Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates

Scanning, Nov 2017

We present an image postprocessing framework for Scanning Tunneling Microscope (STM) to reduce the strong spurious oscillations and scan line noise at fast scan rates and preserve the features, allowing an order of magnitude increase in the scan rate without upgrading the hardware. The proposed method consists of two steps for large scale images and four steps for atomic scale images. For large scale images, we first apply for each line an image registration method to align the forward and backward scans of the same line. In the second step we apply a “rubber band” model which is solved by a novel Constrained Adaptive and Iterative Filtering Algorithm (CIAFA). The numerical results on measurement from copper(111) surface indicate the processed images are comparable in accuracy to data obtained with a slow scan rate, but are free of the scan drift error commonly seen in slow scan data. For atomic scale images, an additional first step to remove line-by-line strong background fluctuations and a fourth step of replacing the postprocessed image by its ranking map as the final atomic resolution image are required. The resulting image restores the lattice image that is nearly undetectable in the original fast scan data.

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Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates

Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates Hao Zhang,1 Xianqi Li,1 Yunmei Chen,1 Jewook Park,2,3 An-Ping Li,2 and X.-G. Zhang4 1Department of Mathematics, University of Florida, Gainesville, FL 32611, USA 2Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6487, USA 3Center for Artificial Low Dimensional Electronic Systems, Institute for Basic Science (IBS), Pohang 37673, Republic of Korea 4Department of Physics and the Quantum Theory Project, University of Florida, Gainesville, FL 32611, USA Correspondence should be addressed to X.-G. Zhang; ude.lfu@zgx Received 23 June 2017; Accepted 30 October 2017; Published 20 November 2017 Academic Editor: Ying Zhao Copyright © 2017 Hao Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract We present an image postprocessing framework for Scanning Tunneling Microscope (STM) to reduce the strong spurious oscillations and scan line noise at fast scan rates and preserve the features, allowing an order of magnitude increase in the scan rate without upgrading the hardware. The proposed method consists of two steps for large scale images and four steps for atomic scale images. For large scale images, we first apply for each line an image registration method to align the forward and backward scans of the same line. In the second step we apply a “rubber band” model which is solved by a novel Constrained Adaptive and Iterative Filtering Algorithm (CIAFA). The numerical results on measurement from copper(111) surface indicate the processed images are comparable in accuracy to data obtained with a slow scan rate, but are free of the scan drift error commonly seen in slow scan data. For atomic scale images, an additional first step to remove line-by-line strong background fluctuations and a fourth step of replacing the postprocessed image by its ranking map as the final atomic resolution image are required. The resulting image restores the lattice image that is nearly undetectable in the original fast scan data. 1. Introduction The invention of the scanning tunneling microscopy (STM) revolutionized the study of nanoscale and atomic scale surface structures and properties [1, 2]. However, STM has rarely been considered a real-time method because of its slow scanning rate compared to most dynamic processes on a surface [3]. This has severely limited its application to the study of most dynamic processes on surfaces such as surface diffusion, phase transitions, self-assembly phenomena, film growth and etching, chemical reactions, and conformational changes of molecules. Raising the scan rate of scanning probes has been the objective of intense research efforts in the past decades [3–5], with most of the efforts focused on hardware improvements. On the other hand, researchers have also applied other techniques to utilize conventional, slow scan STM to study dynamic processes. For example, low-frequency dynamic behavior of a flexible free-standing graphene sheet has been studied using clever postprocessing [6]. The common practice for STM measurement is by bringing the tip close to the sample surface and applying a voltage bias to generate a tunnel current between the tip and sample. The tip is moved across the sample parallel to the surface (in the plane). Changes in the surface height or in the density of states cause a change in the tunneling current. The change in current with respect to position can be measured itself, or alternatively the height of the tip corresponding to a constant current can be measured. These two modes are called the constant height mode and the constant current mode, respectively. In the constant current mode, feedback electronics adjust the height by a voltage to the piezoelectric height control mechanism. In the constant height mode, the voltage and height are both held constant while the current changes to keep the junction voltage from changing. The constant current mode is usually used in STM because surface features can easily exceed a predefined tip-sample separation (typically 4–7 Å) and can crash the tip in a constant height mode. But the constant current mode is slow, due to more time required by the piezoelectric movements to register the height change. The time to complete a measurement for each pixel position is about 2 msec for a typical equipment and approaches 0.1 msec for a top-of-line setup [3–5]. Conventional STM has a limited scanning speed because of the response time of the electric circuit and the piezoelectric component used to control the movement of the probes. The control of the motion of the tip requires an electric feedback circuit which can generate a resonance at the frequency of the order of 10 kHz. If the scanning speed is too fast large (...truncated)


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Hao Zhang, Xianqi Li, Yunmei Chen, Jewook Park, An-Ping Li, X.-G. Zhang. Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates, Scanning, 2017, 2017, DOI: 10.1155/2017/1097142