Assembling nanoscale components to make functional devices remains a grand challenge despite rapid advances in imaging, measurement, and fabrication at the nanoscale. While manipulation techniques for nanocomponents are finally emerging they currently lack automation. The lack of automation seriously limits the rate at which new nanocomponent-based devices can be invented. In order to develop automated real-time planning algorithms, we need to develop a fundamental understanding of the interaction of nanocomponents with trapping fields. Understanding different ways in which components can interact with the trap requires dense sampling of the planning parameter space using millions of computationally intensive simulation runs. The proposed project will focus on (1) development of GPU-based simulation infrastructure for simulating trap and nanocomponent interactions, (2) development of algorithms for automatically constructing simplified assembly process models from simulation data, (3) development of visualization tools for enhancing the understanding of the nanoscale assembly processes, (4) identification and characterization of real-time motion planning strategies for nanoscale assembly processes, and (5) integration of the proposed the research results with education and wider dissemination.
The proposed work will lead to a reliable, efficient, and automated assembly process for fabricating nanocomponent-based devices. We expect that this assembly process will enable nanotechnology researchers to explore new design possibilities in the area of nano electronics, nano photonics, and bio-inspired sensors. Automated assembly capability will also allow them to explore a large number of design options in a cost effective manner and hence accelerate discovery and invention. The proposed research will significantly reduce the need for manual assembly operations and will make nanomanipulation significantly less labor-intensive thereby facilitating the manufacturing of nanodevices in a cost-competitive manner. The proposed project will also create training and education materials in the areas of GPU-based simulations, interactive visualization at nanoscale, automated model construction, and real-time motion planning.
