Piezoresponse force microscopy (PFM) is an atomic force microscopy-based approach utilized for measuring local properties of piezoelectric materials. The objective of this study is to propose a practical framework for simultaneous estimation of the local stiffness and piezoelectric properties of materials. For this, the governing equation of motion of a vertical PFM is derived at a given point on the sample. Using the expansion theorem, the governing ordinary differential equations of the system and their state-space representation are derived under applied external voltage. For the proof of the concept, the results obtained from both frequency and step responses of a PFM experiment are utilized to simultaneously identify the microcantilever parameters along with local spring constant and piezoelectric coefficient of a periodically poled lithium niobate sample. In this regard, a new parameter estimation strategy is developed for modal identification of system parameters under general frequency response. Results indicate good agreements between the identified model and the experimental data using the proposed modeling and identification framework. This method can be particularly applied for accurate characterization of mechanical and piezoelectric properties of biological species and cells.
Skip Nav Destination
e-mail: jalili@clemson.edu
Article navigation
November 2009
Dynamic Modeling Control And Manipulation At The Nanoscale
Modeling Piezoresponse Force Microscopy for Low-Dimensional Material Characterization: Theory and Experiment
Amin Salehi-Khojin,
Amin Salehi-Khojin
Department of Mechanical Engineering, Smart Structures and Nanoelectromechanical Systems Laboratory,
Clemson University
, Clemson, SC 29634
Search for other works by this author on:
Saeid Bashash,
Saeid Bashash
Department of Mechanical Engineering, Smart Structures and Nanoelectromechanical Systems Laboratory,
Clemson University
, Clemson, SC 29634
Search for other works by this author on:
Nader Jalili,
Nader Jalili
Associate Professor
Department of Mechanical Engineering, Smart Structures and Nanoelectromechanical Systems Laboratory,
e-mail: jalili@clemson.edu
Clemson University
, Clemson, SC 29634
Search for other works by this author on:
Gary Lee Thompson,
Gary Lee Thompson
Department of Bioengineering,
Clemson University
, Clemson, SC 29634
Search for other works by this author on:
Alexey Vertegel
Alexey Vertegel
Department of Bioengineering,
Clemson University
, Clemson, SC 29634
Search for other works by this author on:
Amin Salehi-Khojin
Department of Mechanical Engineering, Smart Structures and Nanoelectromechanical Systems Laboratory,
Clemson University
, Clemson, SC 29634
Saeid Bashash
Department of Mechanical Engineering, Smart Structures and Nanoelectromechanical Systems Laboratory,
Clemson University
, Clemson, SC 29634
Nader Jalili
Associate Professor
Department of Mechanical Engineering, Smart Structures and Nanoelectromechanical Systems Laboratory,
Clemson University
, Clemson, SC 29634e-mail: jalili@clemson.edu
Gary Lee Thompson
Department of Bioengineering,
Clemson University
, Clemson, SC 29634
Alexey Vertegel
Department of Bioengineering,
Clemson University
, Clemson, SC 29634J. Dyn. Sys., Meas., Control. Nov 2009, 131(6): 061107 (7 pages)
Published Online: November 6, 2009
Article history
Received:
June 13, 2008
Revised:
July 20, 2009
Online:
November 6, 2009
Published:
November 6, 2009
Citation
Salehi-Khojin, A., Bashash, S., Jalili, N., Thompson, G. L., and Vertegel, A. (November 6, 2009). "Modeling Piezoresponse Force Microscopy for Low-Dimensional Material Characterization: Theory and Experiment." ASME. J. Dyn. Sys., Meas., Control. November 2009; 131(6): 061107. https://doi.org/10.1115/1.4000161
Download citation file:
Get Email Alerts
Cited By
Offline and Online Exergy-Based Strategies for Hybrid Electric Vehicles
J. Dyn. Sys., Meas., Control (May 2025)
Multi Combustor Turbine Engine Acceleration Process Control Law Design
J. Dyn. Sys., Meas., Control
A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach
J. Dyn. Sys., Meas., Control (May 2025)
Active Data-Enabled Robot Learning of Elastic Workpiece Interactions
J. Dyn. Sys., Meas., Control (May 2025)
Related Articles
DMCMN: Experimental/Analytical Evaluation of the Effect of Tip Mass on Atomic Force Microscope Cantilever Calibration
J. Dyn. Sys., Meas., Control (November,2009)
Application of a Fast-Stabilizing Frequency Domain Parameter Estimation Method
J. Dyn. Sys., Meas., Control (December,2001)
Modeling and Analysis of Piezoelectric Energy Harvesting Beams Using the Dynamic Stiffness and Analytical Modal Analysis Methods
J. Vib. Acoust (February,2011)
Stochastic System Identification for Operational Modal Analysis: A Review
J. Dyn. Sys., Meas., Control (December,2001)
Related Proceedings Papers
Related Chapters
Layer Arrangement Impact on the Electromechanical Performance of a Five-Layer Multifunctional Smart Sandwich Plate
Advanced Multifunctional Lightweight Aerostructures: Design, Development, and Implementation
Elastic Constants of Isotropic and Orthotropic Composite Materials from Plate Vibration Test Data
Eleventh Volume: Composite Materials—Testing and Design
Structural Damage Detection by Integrating Neural Networks and Vibration Modal Analysis
International Conference on Computer and Automation Engineering, 4th (ICCAE 2012)