creating knowledge for future

High Quality

Scholarly Publishing
                CAREER NETWORK  
World's one of the largest Research
Career Network
  •     Academic & Industry jobs
  •     Project funding
  •     Visiting faculty positions
  •     Visiting scientist positions
  •     Invited talks
  •     and more...  
Register FREE  
  Journal of Nanoscience Letters 2012, 2: 16
  Research Article
High-speed probe-based nanofabrication via an iterative control approach for multi-axis precision tracking
  HaimingWang, Qingze Zou  
Mechanical and Aerospace Engineering Department, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
  Probe-based nanofabrication (PBN) has been demonstrated to have great potentials as an highly effective and versatile nanofabrication platform. PBN techniques, however, are currently limited by adverse effects that became more pronounced when the fabrication is at high-speed and over a relatively large operation range. These adverse effects include the nonlinear hysteresis, vibrational dynamics of piezoactuators, and the dynamics coupling in multi-axis motion. In this article, we present the utilization of the recently developed multi-axis inversion-based iterative control (MAIIC) technique to overcome these challenges in PBN. By using this advanced control technique, precision position control of the probe with respect to the sample substrate can be achieved during high-speed, large-range multi-axis nanofabrication. Particularly, the cross-axis dynamics coupling effect on the output tracking are compensated for. The proposed approach is illustrated through experiments by fabricating two Chinese characters pattern via mechanical scratching on a gold-coated silicon sample surface at high speed. The efficacy of the proposed technique is demonstrated through the experimental results that precision tracking in all 3-D axes can be achieved in the presence of pronounced cross-axis dynamics coupling effect.
  Probe-based nanofabrication; High speed; System-inversion; Iterative learning control; Cross-axis coupling compensation  

  © 2016 Cognizure