Automated 2-D Nanoparticle Manipulation Using Atomic Force Microscopy

Önal, Çağdaş D.; Özcan, Onur; Sitti, Metin

doi:10.1109/tnano.2010.2047510

Cited by 47 publications

(22 citation statements)

References 27 publications

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“…The drawbacks of manipulation with the tip contacting the surface are discussed in [10] and therefore this is not discussed further in this paper. Also, as a well-recognized problem, thermal drift has been extensively researched in the literature [17][18] and thus is assumed to be compensated for along the manipulation process.…”

Section: Dynamic Model Of Manipulationmentioning

confidence: 99%

“…Furthermore, various motion modes, including sliding, rolling and spinning ,have been investigated in [10], and only the sliding mode is reported to most likely happen in a pushing manipulation task. Next, interactive forces are presented and a dynamic model to assist controller design is introduced.…”

Section: Dynamic Model Of Manipulationmentioning

confidence: 99%

“…Firstly, the interaction forces between the SPM tip, particle and substrate after the tip contacts the particle are shown in Figure 1 [10]. In this work, the SPM tip apex is assumed to be a spherical ball with radius t R and the particle radius is denoted as p R .…”

Section: Interaction Forcesmentioning

confidence: 99%

“…Moreover, the forces acting on that scale usually cannot be measured directly. Although extensive studies have been conducted to analyse the adhesive forces between SPM tip, manipulated object and substrate [8][9][10] in mechanical pushing procedures, an accurate mathematical model with exact expression of the forcesto assist control design for manipulation is still unavailable. Furthermore, some comprehensive beam models have been introduced in the literature [11] by considering the shear deformation and rotary inertia representing the system response in a more highly structured fashion, but they are too difficult for real-time control implementation particularly when augmented with the ever-present nonlinear interaction force [12].…”

Section: Introductionmentioning

confidence: 99%

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Automated Manipulation of Micro-Nano Objects with SPM by Using L₁ Adaptive Controller

Yang

Luo

Cao

et al. 2012

International Journal of Advanced Robotic Systems

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In this paper, a novel control methodology for automatically manipulating micro/nano particles by using a Scanning Probe Microscope (SPM) is presented. First of all, a mathematical model of micro/nanomanipulation, including the interactive forces and dynamics between the tip, particle and substrate along with the roughness effect of the substrate, is described. Then, the L1 adaptive control design for the manipulation system of micro/nano objects is presented, which consists of a state predictor with fast adaptation, a piece-wise continuous adaptive law and a low-pass filtered control design. This control framework can handle nonlinear uncertainties and ensures uniformly bounded tracking performance. The tracking performance bound can be systematically improved by reducing the step size of integration. Rigorous mathematical proof is provided. Simulation results demonstrate the effectiveness of the presented L1 adaptive control law on the micro/nanomanipulation model.

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Section: Dynamic Model Of Manipulationmentioning

confidence: 99%

Section: Dynamic Model Of Manipulationmentioning

confidence: 99%

Section: Interaction Forcesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automated Manipulation of Micro-Nano Objects with SPM by Using L₁ Adaptive Controller

Yang

Luo

Cao

et al. 2012

International Journal of Advanced Robotic Systems

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“…At the same time, the AFM-based manipulation method is furtherly studied [5]. The force feedback-based manipulation is proposed on the manipulation model [6], [7]. For promoting nanomanipulation efficiency, the double tip model is put forward in [8].…”

mentioning

confidence: 99%

Stochastic Approach for Feature-Based Tip Localization and Planning in Nanomanipulations

Yuan

Wang

Liu

et al. 2017

IEEE Trans. Automat. Sci. Eng.

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Abstract-In atomic force microscopy (AFM)-based nanomanipulation, the tip position uncertainties still exist due to the parameter inaccuracies in the open-loop compensation of the piezo scanner, the noise in the closed-loop control and thermal drift. These spatial uncertainties are very challenging to be directly estimated owing to the lack of real-time feedback, and its effects are more significant in performing an automatic nanomanipulation/assembly task than macro world manipulations. In this paper, we propose a stochastic framework for feature-based localization and planning in nanomanipulations to cope with these uncertainties. In the proposed framework, some features in the sample surface are identified to calculate their positions in statistics, and detected by using the AFM tip as the sensor itself through a local scan-based motion. In the localization, the Kalman filter is used through incorporating the tip motion model and the local scan-based observation model to estimate the on-line tip position in the task space. The simulation and experiments about tip positioning are carried out to illustrate the validity and feasibility of the proposed algorithm. Then, positioning tip for effective nanomanipulation is presented by using several experiments. Finally, a carbon nanotube is followed to show that the proposed method can provide a great potential for improving the position accuracy.Note to Practitioners-Atomic force microscopy (AFM)-based nanomanipulation has become a promising approach in developing devices and structures at nanoscale. One of the prerequisites for the effective and successful nanomanipulation is that the AFM tip position relative to the interest region can be con- Index Terms-AFM-based nanomanipulation, AFM tip localization, feature-based localization, Kalman filter.

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Introduction

Xie¹,

Önal²,

Régnier³

et al. 2011

Springer Tracts in Advanced Robotics

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Automated 2-D Nanoparticle Manipulation Using Atomic Force Microscopy

Cited by 47 publications

References 27 publications

Automated Manipulation of Micro-Nano Objects with SPM by Using L₁ Adaptive Controller

Automated Manipulation of Micro-Nano Objects with SPM by Using L₁ Adaptive Controller

Stochastic Approach for Feature-Based Tip Localization and Planning in Nanomanipulations

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Automated 2-D Nanoparticle Manipulation Using Atomic Force Microscopy

Cited by 47 publications

References 27 publications

Automated Manipulation of Micro-Nano Objects with SPM by Using L1 Adaptive Controller

Automated Manipulation of Micro-Nano Objects with SPM by Using L1 Adaptive Controller

Stochastic Approach for Feature-Based Tip Localization and Planning in Nanomanipulations

Introduction

Contact Info

Product

Resources

About

Automated Manipulation of Micro-Nano Objects with SPM by Using L₁ Adaptive Controller

Automated Manipulation of Micro-Nano Objects with SPM by Using L₁ Adaptive Controller