TY - GEN
T1 - Kalman Filter Based Estimation of Surface Conductivity in STM
AU - Mishra, Richa
AU - Nikooienejad, Nastaran
AU - Reza Moheimani, S. O.
AU - Petersen, Ian R.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In scanning tunneling microscopy (STM), the surface conductivity, σ, contributes to the total tunneling current due to a quantum phenomenon. The surface conductivity may change from atom to atom during a scan. It is an important electronic property of the surface that cannot be directly measured with current spectroscopy methods. In this paper, we propose an offline estimation method based on augmented state Kalman filter to determine σ. We demonstrate the successful application of this method to a set of STM images obtained from a Si (100)-2× 1:H passivated surface.
AB - In scanning tunneling microscopy (STM), the surface conductivity, σ, contributes to the total tunneling current due to a quantum phenomenon. The surface conductivity may change from atom to atom during a scan. It is an important electronic property of the surface that cannot be directly measured with current spectroscopy methods. In this paper, we propose an offline estimation method based on augmented state Kalman filter to determine σ. We demonstrate the successful application of this method to a set of STM images obtained from a Si (100)-2× 1:H passivated surface.
UR - https://www.scopus.com/pages/publications/85144598733
U2 - 10.1109/CCTA49430.2022.9966003
DO - 10.1109/CCTA49430.2022.9966003
M3 - Conference Paper
T3 - 2022 IEEE Conference on Control Technology and Applications, CCTA 2022
SP - 950
EP - 955
BT - 2022 IEEE Conference on Control Technology and Applications, CCTA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Conference on Control Technology and Applications, CCTA 2022
Y2 - 23 August 2022 through 25 August 2022
ER -