electron Microscopy experiments.@en

Dielectrophoresis (DEP) is a versatile technique for the solution of difficult (bio-)particle separation tasks based on size and material. Particle motion by DEP requires a highly inhomogeneous electric field. Thus, the throughput of classical DEP devices is limited by restrictions on the channel size to achieve large enough gradients. Here, we investigate dielectrophoretic filtration, in which channel size and separation performance are decoupled because particles are trapped at induced field maxima in a porous separation matrix. By simulating microfluidic model porous media, we derive design rules for DEP filters and verify them using model particles (polystyrene) and biological cells (S. cerevisiae, yeast). Further, we bridge the throughput gap by separating yeast in an alumina sponge and show that the design rules are equally applicable in real porous media at high throughput. While maintaining almost 100% efficiency, we process up to 9 mL min^-1, several orders of magnitude more than most state-of-the-art DEP applications. Our microfluidic approach provides new insight into trapping dynamics in porous media, which even can be applied in real sponges. These results pave the way toward high-throughput retention, which is capable of solving existing problems such as cell separation in liquid biopsy or precious metal recovery.

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Although the gas-phase production of nanostructured solids has already been carried out in industry for decades, only in recent years has research interest in this topic begun to increase. Nevertheless, despite the remarkable scientific progress made recently, many long-established processes are still used in industry. Scientific advancements can potentially lead to the improvement of existing industrial processes, but also to the development of completely new routes. This paper aims to review state-of-the-art synthesis and processing technologies, as well as the recent developments in academic research. Flame reactors that produce inorganic nanoparticles on industrial- and lab-scales are described, alongside a detailed overview of the different systems used for the production of carbon nanotubes and graphene. We discuss the problems of agglomeration and mixing of nanoparticles, which are strongly related to synthesis and processing. Finally, we focus on two promising processing techniques, namely nanoparticle fluidization and atomic layer deposition.

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Fluidization is a technique used to process large quantities of nanopowder with no solvent waste and a large gas–solid contact area. Nonetheless, nanoparticles in the gas phase form clusters, called agglomerates, due to the relatively large adhesion forces. The dynamics within the fluidized bed influence the mechanism of formation, and thus, the morphology of the agglomerates. There are many theoretical models to predict the average size of fluidized agglomerates; however, these estimates of the average lack information on the whole size range. Here, we predict the agglomerate size distribution within the fluidized bed by estimating the mode and width using a force balance model. The model was tested for titania (TiO₂), alumina (Al₂O₃), and silica (SiO₂) nanopowders, which were studied experimentally. An in-situ method was used to record the fluidized agglomerates for size analysis and model validation.

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Fluidizing nanopowders in industrial processes for chemical reactions or physical processes typically takes multiple hours. Therefore, we investigated in this study the long-term fluidization behavior of titania nanopowders at time scales of several hours. We analyzed bed properties as well as agglomerate properties in the splash zone of the fluidized bed using a settling tube. The bed expansion as well as the agglomerate size decrease over time while the fractal dimension of the agglomerates stay nearly constant. It seems that at low gas velocities, stratification of the agglomerates in the fluidized bed occurs. Furthermore, our results suggest that at all investigated gas velocities small entities break from the outer part of the agglomerates during fluidization.

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In this work we present a comprehensive experimental study to determine the contact forces between individual metal oxide nanoparticles in the gas-phase using atomic force microscopy. In addition, we determined the amount of physisorbed water for each type of particle surface. By comparing our results with mathematical models of the interaction forces, we could demonstrate that classical continuum models of van der Waals and capillary forces alone cannot sufficiently describe the experimental findings. Rather, the discrete nature of the molecules has to be considered, which leads to ordering at the interface and the occurrence of solvation forces. We demonstrate that inclusion of solvation forces in the model leads to quantitative agreement with experimental data and that tuning of the molecular order by addition of isopropanol vapor allows us to control the interaction forces between the nanoparticles.

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Efficient nanopowder processing requires knowledge of the powder’s mechanical properties. Due to the large surface area to volume ratio, nanoparticles experience relatively strong attractive interactions, leading to the formation of micron-size porous structures called agglomerates. Significant effort has been directed towards the development of models and experimental procedures to estimate the elasticity of porous objects such as nanoparticle agglomerates; however, none of the existing models has been validated for solid fractions below 0.1. Here, we measure the elasticity of titania (TiO2, 22 nm), alumina (Al2O3, 8 nm), and silica (SiO2, 16 nm) nanopowder agglomerates by Atomic Force Microscopy, using a 3.75 μm glass colloid for the stress–strain experiments. Three sample preparations with varying degree of powder manipulation are assessed. The measured Young’s moduli are in the same order of magnitude as those predicted by the model of Kendall et al., thus validating it for the estimation of the Young’s modulus of structures with porosity above 90 %.@en