All nanoscale devices are subject to random diffusive forces that lead to slow, uncontrollable transport of materials and information. Synthetic nanoscale systems designed for computational and self-assembly tasks, require more precise control over energy- and information-carrying molecules. Such systems include nanoscale devices currently being developed for delivery of diagnostic logic circuits to cells, querying the state of health of specific cells or subcellular structures, and conditional release of therapeutic cargo molecules. Ideally, such systems could employ programmable synthetic molecular motors to ferry information and materials in directed motion over a complex network of tracks, analogous to natural molecular motors in living cells, thus enabling behaviors otherwise not possible in a purely diffusion-driven environment. In this project computational models, simulation algorithms, and data visualization tools will be developed that will help synthetic chemists build the next generation of nanoscale walker systems. In the project, students at all levels (high-school to postdoctoral) will be trained in interdisciplinary research. High-school students will be engaged on the project through already established, tracked science involvement programs that emphasize participation of traditionally underrepresented groups. In the context of the project, a regular seminar will be developed on nanoscale technology, molecular computing, and molecular robotics within the biomedical engineering degree program, to educate future generations of students (undergraduate and graduate) in this emerging field of science.
Previous work has shown that simple DNA-enzyme driven synthetic walkers can move superdiffusively along nanoscale tracks, and can do mechanical work. In this project more advanced walker designs with large, complex body shapes and heterogeneity in their interactions with other walkers and molecules in their environment will be modeled and simulated. This class of structured walker scaffolds will exhibit modes of motion not available in symmetrical walkers, e.g., rotational persistence, orientation-aware sorting, chiral walker-walker and walker-track interactions. These features will be used to break symmetries in the walker's local environment, leading to stronger directional biases and more efficient directional transport.
The goal of the project is to understand the algorithmic basis of how a walker's shape and structure affect its motion, and how these features can be composed, modularly, into larger nanoscale transportation systems with programmable control, to achieve directed transport even under the randomizing and disorienting influence of Brownian motion. The models developed will enable more complex nano systems to be engineered to take advantage of programmable nanoscale transport.
The approach taken in the project is computational. Walker motion is treated as a continuous-time Markov process, at a level of abstraction that balances physical detail and computational tractability. A hierarchy of Monte Carlo simulations will be developed to approximate physical and chemical processes at the appropriate relative scales, while maintaining computational tractability.