NANO MANIPULATION WITH RECTANGULAR CANTILEVER OF ATOMIC FORCE MICROSCOPE (AFM) IN A VIRTUAL REALITY ENVIRONMENT

One of the problems of working with AFM in nano environment is lack of simultaneous image feedback. For solving this problem, a virtual reality environment (VR) is designed. For this purpose, a nano manipulation environment is implemented and then, through examining and analyzing the forces existing between probe tips and nanoparticle, the process of nanoparticle driving is added to this environment. In the first step of nano manipulation operations, the dimensions of the base plan as well as the exact place of nanoparticles on that plan needs to be defined so that the user can identify the place of the origin and nanoparticles' destination. The second step in simulation is driving the nanoparticle. In this process, the AFM probe tip starts moving toward nanoparticle with a constant speed of V and after touching it and applying F resultant force from probe tip side on nano particles and increasing up to critical value (F ), it overcomes contract and frictional forces existing between the particle and base plane. In this moment, the probe tip starts moving along with nanoparticle and as a result the nanoparticle is transferred to the pre-determined place by the user. Thus the user may observe the manipulation process

Detection and real-time correction of faulty visual feedback in atomic force microscopy based nanorobotic manipulation

One of the main roadblocks to Atomic Force Microscope (AFM) based nanomanipulation is lack of real time visual feedback. Although the model based visual feedback can partly solve this problem, its unguaranteed reliability due to the inaccurate models in nano-environment still limits the efficiency of AFM based nanomanipulation. This paper introduce a Real-time Fault Detection and Correction (RFDC) method to improve the reliability of the visual feedback. By utilizing Kalman filter and local scan technologies, the RFDC method not only can real-time detect the fault display caused by the modeling error, but also can on-line correct it without interrupting manipulation. In this way, the visual feedback keeps consistent with the true environment changes during manipulation, which makes several operations being finished without a image scanning in between. The theoretical study and the implementation of the RFDC method are elaborated in this paper. Experiments of manipulating nano-particles have been carried out to demonstrate the effectiveness and efficiency of the proposed method. ©2008 IEEE.Link_to_subscribed_fulltex