The science of computing and information processing is rapidly proliferating within established disciplines that at first glance appear unrelated. Examples include biochemistry and biology through the areas of bioinformatics and algorithmic molecular assembly, or physics, through quantum computing. Current top-down photolithographic methods of electronic component construction are likely to encounter severe barriers as miniaturization requires features at very small sizes. An alternative approach to such construction is programmable bottom-up assembly on the molecular scale. The most popular basis for bottom-up assembly is DNA self-assembly, because DNA contains information through which assembly can be controlled in a variety of ways. This approach has been explored by a variety of laboratories in recent years, but was pioneered by the PI Seeman's laboratory roughly thirty years ago. Robust DNA motifs can be self-assembled into objects, lattices and devices, using the information content inherent in the DNA molecules (or their analogs) themselves. Notable milestones include the self-assembly of DNA polyhedra, the self-assembly of 2D DNA periodic lattices, the self-assembly of high-resolution 3D DNA crystals, the development of clocked and autonomous cascade-like DNA walkers, the development of DNA origami, and the construction of 1D and 2D algorithmic assemblies.

This project aims to combine several of these developments to produce robust aperiodic structures that will enable nano-scale construction of computational machinery. The goal of the project is to introduce a new paradigm in the self-assembly of nano-scale devices by DNA self-assembly: active (rather than passive) recursion-based assembly of aperiodic structures. The project will incorporate elements of DNA walkers into DNA origami-based tiles as signals that guide hierarchical active assembly of aperiodic arrays.

The proposed hierarchical algorithmic assembly would be the first demonstration of recursion in molecular self-assembly that can be seen as a physical incarnation of programmed recursion. It is known that self-similar and fractal-like structures have advantages in material design, heat exchange and information processing, e.g., the very significant advances obtained by miniature fractal-like antennas. Consequently, the possibilities for self-similar arrangements at the nano-scale can be expected to advance further the design of materials and electronics, while decreasing the costs involved in their construction.

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New York University
New York
United States
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