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Optical sorting: past, present and future
Optical sorting combines optical tweezers with diverse techniques, including optical spectrum, artificial intelligence (AI) and immunoassay, to endow unprecedented capabilities in particle sorting. In comparison to other methods such as microfluidics, acoustics and electrophoresis, optical sorting offers appreciable advantages in nanoscale precision, high resolution, non-invasiveness, and is becoming increasingly indispensable in fields of biophysics, chemistry, and materials science. This review aims to offer a comprehensive overview of the history, development, and perspectives of various optical sorting techniques, categorised as passive and active sorting methods. To begin, we elucidate the fundamental physics and attributes of both conventional and exotic optical forces. We then explore sorting capabilities of active optical sorting, which fuses optical tweezers with a diversity of techniques, including Raman spectroscopy and machine learning. Afterwards, we reveal the essential roles played by deterministic light fields, configured with lens systems or metasurfaces, in the passive sorting of particles based on their varying sizes and shapes, sorting resolutions and speeds. We conclude with our vision of the most promising and futuristic directions, including AI-facilitated ultrafast and bio-morphology-selective sorting. It can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.
Mass and particle size distribution of household dust on children’s hands
Children are vulnerable to household dust exposure; however, to date, a handful of studies simultaneously report both the mass and particle size of household dust found on children’s hands after natural indoor play activities.
Collective chemo-mechanical oscillations and cluster waves in communicating colloids
Communication and feedback are crucial for the self-organization and the emergent viscoelastic behavior of life-like soft matter systems. However, the specific effects of communication between the individual components on their properties, interactions, and collective dynamics are not fully understood. Here, we report on two-dimensional Brownian dynamics simulations of catalytically active, non-motile hydrogel colloids with explicit resolution of chemical signaling clouds and chemo-mechanical feedback through a size-dependent permeability for the fuel. In particular, we investigate how their spatiotemporal structure and dynamical behavior depend on the communication magnitude and the colloid density. We discover a diverse range of nonequilibrium structures and active phases, including transitions from uncorrelated to synchronized oscillations and the emergence of elastic cluster waves for increasing chemo-mechanical coupling. Our findings highlight microscopic physical principles behind communication-driven cooperativity and could inform the design of active soft matter systems with adaptive functionalities.
Crossover scaling of structural and mechanical properties in 3D assemblies of non-spherical, frictional particles
The stability of particle assemblies is strongly affected by particle shape, yet definitive laws describing key properties, such as the mean contact number and apparent friction coefficient, remain elusive. Using X-ray computed tomography and discrete element simulations, we study 70 assemblies of 3D frictional particles. Once properly rescaled, our data collapse onto master curves, revealing linear relationships linking particle shape to these properties for short-axis particles below certain crossover points. These data suggest that the scaling behavior for the mean contact number can be maintained at lower sphericity than the apparent friction coefficient, indicating different sensitivity of the system’s structural versus mechanical properties to particle shape. Through analyzing elongated particles beyond the crossover points, we find that while particle elongation increases the contact number, it has limited effects on improving mechanical stability. This insight, along with the law, paves the route towards optimizing granular packing via manipulating particle shape.
Experimental observation of gapped shear waves and liquid-like to gas-like dynamical crossover in active granular matter
Unlike crystalline solids, liquids lack long-range order, resulting in diffusive shear fluctuations rather than propagating waves. Simulations predict that liquids exhibit a k-gap in wave-vector space, where solid-like transverse waves reappear above this gap. Experimental evidence in classical liquids has been limited, observed only in 2D dusty plasmas. Here, we investigate this phenomenon using active Brownian vibrators and uncover distinct gas-like and liquid-like phases depending on the packing fraction. We measure key properties, including pair correlation functions, mean square displacements, velocity auto-correlation functions, and vibrational density of states. In the liquid-like phase, we confirm the k-gap in transverse excitations, whose size grows as the packing fraction decreases and eventually disappears in the gas phase. Our findings extend the concept of the k-gap to active granular systems and reveal striking parallels with supercritical fluids.
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