Collective Hierarchical Systems:
Developing life-emulating technologies by exploiting the physics of far-from-equilibrium, self-assembling systems
What is it?
We want to establish the Physical, Chemical and Nano Sciences Center and Sandia National Laboratories as major players in developing the interdisciplinary science of complex, far-from-equilibrium, self-assembling systems. These are systems that self-assemble highly organized states dynamically, across multiple length scales, through the constant flow-through and consumption of energy and material. Such driven systems, in contrast to equilibrated systems, can, in special cases, develop the key capability of representing, maintaining and modifying information. Such systems also typically bridge multiple length scales by developing hierarchical organization, i.e., different physical mechanisms are harnessed to produce self-assembly at multiple length scales. Far-from-equilibrium systems are in a special subset of statistical mechanics that has been largely ignored until very recent times. At present, biological systems exhibit by far the widest range of complex far-from-equilibrium self-assembly behaviors. Our goal is both to develop an understanding of general hierarchical self-organization principles in existing biological systems, and to attempt to extend those principles to more robust hybrid and non-biological systems. Note that this effort is distinct from the study of systems that achieve order by "settling down" (approaching equilibrium) after energy sources are removed. Such systems are already an active area of research.
Why care?
In short, scientific and technological opportunities abound here.
- A breakthrough in understanding such systems may enable the development of revolutionary new classes of intelligent, life-emulating technologies. Self-assembling, self-monitoring and self-repairing machinery represent the ultimate goal.
- There may be very fundamental statistical physics principles "waiting for discovery" in these complex, far-from-equilibrium systems — principles that may also fundamentally impact how we look at information science and complex biological system science.
- Computational simulation capabilities and the exploding knowledge base for model biological systems make this the right time to do it.
What are we doing?
We are developing theoretical models and supporting the experimental study of far-from-equilibrium behaviors that underlie interesting dynamic self-assembly processes, using selected biological systems as a guide. We have theoretically demonstrated how to carry out arbitrary computations using certain dynamic self-assembly processes common in protein networks. We have recently identified a previously unappreciated role of programmed death in biological systems. We have also discovered how to control and manipulate the stochastic molecular processes associated with dynamic instability in microtubules and active transport of motor proteins to construct nanoscale and microscale structures. This part of the thrust is part of a larger Department of Energy Basic Energy Sciences project to exploit microtubule structural proteins and associated motor proteins for active assembly. Ultimately, we will develop more robust, artificial systems made entirely from non-biological components, and understand and develop the information processing capabilities of these systems. Our initial efforts in this direction are to develop self-assembling software systems.
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Lasers, Optics, and Remote Sensing Department