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Active Matter
Active matter is composed of large numbers of active "agents", each of which consumes energy in order to move or to exert mechanical forces. Due to the energy consumption, these systems are intrinsically out of thermal equilibrium. Examples of active matter are schools of fish, flocks of birds, bacteria, artificial self-propelled particles, and self-organising bio-polymers such as microtubules and actin, both of which are part of the cytoskeleton of living cells. Most examples of active matter are biological in origin; however, a great deal of current experimental work is devoted to synthetic systems. Active matter is a relatively new material classification in soft matter: the most extensively studied model, the Vicsek model, dates from 1995.

Research in active matter combines analytical techniques, numerical simulations and experiments. Notable analytical approaches include hydrodynamics, kinetic theory, and non-equilibrium statistical physics. Numerical studies mainly involve self-propelled-particles models, making use of agent-based models such as molecular dynamics algorithms as well as computational studies of hydrodynamic equations of active fluids. Experiments on biological systems extend over a wide range of scales, including animal groups (e.g., bird flocks, mammalian herds, fish schools and insect swarms ), bacterial colonies, cellular tissues (e.g. epithelial tissue layers, cancer growth and embryogenesis), cytoskeleton components (e.g., in vitro motility assays, actin-myosin networks and molecular-motor driven filaments ). Experiments on synthetic systems include self-propelled colloids (e.g., phoretically propelled particles ), driven granular matter (e.g. vibrated monolayers ), swarming robots and Quinke rotators.

Concepts in Active matter

 * Active gels
 * Dense active matter

Collective motion


 * Collective animal behavior

Animals who live in groups are inclined to demonstrate coordinated behaviors as well as emergent properties which could incorporate cost-benefit balance, information transmission and decision making process.


 * Collective cell migration

Collective cell migration is commonly seen in multicellular organisms whose cells are cohesive to each other and can move in shapes like sheets, strands, and tubes, etc. The environment can largely affect the process of migration and cells can sense their neighbors by adhesion.


 * Motility induced phase separation

Self-propelled particles tend to accumulate in areas where they move relatively slowly, while at high density, they may also move more slowly. This mechanism could lead to positive feedback which will cause motility induced phase separation.


 * Schooling, flocking and swarming

There are many ways to simulate swarms in natural settings. For example, a very common phenomenon in school of fish, colony of bees is that agents are influenced by the mean action of their neighbors. These micro-interactions between individual group members will at last emerges as a group-level behavior pattern. A simulation of such emergence is shown in the right picture.


 * Collective motion

Collective motion refers to the emergence of ordered motion in a self-propelled system. Observations has been made in such systems consisting of units ranging from macromolecules through metallic rods and robots to groups of animals and people.


 * Active stress

Active matter systems


 * Biological tissues
 * Subcellular and cell mechanics
 * Microtissues

There are many current research areas in active matter that are closely related to the biophysics of living cells, micro-tissues, or subcellular processes. For example, the cardiac cells which have typical natural beating along with interaction of adjacent neighboring cells, would demonstrate unique mechanical properties.


 * Crowd behaviour
 * Self-propelled particles and colloids

Self-propelled particles (SPP) is a broad concept which can refer to items from Active colloidal particles, dubbed nanomotors which are wet-artificial SPP to most animals which find energy from their food and show locomotion strategies. In the modeling of SPP introduced in 1995 by Tamás Vicsek et al , the SPP are point particles moving with a constant speed. Simulations have demonstrated that an appropriate "nearest neighbour rule", at low noise, would eventually lead to all the particles moving in the same direction or forming a swarm, no matter how those agents are arranged to each other or whether their neighbors change over time.