Advances in collective patterns, spatial organization and hierarchical structures in soft matter

Several soft matter systems, for example liquid crystals, colloids, polymers, and active matter, share features like weak interactions and high sensitivity to external stimuli. These systems tend to spontaneously generate collective patterns and hierarchical structures. From such conditions, it follows that the macroscopic behavior is largely determined by collective self-organization. Consequently, great relevance is assumed by the multiscale correlations between local order, mesoscopic interactions and collective pattern at macroscopic scale. In some soft systems, this hierarchy becomes crucial for mechanical and dynamic properties. In amorphous and soft materials, where the relevant spatial information is not concentrated on a unique length-scale, it is difficult to describe these hierarchical structures with local descriptors, and novel methods (e.g. based on topology) are emerging. As an example, recently it has been proved that topological defects can have an influence on global spatial organization, while in other systems, like active matter, it is the flux of energy that leads to the emergence of collective patterns and out-of-equilibrium organization.The goal of the Research Topic is to report recent progress, both experimental and theoretical, that advance the understanding of the mechanisms that favor the emergence of collective patterns or hierarchical structures in soft matter. Collective patterns, spatial organization and hierarchical structures are not separate aspects, but manifestation of the same soft matter physics, that can be exploited to attain multifunctional, robust and adaptive materials. Therefore, emphasis is given to the design and optimization of multiscale structures (from nanoscale to meso- and macroscale) to shape specific properties or functions in soft materials and composites. Further, it is of particular interest, research on the application of topological data analysis (TDA) and data-driven methods to capture the relevant spatial information that drives the self-assembly or system evolution. The objective is to show that novel, non-conventional methods and descriptors are able not only to describe partial ordering, multiscale hierarchy and defects in soft matter, but also to identify subtle phase transitions and collective organization, becoming predictive methods in the study of soft materials.In the Research Topic, we aim at contributions from the entire soft matter community, including physics, chemistry, materials science and biology, to make the field evolve from a phenomenological approach to a data-driven, multiscale one. Applications encompass, but are not limited to tissue engineering, drug delivery, smart biomaterials, efficient transport in energy harvesting and storage, and soft photonics. Within the scope of the Topic fall research articles and reviews related – but not limited – to the following themes:- Integration of continuum models, simulations and topological description. - Studies on the stability and evolution of collective patterns in active matter- Hierarchical patterns for controlled wettability- Hierarchical patterns for reduced friction- Bio-inspired adhesives- Semi-ordered materials and nanocomposites.- Phase transitions (order-disorder, isotropic-nematic) and phase coexistence- Defect mediated properties- Skin-like materials- Application of topological data analysis (TDA) and geometrical descriptors- Topological soft matter- Photonic band structure design- Tracking of collective cell motion- Hierarchical bioinspired nanocomposites- Nanoparticle superclusters- Thin film soft material for energy systems- Chemical design of soft matter systemsTopic editor Giuseppe Di Florio is employed by Enea. All other Topic Editors declare no competing interests with regards to the Research Topic subject Topic editors: Giuseppe Di Florio, Edmondo Battista, Maddalena Corsini Source: https://www.frontiersin.org/research-topics/81623/advances-in-collective-patterns-spatial-organization-and-hierarchical-structures-in-soft-matter