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The demixing and sorting strategies for chiral active mixtures are crucial to the biochemical and pharmaceutical industries. However, it remains uncertain whether chiral mixed particles can spontaneously demix without the aid of specific strategies. In this paper, we investigate the demixing behaviors of binary mixtures in a model of chiral active particles to understand the demixing mechanism of chiral active mixtures. We demonstrate that chiral mixed particles can spontaneously demix in motility-induced phase separation (MIPS). The hidden velocity alignment in MIPS allows particles of different types to accumulate in different clusters, thereby facilitating separation. There exists an optimal angular velocity or packing fraction at which this separation is optimal. Noise (translational or rotational diffusion) can promote mixture separation in certain cases, rather than always being detrimental to the process. Since the order caused by the hidden velocity alignment in this process is not global, the separation behavior is strongly dependent on the system size. Furthermore, we also discovered that the mixture separation caused by MIPS is different from that resulting from explicit velocity alignment. Our findings are crucial for understanding the demixing mechanism of chiral active mixtures and can be applied to experiments attempting to separate various active mixtures in the future.

The demixing of embryonic cell populations plays a crucial role in developing organisms. This process facilitates the compartmentalization of various cell types, allowing for specialized functions and tissue development. We examine if orientation coupling alone is sufficient to induce demixing in a binary cell mixture. To address this question, we utilized the self-propelled Voronoi model to investigate the demixing behavior of binary cells with different chirality in the presence of polar alignment. There exists an optimal value of chirality or polar alignment at which cells undergo robust demixing. Furthermore, our research reveals that a particular interplay between the self-propelled velocity and the shape index can aid in the process of cell demixing. Notably, an increase in self-propelled velocity corresponds to a decrease in the shape index value required for effective cell demixing. The ability to manipulate cell demixing through orientation coupling could offer new strategies for engineering tissue structures or controlling cell demixing in regenerative medicine and synthetic biology.

In biological microscopy, light scattering represents the main limitation to image at depth. Recently, a set of wavefront shaping techniques has been developed in order to manipulate coherent light in strongly disordered materials. The Transmission Matrix approach has shown its capability to inverse the effect of scattering and efficiently focus light. In practice, the matrix is usually measured using an invasive detector or low-resolution acoustic guide stars. Here, we introduce a non-invasive and all-optical strategy based on linear fluorescence to reconstruct the transmission matrices, to and from a fluorescent object placed inside a scattering medium. It consists in demixing the incoherent patterns emitted by the object using low-rank factorizations and phase retrieval algorithms. We experimentally demonstrate the efficiency of this method through robust and selective focusing. Additionally, from the same measurements, it is possible to exploit memory effect correlations to image and reconstruct extended objects. This approach opens up a new route towards imaging in scattering media with linear or non-linear contrast mechanisms. Light scattering represents the main limitation to image at depth in biological microscopy. The authors present a strategy to characterize light propagation in and out of a scattering medium based on linear fluorescence feedback and from the same measurements exploit memory effect correlations to image and reconstruct extended objects.

Biological organisms and artificial active particles self-organize into swarms and patterns. Open questions concern the design of emergent phenomena by choosing appropriate forms of activity and particle interactions. A particularly simple and versatile system are 3D-printed robots on a vibrating table that can perform self-propelled and self-spinning motion. Here we study a mixture of minimalistic clockwise and counter-clockwise rotating robots, called rotors. Our experiments show that rotors move collectively and exhibit super-diffusive interfacial motion and phase separate via spinodal decomposition. On long time scales, confinement favors symmetric demixing patterns. By mapping rotor motion on a Langevin equation with a constant driving torque and by comparison with computer simulations, we demonstrate that our macroscopic system is a form of active soft matter. Active rotating particles were shown to undergo a phase separation through numerical simulations. Here the authors provide an experimental realization of this phenomenon by presenting an ensemble of 3D-printed robots that rotate in different directions and interact with each other.

Multivalent protein-protein and protein-RNA interactions are the drivers of biological phase separation. Biomolecular condensates typically contain a dense network of multiple proteins and RNAs, and their competing molecular interactions play key roles in regulating the condensate composition and structure. Employing a ternary system comprising of a prion-like polypeptide (PLP), arginine-rich polypeptide (RRP), and RNA, we show that competition between the PLP and RNA for a single shared partner, the RRP, leads to RNA-induced demixing of PLP-RRP condensates into stable coexisting phases—homotypic PLP condensates and heterotypic RRP-RNA condensates. The morphology of these biphasic condensates (non-engulfing/ partial engulfing/ complete engulfing) is determined by the RNA-to-RRP stoichiometry and the hierarchy of intermolecular interactions, providing a glimpse of the broad range of multiphasic patterns that are accessible to these condensates. Our findings provide a minimal set of physical rules that govern the composition and spatial organization of multicomponent and multiphasic biomolecular condensates. Liquid ribonucleoprotein condensates typically involve a dense network of multiple proteins and RNAs. Here, the authors employ a minimal system composed of Prion-like polypeptides (PLP), Arg-rich polypeptides (RRP), and RNA to form biphasic condensates with diverse morphologies tunable via mixture stoichiometry and hierarchy of intermolecular interactions.

The active layer morphology transition of organic photovoltaics under non-equilibrium conditions are of vital importance in determining the device power conversion efficiency and stability; however, a general and unified picture on this issue has not been well addressed. Using combined in situ and ex situ morphology characterizations, morphological parameters relating to kinetics and thermodynamics of morphology evolution are extracted and studied in model systems under thermal annealing. The coupling and competition of crystallization and demixing are found to be critical in morphology evolution, phase purification and interfacial orientation. A unified model summarizing different phase diagrams and all possible kinetic routes is proposed. The current observations address the fundamental issues underlying the formation of the complex multi-length scale morphology in bulk heterojunction blends and provide useful morphology optimization guidelines for processing devices with higher efficiency and stability. Designing efficient blue perovskite LEDs by using mixed halides perovskite is still a challenge, limited mainly by the phase segregation issue. Here, the authors demonstrate in situ fabrication of quasi-2D CsPbClBr2 nanocrystal films with mixed ligands to overcome the constraint.

Non-invasive optical imaging techniques are essential diagnostic tools in many fields. Although various recent methods have been proposed to utilize and control light in multiple scattering media, non-invasive optical imaging through and inside scattering layers across a large field of view remains elusive due to the physical limits set by the optical memory effect, especially without wavefront shaping techniques. Here, we demonstrate an approach that enables non-invasive fluorescence imaging behind scattering layers with field-of-views extending well beyond the optical memory effect. The method consists in demixing the speckle patterns emitted by a fluorescent object under variable unknown random illumination, using matrix factorization and a novel fingerprint-based reconstruction. Experimental validation shows the efficiency and robustness of the method with various fluorescent samples, covering a field of view up to three times the optical memory effect range. Our non-invasive imaging technique is simple, neither requires a spatial light modulator nor a guide star, and can be generalized to a wide range of incoherent contrast mechanisms and illumination schemes. The authors demonstrate non-invasive fluorescence imaging behind scattering layers beyond the optical memory effect. They achieve this by demixing speckle patterns emitted by a fluorescent object under variable unknown random illumination, using matrix factorization and a fingerprint-based reconstruction.

An exactly solvable model mimicking demixing of two Bose-Einstein condensates at the many-body level of theory is devised. Various properties are expressed in closed form along the demixing pathway and investigated. The connection between the center-of-mass coordinate and in particular the relative center-of-mass coordinate and demixing is explained. The model is also exactly solvable at the mean-field level of theory, allowing thereby comparison between many-body and mean-field properties. Applications are briefly discussed.

Demixing binary liquids is a ubiquitous transition explained using a well-established thermodynamic formalism that requires the equality of intensive thermodynamics parameters across phase boundaries. Demixing transitions also occur when binary fluid mixtures are driven away from equilibrium, but predicting and designing such out-of-equilibrium transitions remains a challenge. Here we study the liquid–liquid phase separation of attractive DNA nanostars driven away from equilibrium using a microtubule-based active fluid. We find that activity lowers the critical temperature and narrows the range of coexistence concentrations, but only in the presence of mechanical bonds between the liquid droplets and reconfiguring active fluid. Similar behaviours are observed in numerical simulations, suggesting that the activity suppression of the critical point is a generic feature of active liquid–liquid phase separation. Our work describes a versatile platform for building soft active materials with feedback control and providing an insight into self-organization in cell biology.The rational design of out-of-equilibrium demixing transitions remains challenging. Active fluids are used to control the liquid–liquid phase separation of passive DNA nanostars and establish the activity-based control of the phase diagram.

We consider simple mean field continuum models for first order liquid-liquid demixing and solid-liquid phase transitions and show how the Maxwell construction at phase coexistence emerges on going from finite-size closed systems to the thermodynamic limit. The theories considered are the Cahn-Hilliard model of phase separation, which is also a model for the liquid-gas transition, and the phase field crystal model of the solid-liquid transition. Our results show that states comprising the Maxwell line depend strongly on the mean density with spatially localized structures playing a key role in the approach to the thermodynamic limit.