Autonomous Matter
AMOLF initiates and conducts fundamental research that leads to valuable insights and opportunities to create new functional materials and to find solutions to societal challenges. This translates into a research program that focuses on three highly interdisciplinary themes. One of these themes is Autonomous Matter.
What makes matter autonomous?
Autonomy can be defined as the ability to independently adapt, optimize, regenerate, and learn. Autonomous functionality is increasingly employed in man-made systems, but remains limited when compared to nature, where even the simplest cells exhibit autonomy in abundance. Within the Autonomous Matter department at AMOLF, we study autonomous functionality in an emerging class of systems at the intersection of chemistry, physics, biology, and engineering.
Principles of self-organization
Central to this new direction is a shift in thinking. Whereas engineering traditionally strives to maximize control through centralized architectures and functional separation, cells optimize robustness by integrating functions locally. Biology exploits the dynamic interplay between properties that are traditionally left unharnessed in man-made systems, like diffusing building blocks, energy consumption, force generation, mechanical instabilities, feedbacks, and growth balanced by targeted destruction.
How these phenomena are integrated to yield self-organized systems that are robust yet dynamic, presents a range of open questions. Moreover, embedding these traits within chemical and soft-matter systems promises a next generation of intelligent materials.
Aims and questions
Our overarching goals are to understand the principles of autonomy, and to create a new class of autonomous matter that performs complex functions in a self-organized fashion.
This research program builds on our core strengths in molecular and cellular biophysics, bio-inspired chemistry and robotics. Topics include:
- Out-of-equilibrium chemical reaction networks that exploit diffusion and feedback to generate spatial patterns
- The regulation of multi-protein complex assembly by the coordination between ribosomes (the molecular structures inside cells that make proteins)
- Self-learning in modular robotic systems that allows them to adapt to their environment
- The spatio-temporal dynamics of cells that underlie organoid formation and homeostasis (spatio-temporal: patterns in space and time)
- The spatio-temporal organization of receptor proteins that enables immune-cell recognition
Key research questions
Within these autonomous systems, we study the following questions:
An important feature of autonomous matter is its capacity to adaptively assemble and disassemble, and hence repeatedly form and destruct structures, enabled by the dynamic displacements of its building blocks.
This process is associated with a host of questions:
- Can we control assembly by local cues or energy-driven processes?
- Can 2D confinement or signaling enable new forms of self-organization?
- Can the shape of a material be used to create new types of catalysis?
- Can we evolve robotic swarming, where large numbers of simple robots work together to achieve complex tasks?
- Can we evolve reactive assembly networks, enabling simple building blocks to self-organize into functional materials?
- Can we define and manipulate shape landscapes (the set of shapes a material can adopt and transition between)?
The ability to self-organize in space and time is a crucial feature of autonomous systems, enabled by the interplay of assembly and disassembly with other phenomena in systems ranging from protein-membrane hybrids to soft robots.
Spatial self-organization gives rise to a range of questions:
- What is the role of molecular gradients in spatial cellular organization, and can we exploit them in chemical reactions?
- How can the exchange of signals enable other forms of spatio-temporal organization?
- Which possibilities are opened up by energy-powered movement?
- What can be achieved by entropic and other passive effects?
A next level of control in autonomous systems is the ability to program self-organized behavior, which may for instance be achieved in biological systems at the DNA level and in robotic systems at the algorithmic level.
Key questions are:
- Can we achieve programmability in actuated metamaterials (engineered materials that change shape or behavior in response to stimuli)?
- How do immune cells use spatial protein patterning to achieve specificity for many targets (spatial protein patterning: how proteins are organized across the cell surface)?
- Can we use DNA sequence specificity as a basis for programmable adaptive materials?
- Can we uncover the role of dynamic cellular movements in developmental programs?
Most recent publications
Contact
Do you have questions about the Autonomous Matter research program? Then please contact Sander Tans at S.Tans@amolf.nl.