Dmitry Fedosov | Searcharxiv

arXiv2025

Intelligent Soft Matter: Towards Embodied Intelligence

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static or predefined functions, intelligent soft matter dynamically interacts with its environment. It integrates multiple sensory inputs, retains experiences, and makes decisions to optimize its responses. Inspired by biological systems, these materials intend to leverage the inherent properties of soft matter: flexibility, self-evolving, and responsiveness to perform functions that mimic cognitive processes. By synthesizing current research trends and projecting their evolution, we present a forward-looking perspective on how intelligent soft matter could be constructed, with the aim of inspiring innovations in fields such as biomedical devices, adaptive robotics, and beyond. We highlight new pathways for integrating design of sensing, memory and action with internal low-power operations and discuss challenges for practical implementation of materials with "intelligent behavior". These approaches outline a path towards to more robust, versatile and scalable materials that can potentially act, compute, and "think" by their inherent intrinsic material behaviour beyond traditional smart technologies relying on external control.

cond-mat.soft↗

arXiv2023

Janus microswimmers are poor hydrodynamic mixers

The generation of fluid flows by autophoretic microswimmers has been proposed as a mechanism to enhance mass transport and mixing at the micro- and nanoscale. Here, we experimentally investigate the ability of model 2-D "active baths" of photocatalytic silica-titania Janus microspheres to enhance the diffusivity of tracer particles at different microswimmer densities below the onset of collective behaviour. Inspired by the similarities between our experimental findings and previous results for biological microorganisms, we then model our Janus microswimmers using a general squirmer framework, specifically treating them as neutral squirmers. The numerical simulations faithfully capture our observations, offer an insight into the microscopic mechanism underpinning tracer transport, and allow us to expand the parameter space beyond our experimental system. We find strong evidence that near-field interactions dominate enhancements in tracer diffusivity in active Janus baths, leading to the identification of an operating window for enhanced tracer transport by chemical microswimmers based on scaling arguments. Based on this argumentation, we suggest that for many chemically active colloidal systems, hydrodynamics alone is likely to be insufficient to induce appreciable mixing of passive components with large diffusion coefficients.

cond-mat.soft↗