Any "function" in living and synthetic materials requires to autonomously create inhomogeneous and adaptable structures, typically on very different length scales from molecular to macroscopic. Our research evolves around the question how such complex "behavior" (both structural and dynamical) emerges when many molecules (more generally, constituents) come together, and what are the physical principles. We tackle specific problems from the perspective of classical many-body statistical physics, in particular the theory of phase transitions, but extended to systems constantly driven away from thermal equilibrium. To this end, we also develop methods, both theoretical and numerical.
How does order emerge from disorder?
We explore this central question through the following research topics and address questions from biology, chemistry, and materials science.
(1) Self-assembly
Background
Self-assembly is a process by which systems spontaneously organize into structured patterns or functional architectures. This phenomenon is driven by local interactions between components, such as molecules, nanoparticles, or polymers, and can occur through various mechanisms, including van der Waals forces, hydrogen bonding, or electrostatic interactions. This process plays a crucial role in the development of smart materials.
We study
- Nucleation
- Phase space complexity
- Multifarious self-assembly
- Structure formation at soft-matter interfaces
(2) Biomolecular condensates
Background
Whereas our genome is localized in the membrane-enclosed nucleus, membrane-less compartments within the nucleus further establish sections of specialized function (e.g. transcriptional condensates). Membrane-less compartments formed by phase separation are spatially and temporally highly dynamic, enabling context-specific control of cellular processes such as gene regulation. Our goal is to understand the formation of such condensates which are driven out of equilibrium theoretically.
We study
- Non-equilibrium phase coexistence
- Microphase separation and reversed Ostwald ripening
- Spatial and temporal oscillations in reaction-diffusion systems
- Active field theories
(3) Active matter
Background
Active matter refers to systems composed of individual units that consume energy to generate motion. Unlike passive materials, active matter operates far from thermodynamic equilibrium because its constituents continuously convert energy into movement at the microscopic scale. Examples range from biological systems such as bacterial colonies, cell tissues, and flocks of birds to synthetic systems like self-propelled colloids and engineered microswimmers.
We study
- Thermodynamically consistent description of active particles
- Collective behaviors (e.g. edge currents and cluster formation)
- Hyperuniformity
(4) Intelligent Materials
Background
Materials that can sense their environment, process information, and respond adaptively are of central interest. These systems often combine principles from soft matter physics, active matter, and nonlinear dynamics. Understanding them requires computational modeling of complex, interacting components.
We study
- Microrobots
- Adaptive materials
- Intelligent active particles
Recent progress made in (2)
Equilibrium phase coexistence is well understood, however, we only have limited insights if the system is driven out of equilibrium. In our recent preprint, we establish phase coexistence conditions for a two-component chemically driven mixture. In contrast to the equilibrium case, the chemical potentials are not equalized in the two bulk phases.
Recent progress made in (3)
Living systems adapt through complex internal dynamics that couple energy consumption to behavior. In this recent work, we develop a thermodynamically consistent active matter framework with internal state networks, enabling directed motion and the explicit calculation of energy dissipation.
Recent progress made in (4)
We introduce an active particle model that we call topological chiral random walker which is able to sense boundaries in a system and delvops robust edge currents around them. Our walker effectively solves mazes and speeds up self-assembly by around 80%. For more details, see preprint.
Contact
Thomas Speck
Prof. Dr.Head of Institute