Doctor of Philosophy, The Ohio State University, 2020, Mechanical Engineering
Major advances in DNA nanofabrication by the self-assembly process have occurred over the last decade to construct nano-devices for many applications of science and technology. However, advances in design methodology as well as advanced computational design tools have lagged behind, including computer-aided design (CAD) and coarse-grained models. Currently, for the majority of research in DNA nanotechnology, the design process is carried out using a bottom-up manual approach, which requires expertise and limits complexity. Recently developed top-down automated approaches that are limited to select types of static geometries, sacrificing the design flexibility for various applications. In addition, the integration between CAD and coarse-grained models require extra steps and limits the realization of virtual iterative design for engineering DNA assemblies in a robust manner.
Here, we establish a versatile CAD tool that integrates top-down design automation with bottom-up control of component geometry and connectivity to build DNA nanomachines with various geometries (solid, shell, wireframe, or combinations), selected mobility (static, 1D, 2D, or 3D motion), large size via multi-structure assemblies. Based on this custom CAD tool, MagicDNA, we proposed a closed-loop integrated framework with MagicDNA and coarse-grained models, which enables the product design pipeline similar to macroscopic engineering (CAD and CAE) into nanoscale DNA assemblies for evaluating design parameters, rapid prototyping and eventually a robust design for experimental characterization and applications. Several structures were further fabricated to validate not only the target geometry but also the motion pathway, which in all cases generally agreed with simulation results. For these nanomachines, thermal fluctuation plays an important role to affect the component geometry and was quantified with hybrid coarse-grained models and kinematic variance analysis to predict the performance of the (open full item for complete abstract)
Committee: Hai-Jun Su (Advisor); Carlos Castro (Advisor); Shen Herman (Committee Member); Cho Hanna (Committee Member)
Subjects: Engineering; Nanoscience; Nanotechnology