Motion Control, Planning and Manipulation of Nanowires Under Electric-Fields in Fluid Suspensio

Automated manipulation of nanowires and nanotubes would enable the scalable manufacturing of nanodevices for a variety of applications. However, two fundamental challenges still remain: (i) placement of nanostructures such as nanowires or nanotubes in precise locations, and (ii) automated scalable characterization, manipulation and assembly of nanostructures into nanodevices. Overcoming these challenges could enable further potential capacities of assembling and manufacturing functional nanodevices. In this dissertation, we present an electric-field-based automated system to motion plan and control of individual and simultaneous multiple nanowires in liquid suspension with a simple, generic set of electrodes. The proposed robust motion control has been proved to be stable, and various motion planning algorithms significantly reduce the computational complexity while maintaining sub-optimal performance. Extensive experimental results confirm the analysis and the design of the nanowire motion control, planning and manipulation scheme. Finally, we propose a fully automated procedure of solution based online characterization, manipulation, and assembly of nanowires. Proof-of-concept silicon nanowire field-effect transistors (FETs) with selected electrical conductivities are fabricated and assembled using the proposed procedure. The device testing results confirm the feasibility and effectiveness of the intergraded scheme.;In order to address those fundamental challenges, in the first part of this dissertation, we summarize the lowest-order electric field induced forces acting on a particle in suspension and present a dynamic model of nanowires under electrophoretic force. We then propose a micro-fluidic device design that is actuated by a simple, scalable and generic set of electrodes to precisely generate controllable electric fields. With symmetric properties of the designed electrode arrays, a superposition approach is developed to efficiently compute electric-field distribution on the micro-fluidic device.;With the proper approach to actuate the motion of nanoparticles, in the second part, we propose a novel electric-field-based single-nanowire motion planning and control scheme. A vision-based motion control of nanowire in dilute suspension is designed to precisely control the motion of individual nanowires using the independently controlled electrode arrays. The motion planning of a nanowire from one position to the target location is NP-hard due to the nature of combinatorial optimization. Two heuristic algorithms are presented to generate sub-optimal motion trajectory. In addition, we demonstrate a single, integrated process to position, orient and deposit multiple nanowires sequentially onto the substrate of the microfluidic device.;In order to facilitate the manipulation and assembly, we introduce motion-planning and control algorithms for simultaneously steering multiple nanowires in the third part of the dissertation. A motion-control algorithm is presented to simultaneously steer multiple nanowires along different desired trajectories under controlled electrophoretic forces. We provide the control-system properties that capture the relationship between the maximum number of the simultaneously controllable nanowires and the given number of actuated electrodes. A two-stage motion-planning algorithm is then presented to generate the desired trajectories for multiple nanowires with minimum total traveling distances. We demonstrate the simultaneous motion control and planning of multiple nanowires to form various geometric patterns and track different trajectories. However, the shortest distance trajectories do not result in the fastest manipulation. To improve the efficiency of the simultaneous manipulation and assembly of nanowires, we present online time-optimal motion-planning and control algorithms for effectively steering multiple nanowires simultaneously in liquid suspension. The motion planner, called SRRT*, is an improved sparse structure Rapidly-exploring Random Tree Star (RRT*)-based motion-planning algorithm. The SRRT* guarantees the asymptotically near time-optimal trajectories of multiple nanowires. Moreover, unlike the two-stage algorithm, the maximum number of nanowires that can be simultaneously controlled is not restricted explicitly. All of the above-mentioned motion control and planning strategies are validated through extensive experiments and simulations.;In the last part of the dissertation, we propose an integrated procedure of online automated characterization, manipulation, and assembly of nanowires to build functional nanodevices. Particularly, we separate and assemble silicon nanowires according to their electrical conductivities into FETs. The characteristic measurements of the FETs confirm the feasibility and effectiveness of the integrated characterization, manipulation and assembly procedure. The discussion of future research directions is also included at the end of the dissertation.