Masters Theses

Abstract

"Atomic Force Microscopy is one of the most powerful tools for imaging, measuring and manipulating materials at nanometer scale. Among different modes of AFM, tapping mode, in which the oscillating tip touches the sample periodically, is most common mode. During the tip approach and retract, the tip interacts with sample and experiences different force regimes. This tip-sample interaction force contains information about the sample topology, material properties and tip geometry. However, quantitative measurement of the time-varying tip-sample interaction forcing function is challenging in the tapping mode because of the combined dynamic complexities of the cantilever and nonlinear complexity of the tip-sample force.

In first part of this research, an initial investigation of a neural-network approach to tip-sample interaction force estimation is studied. The tip-sample interaction is treated as an unknown force and a neural-network is used in a dynamic observer framework to approximate the unknown forcing function. Simulations are used to demonstrate plausibility of the approach and accuracy of the force model is evaluated for several scenarios.

In second part, an approach based on repetitive control is used to design a filter for execrating tip-sample force signal from noisy tip displacement measurements. Design of the filter parts and their parameters are explained and effect of each parameter on force estimation performance is discussed using simulations. Improvement in filter performance by using torsional harmonic cantilevers as the sensor is demonstrated"--Abstract, page iv.

Advisor(s)

Bristow, Douglas A.

Committee Member(s)

Balakrishnan, S. N.
Landers, Robert G.

Department(s)

Mechanical and Aerospace Engineering

Degree Name

M.S. in Mechanical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Summer 2015

Journal article titles appearing in thesis/dissertation

  • Estimation of tip-sample interaction in tapping mode AFM using neural-network approach
  • Estimation of tip-sample force signal in tapping mode AFM using a repetitive control based filter

Pagination

x, 58 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2015 Alireza Toghraee, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11363

Electronic OCLC #

1041856529

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