Sensitivity analysis of nanoparticles pushing manipulation by AFM in a robust controlled process

Abstract This paper investigates the sensitivity of nanoparticle parameters in a robust controlled process, by a compatible nanomanipulation model consisting of all effective phenomena in nanoscale. The dynamic model of nanoparticle displacement utilizes the Lund–Grenoble (LuGre) friction model, since it demonstrates pre-slip displacement, friction delay, various forces of failure and the stick-slip movement, with respect to other presented models. Also, the interaction force between nanoparticle and AFM cantilever tip are modeled by using the Derjaguin model. Sliding mode control (SMC) approach is used to provide the desired substrate motion trajectory, despite the challenges in the piezoelectric substrate motion control, consisting of thermal drift, hysteresis, and other uncertainties. In this paper, the dynamic model of nanoparticle manipulation is expressed to determine the nanoparticle behavior for substrate movement with desired trajectory and the effect of pre-process selections of the result of the manipulation. Depending on obtained diagrams for parameters sensitivity, the prediction of manipulation result is more precise, and also this is effective on choosing of proper initial condition and parameter selection in pushing purposes. Finally, it can be used to adjust proper pushing time and input for an accurate and successful pushing and assembly. It also provides a real-time visualization during micro/nanomanipulation and increases complexity of the resulting created structures.

[1]  J. Sader,et al.  In-plane deformation of cantilever plates with applications to lateral force microscopy , 2004 .

[2]  Fathi H. Ghorbel,et al.  Nanoscale Friction Dynamic Modeling , 2009 .

[3]  James B. Dabney,et al.  An AFM-Based Nanomanipulation Model Describing the Atomic Two Dimensional Stick-Slip Behavior , 2007 .

[4]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[5]  F. Thau.  Observing the state of non-linear dynamic systems† , 1973 .

[6]  Bharat Bhushan,et al.  Multiscale friction mechanisms and hierarchical surfaces in nano- and bio-tribology , 2007 .

[7]  Aristides A. G. Requicha,et al.  Drift compensation for automatic nanomanipulation with scanning probe microscopes , 2006, IEEE Transactions on Automation Science and Engineering.

[8]  T. Low,et al.  Modeling of a three-layer piezoelectric bimorph beam with hysteresis , 1995 .

[9]  James B. Dabney,et al.  Nanomanipulation modeling and simulation , 2006 .

[10]  Georg Schitter,et al.  Tuning the interaction forces in tapping mode atomic force microscopy , 2003 .

[11]  Moharam Habibnejad Korayem,et al.  Sensitivity analysis of nanoparticles pushing critical conditions in 2-D controlled nanomanipulation based on AFM , 2009 .

[12]  J. Neumeister,et al.  Lateral, normal, and longitudinal spring constants of atomic force microscopy cantilevers , 1994 .

[13]  W. Arnold,et al.  High-frequency response of atomic-force microscope cantilevers , 1997 .

[14]  S. H. Mahboobi,et al.  DYNAMICS MODELING OF NANOPARTICLE IN AFM-BASED MANIPULATION USING TWO NANOSCALE FRICTION MODELS , 2009 .

[15]  H. Hashimoto,et al.  Controlled pushing of nanoparticles: modeling and experiments , 2000 .

[16]  Bijan Shirinzadeh,et al.  Robust Adaptive Constrained Motion Tracking Control of Piezo-Actuated Flexure-Based Mechanisms for Micro/Nano Manipulation , 2011, IEEE Transactions on Industrial Electronics.

[17]  R. Superfine,et al.  Nanometre-scale rolling and sliding of carbon nanotubes , 1999, Nature.