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Model-based topography estimation in trolling mode atomic force microscopy

Seifnejad Haghighi, M ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1016/j.apm.2019.08.014
  3. Publisher: Elsevier Inc , 2020
  4. Abstract:
  5. In this study, a novel approach based on a modified Kalman filter algorithm is presented to directly estimate and measure the surface topography of samples by trolling mode atomic force microscopy. Trolling mode atomic force microscopy was introduced as an atomic force microscopy alternative to overcome imaging problems in liquid environments by reducing the liquid-resonator interaction forces. In conventional imaging techniques, the time to reach the steady state periodic motion of the oscillating probe restricts scanning speed. To overcome this limitation, we propose a novel imaging technique for trolling mode atomic force microscopy based on the system dynamics model and using the adaptive fading Kalman filter with forgetting factor. In this approach, the sample height is estimated directly without the need for any closed loop controller. As a result, the scanning speed is improved significantly, and topography is obtained more accurately compared to the conventional imaging method. Moreover, the effects of process noise, scanning speed, and parameter uncertainties on the performance of proposed approach are investigated. © 2019 Elsevier Inc
  6. Keywords:
  7. Adaptive fading extended Kalman filter ; Forgetting factor ; Trolling mode atomic force microscopy ; Adaptive filtering ; Atomic force microscopy ; Imaging techniques ; Scanning ; Topography ; Closed loop controllers ; Conventional imaging ; Forgetting factors ; Kalman filter algorithms ; Novel imaging techniques ; Parameter uncertainty ; System dynamics model ; Topography estimation ; Kalman filters
  8. Source: Applied Mathematical Modelling ; Volume 77 , 2020 , Pages 1025-1040
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0307904X19305025