Atomic Force Microscope (AFM) Based Nanomanipulation
Nanoparticle positioning system using Atomic Force Microscopes (AFM)

Goal: Atomic force microscope (AFM) based nanomanipulation systems are very slow, not repeatable and imprecise since nanomanipulation operations are mostly conducted by a user's direct control. To increase the speed, reliability and precision of such systems, this task proposes an autonomous nanomanipulation method.

Approach: Spherical gold nanoparticles with 100 nm diameter are positioned mechanically on a flat mica substrate by contact manipulation by the AFM probe tip to a desired position autonomously. The most significant issue of the manipulation operation is the lack of real-time visual feedback. This issue is solved by developing a robust algorithm for particle center detection and using the AFM cantilever deflection (force) signals to detect contact losses in real-time and to repeat the manipulation again until the target location is reached. Using these solutions, the automated AFM manipulation system is developed and a statistical study on performance of the manipulation system is conducted. The most important contribution of this study is the contact loss algorithm that continuously tracks the real-time force feedback of the AFM probe that improves the control on the success and speed of each individual autonomous manipulation operation compared to the traditional, blind, push-and-look approach. The contact loss algorithm dramatically changes the reliability and speed of the system because if contact loss can be detected during manipulation, it is easier to detect errors in positioning and pushing operation.
In order to understand the physics behind the nanoparticle manipulation using a sharp probe, a system model is also created and the experiments are conducted to support the model.

Models: We apply contact mechanics theory to model the forces the probe and the particle experiences during manipulation in order to investigate the nanoparticle manipulation mechanism. This investigation involves an analysis of possible particle motion modes (rolling, spinning, and sliding) for pushing and pulling cases, according to applicable material properties and dimensions.

Benefits: Designing and implementing a fast and reliable technique for multiple particle manipulation would enable the use of an AFM for micro/nano-manufacturing applications, where the AFM would be inexpensive in comparison to most of the techniques and machines that are currently available for this purpose. We believe forming nanofabrication masks and templates for plasmonic, optoelectronic or MEMS/NEMS devices would be possible using these types of procedures. Manipulating nanoparticles into predefined positions could also potentially be used for gluing or soldering in the nanoscale. Furthermore, the models developed during this work can enhance our understanding of nanoscale interaction and physics behind nanomanipulation tasks.

Members: Onur Ozcan, Metin Sitti

Former Members: Cagdas Onal

Publications:

  • C. D. Onal, O. Ozcan, and M. Sitti, ''Automated Tip based 2-D Mechanical Assembly of Micro/Nanoparticles,'' Control from MEMS to Atoms, ed. by J. Gorman and B. Shapiro, 2011 (to appear).
  • C. Onal, O. Ozcan, and M. Sitti, ''Automated 2-D Nanoparticle Manipulation using Atomic Force Microscopy,'' IEEE Trans. on Nanotechnology, vol. 10, no.3, pp.472-481, 2011. DOI: 10.1109/TNANO.2010.2047510
  • C. D. Onal, O. Ozcan, and M. Sitti, ''Atomic Force Microscopy based Nanomanipulation Systems,'' Handbook of Nanophysics: Nanomedicine and Nanorobotics, ed. by K. D. Sattler, 2010.
  • C. D. Onal, O. Ozcan, and M. Sitti, ''Automated 2-D Nanoparticle Manipulation with an Atomic Force Microscope,'' IEEE Conf. on Robotics and Automation, Kobe, Japan, 2009. link

  • [Overall system structure of the automated nanoparticle manipulation setup.]

    [A flowchart description of the automated single nanoparticle manipulation algorithm.]

    [A flowchart description of the automated multiple nanoparticle manipulation algorithm.]

    [Automated manipulation of five nanoparticles to form a linear assembly. An initial image is taken and all particles are detected using a watershed algorithm. The target positions are given to the program by the user. A task planner decides which particle will be manipulated to which target position. A final image after the experiment is shown.]

    [Automated manipulation of six nanoparticles to form a pattern that cannot be formed with a distance based planner. An initial image is taken and all particles are detected using a watershed algorithm. Task planner decides which particle will be manipulated to which target position. A final image after the experiment is shown.]