In view of the broad range of active matter systems, various numerical approaches have been developed to model such systems. Some of the major challenges arising in modeling active systems are: (i) Active matter is a multiscale material similar to other complex fluids such as milk or blood, (ii) Active fluids are intrinsically out of equilibrium due to energy consumption on microscopic scale, (iii) The interactions between active particles can be highly nonlinear and are often of multibody character (e.g. hydrodynamic interactions or interactions due to chemical stimuli), (iv) Active particles are mostly not simple geometrical objects, such as hard spheres, but rather of complex shape due to propulsion and other functional units. So far, various system-specific methods with different levels of resolution, ranging from micro- to macroscale, have been developed and employed. For example, active Brownian dynamics and partial differential equations (PDE) (such as generalized Navier Stokes equations), have been used to model active fluids in a very coarse-grained way. However, coarse gaining of active systems in not trivial and modification of microscopic details can strongly alter the macroscopic behaviour. It is unclear e.g. how particle-wall and particle-particle interactions translate into proper boundary conditions and transport coefficients of the corresponding macroscale PDE. On the other hand, mesoscale techniques (e.g. lattice Boltzmann method) try to bridge different length and time scales and to model properly the hydrodynamic interaction between active particles. However, these techniques have to compromise strongly between microscopic accuracy and macroscopic system size. Another point is that the existing techniques need to be further developed to cope with real-world applications. For example, the typical environment for micro-organisms is not a simple fluid but rather a suspension of extracellular polymeric substances (e.g. proteins, lipids and DNA), which can strongly influence the motility and interactions of the moving objects. Another long-term goal for the modeling of biological active matter is to include the adaptive behavior of micro-organisms, i.e. the ability to detect and respond to different stimuli such as material properties of the surrounding (durotaxis) or chemical concentrations (chemotaxis or quorum sensing), which requires a coupling between intracellular and extracellular models.
Similar modeling challenges apply to synthetic active matter. For example, a microscopic modeling and understanding of propulsion based on autophoresis (e.g. thermo or diffusiophoresis) is required to design artificial active materials that are capable of making decisions (based on sensory input) and adapting to enviromental changes in a self-organized manner. We will also discuss trendsetting developments of unconventional computing, namely of “materials that compute”. Recent studies indicate that active materials can be used to construct logical units and in long-term to implement autonomous computation schemes.
The goal of this workshop is to bring together the experts in modeling soft condensed matter and biological systems to tie recent advances in computational techniques and the most recent ideas and concepts of active matter theory. This workshop will provide the opportunity to compare state of the art computational active matter approaches and to open the discussion on the existing challenges and problems.