Virtual Tooling for Nanoassembly and Nanomanipulations
Atomic force microscopy (AFM) (Binning et al., Phys Rev Lett 56:930–933, 1986) has been used as a nanomanipulation tool recently because it not only has high resolution scanning ability but also can be controlled as an end-effector in the nanoenvironment (Junno et al., Appl Phys Lett 66:3627–3629, 1995). There are several challenging problems including controller design with relatively large thermal drift and other uncertainties, real-time positioning and manipulation control with sensor feedback, and nanosensing and manipulation planning. In the last decade, many researchers are working on these problems and some methods have been proposed that solved these problems partially (Chen et al., IEEE Trans Autom Sci Eng 3:208–217, 2006; Li et al., IEEE Trans Nanotechnol 4:605–614, 2005; Resch et al., Langmuir 14:6613–6616, 1998; Hansen et al., Nanotechnology 9:337–342, 1998; Sitti, IEEE ASME Trans Mechatron 9:343–348, 2004). However, the problem caused by single tip interaction is still hindering its efficiency especially in handling nanoparticles/nano-objects to form patterns or nanostructures.
Tools are usually designed and used for object handling or other tasks especially for having higher efficiency and accuracy or coping with various uncertainties on task performing. We proposed a concept of virtual nanohand which mimicking multi-fingered hand and controlling an AFM tip to form a virtual tool for achieving stable nano manipulation and nanoassembly. The nanohand strategy is implemented by moving the AFM tip to a set of predefined trajectories in relative high frequency. It allows us easily to design and apply various virtual tools for coping with requirements in nanomanipulation. This virtual tooling strategy is a solution with good potential on realizing high efficiency nanoassembly and nanomanipulation.
KeywordsAtomic Force Microscopy Position Error Viscous Friction Particle Center Instant Center
- 3.Makaliwe JH, Requicha AA (2001) Automatic planning of nanoparticle assembly tasks. In: Proceedings of the 2001 IEEE international symposium on assembly and task planning (ISATP2001), pp 288–293Google Scholar
- 8.Wang ZD, Hirata Y, Kosuge K (2003) Control multiple mobile robots for object caging and manipulation. In: Proceedings of the 2003 IEEE/RSJ international conference on intelligent robots and systems, pp 1751–1756Google Scholar
- 9.Hou J, Wang ZD, Liu LQ, Yang YL, Dong ZL, Wu CD (2010) Modeling and analyzing nano-particle pushing with an AFM by using nano-hand strategy. In: Proceedings of the 2010 5th IEEE international conference on nano/micro engineered and molecular systems NEMS, pp 518–523.Google Scholar
- 10.Hou J, Wu CD, Liu LQ, Wang ZD, Dong ZL (2010) Modeling and analyzing nano-rod pushing with an AFM. In: Proceedings of the 10th IEEE conference on nanotechnology IEEE-NANO 2010, pp 329–334Google Scholar
- 13.Tafazzoli A, Sitti M (2004) Dynamic behavior and simulation of nanoparticle sliding during nanoprobe-based positioning. In: Proceedings of the IMECE’04 2004 ASME international mechanical engineering congress, pp 1–8Google Scholar