The Experts below are selected from a list of 126 Experts worldwide ranked by ideXlab platform
X G Zhang - One of the best experts on this subject based on the ideXlab platform.
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Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates
'Hindawi Limited', 2018Co-Authors: Hao Zhang, Yunmei Chen, Jewook Park, X G ZhangAbstract: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 © 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.
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postprocessing algorithm for driving conventional scanning tunneling microscope at fast scan rates
Scanning, 2017Co-Authors: Hao Zhang, Yunmei Chen, Jewook Park, X G ZhangAbstract: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.
Wei Qiu - One of the best experts on this subject based on the ideXlab platform.
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Digital rotation moiré method for strain measurement based on high-resolution transmission electron microscope Lattice Image
Optics and Lasers in Engineering, 2019Co-Authors: Huadan Xing, Zhixun Gao, Hong-tao Wang, Zhenkun Lei, Wei QiuAbstract:Abstract This study presented a digital rotation moire (DRM) method for strain measurement based on high-resolution transmission electron microscope (HR-TEM) Lattice Images. The TEM Lattice Images were used to generate the reference and specimen gratings. The procedure involved in the proposed DRM method was based on the rotation moire principle and a digital moire algorithm, which detect the in-plane strain components by quantifying the Image parameters, including the mean value of the relative rotation angles between the specimen and reference gratings and the fringe inclination angle in the digital moire patterns. The obtained strain is the strain of the Lattices in the analysis area relative to that of the Lattices in the reference region. A series of virtual experiments were performed on Lattice Images of (110) monocrystalline silicon, and the accuracy of the proposed method was verified. Subsequently, this method was successfully employed to measure the local strain of a multi-layer semiconductor heterostructure. The results were analyzed and compared with those obtained through micro-Raman spectroscopy, showing that the DRM method based on Lattice Images was generally applicable to analyze the detailed information of the three in-plane strain components with a spatial resolution in the ten-nanometer scale.
Hao Zhang - One of the best experts on this subject based on the ideXlab platform.
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Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates
'Hindawi Limited', 2018Co-Authors: Hao Zhang, Yunmei Chen, Jewook Park, X G ZhangAbstract: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 © 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.
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postprocessing algorithm for driving conventional scanning tunneling microscope at fast scan rates
Scanning, 2017Co-Authors: Hao Zhang, Yunmei Chen, Jewook Park, X G ZhangAbstract: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.
Huadan Xing - One of the best experts on this subject based on the ideXlab platform.
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Digital rotation moiré method for strain measurement based on high-resolution transmission electron microscope Lattice Image
Optics and Lasers in Engineering, 2019Co-Authors: Huadan Xing, Zhixun Gao, Hong-tao Wang, Zhenkun Lei, Wei QiuAbstract:Abstract This study presented a digital rotation moire (DRM) method for strain measurement based on high-resolution transmission electron microscope (HR-TEM) Lattice Images. The TEM Lattice Images were used to generate the reference and specimen gratings. The procedure involved in the proposed DRM method was based on the rotation moire principle and a digital moire algorithm, which detect the in-plane strain components by quantifying the Image parameters, including the mean value of the relative rotation angles between the specimen and reference gratings and the fringe inclination angle in the digital moire patterns. The obtained strain is the strain of the Lattices in the analysis area relative to that of the Lattices in the reference region. A series of virtual experiments were performed on Lattice Images of (110) monocrystalline silicon, and the accuracy of the proposed method was verified. Subsequently, this method was successfully employed to measure the local strain of a multi-layer semiconductor heterostructure. The results were analyzed and compared with those obtained through micro-Raman spectroscopy, showing that the DRM method based on Lattice Images was generally applicable to analyze the detailed information of the three in-plane strain components with a spatial resolution in the ten-nanometer scale.
Jewook Park - One of the best experts on this subject based on the ideXlab platform.
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Postprocessing Algorithm for Driving Conventional Scanning Tunneling Microscope at Fast Scan Rates
'Hindawi Limited', 2018Co-Authors: Hao Zhang, Yunmei Chen, Jewook Park, X G ZhangAbstract: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 © 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.
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postprocessing algorithm for driving conventional scanning tunneling microscope at fast scan rates
Scanning, 2017Co-Authors: Hao Zhang, Yunmei Chen, Jewook Park, X G ZhangAbstract: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.