Recent Advances in Active Matter

Collective behaviors in active matter arise from interactions among many autonomous units, often without central control—birds flock, fish school, ants colonize, and cells coordinate, to name a few. Assemblies of active particles, whether biological, chemical, or synthetic, interact with one another and their environment to sense, integrate, and respond to diverse physicochemical cues. These interactions generate striking patterns and functions across scales, from molecules to tissues and from microscopic colloids to macroscopic swarms, with remarkable robustness, adaptability, and memory. Active matter systems harvest energy from their surroundings and convert it into mechanical work, pushing them far from equilibrium and enabling long-range organization, dynamic adaptation, and diverse collective states.

While experimental studies, particularly in living systems, have led the way, computational active matter faces unique challenges, as equilibrium frameworks often fall short in describing far-from-equilibrium ordering. Yet the field is rapidly advancing: particle-based simulations, continuum and hydrodynamic models, and fluid–structure interaction frameworks now capture phenomena such as motility-induced phase separation, active turbulence, and defect dynamics. Machine learning and high-performance computing are accelerating discovery, revealing hidden patterns, and guiding the design of swarm behaviors. Applications are broad, spanning microswimmer engineering, tissue morphogenesis, swarm robotics, adaptive materials, and distributed information processing.

This special Collection on Recent Advances in Active Matter seeks to bring together contributions that advance computational tools, uncover emergent phenomena, and demonstrate new applications. We warmly invite researchers across disciplines to submit. Submissions may address, but are not limited to, the following themes:

Computational Frameworks

• Particle-based simulations (agent-based, MD, active Brownian particles)
• Continuum and hydrodynamic modeling (phase-field, elastic/viscoelastic, fluid–structure interactions)
• Multiscale computational approaches bridging molecular to macroscopic scales
• Data-driven, machine learning, and AI-accelerated simulations

Emergent Phenomena

• Motility-induced phase separation and pattern formation
• Active turbulence, chaotic flows, and transport in active fluids
• Defect dynamics in active nematics and liquid crystals
• Mechanochemical feedbacks, chemotaxis, and mechanotransduction
• Collective behaviors in biological systems (cytoskeleton, tissues, biofilms)
• Synthetic and engineered collectives (microswimmers, Janus particles, active gels, swarm robotics)

Applications and Frontiers

• Computational design of adaptive and bio-inspired materials
• Active matter–based strategies for biomedical therapies and diagnostics
• Control of swarm behaviors and robotic collectives
• Cross-scale computational principles unifying molecules, organisms, and engineered swarms

（Important Notes for authors: Experimental studies are advised to be submitted to npj Soft Matter, while computational studies should be submitted to npj Computational Materials.）