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To obtain scanning tunneling microscope images, constant current is held as the tip moves across the surface, experiencing voltage drops over bumps. Figure provided by Michael Schmid, TU Wien, at https://commons.wikimedia.org/ w/index.php?curid=180388
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In the fields of nanoscience and nanotechnology, it is important to be able to functionalize surfaces chemically for a wide variety of applications. Scanning tunneling microscopes (STMs) are important instruments in this area used to measure the surface structure and chemistry with better than molecular resolution. Self-assembly is frequently used...
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... nonlinear version of (2) relies on a classifier which determines whether a pixel of the original image belongs to the cartoon or the texture component (Buades et al 2011). The idea consists of measuring the rate of change of the lo- cal total variation (LTV) between the original image and its lowpass filtered version, defined ...
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... order to segment the images according to intensities or texture patterns, we first perform the cartoon+texture decom- position on each of them to obtain their cartoon and texture components. In our experiments, we select σ = 3 in Algo- rithm 1. This parameter leads to more appealing segmenta- tion results compared to other values of σ . Moreover, σ = 3 is the minimum value for which humans could perceive re- gion as textures (Buades et al ...
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... F * 1 stands for the inverse 1D Fourier Transform. The EWT was later generalized to 2D images for vari- ous kinds of wavelet transform, specifically tensor wavelets, Littlewood-Paley wavelet transform, the ridgelet transform, and the curvelet transform (Gilles et al ...
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... this paper, we proposed a framework to segment STM im- ages, combining variational methods and a clustering algo- rithm based on features extracted by the empirical wavelet transform. The expected information of microscopy images led us to first apply a cartoon+texture decomposition and then run a modified version of the multiphase CV model on the cartoon part, and a clustering of features extracted by the empirical curvelet transform on the texture part. The results in Section 5 demonstrate the proficiency of this framework to analyze STM images. Guttentag et al (2016a) have al- ready used the proposed approach to characterize patterns of cyanide molecules on Au{111}, complementing the results in another related work (Guttentag et al ...
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... order to obtain a scanning tunneling microsopy im- age of a SAM, an atomically sharp conducting probe tip is brought within one or two atomic diameters of the surface of the sample so that electrons can tunnel from the surface to the tip. A voltage bias is applied between the two and the tip-sample separation is typically adjusted while scan- ning to maintain a constant tunneling current of electrons. Since the current is extremely sensitive to the tip-sample sep- aration, better than atomic resolution is often obtained and apparent height differences across the surface are recorded, thereby acquiring nanoscale images with molecular features. The scanning procedure is shown in Figure 2 and examples of STM images of cyanide (CN) monolayers on Au{111} are shown in Figure 3. These images show the varying textures and different apparent heights (displayed as intensities) as a result of the structure and chemical properties of the SAM. Partitioning the images according to the apparent heights and texture patterns would help facilitate the understanding and analyses of SAMs and other surfaces studied. We note that not only are the ordered regions important but also are the Fig. 1 In self-assembled monolayers, a single layer of molecules is chemically bound to a solid or liquid substrate. The wide range of substrates (e.g., metals, semiconductors, insulators, glasses, superconductors, nanoparticles) that can be used call for complementary chemistries of attachment of the molecular layers. The exposed functional group at the ends of the molecules typically dominates the interactions of the substrate with the surrounding chemical, physical, and biological environment boundaries between them (Poirier 1997) since these domain boundaries determine access of other molecules to the sub- strate and can be used to isolate single molecules, or pairs, lines, or clusters of molecules (Bumm et al 1996;Kim et al 2011;Claridge et al ...
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... nonlinear version of (2) relies on a classifier which determines whether a pixel of the original image belongs to the cartoon or the texture component (Buades et al 2011). The idea consists of measuring the rate of change of the lo- cal total variation (LTV) between the original image and its lowpass filtered version, defined ...
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... order to segment the images according to intensities or texture patterns, we first perform the cartoon+texture decom- position on each of them to obtain their cartoon and texture components. In our experiments, we select σ = 3 in Algo- rithm 1. This parameter leads to more appealing segmenta- tion results compared to other values of σ . Moreover, σ = 3 is the minimum value for which humans could perceive re- gion as textures (Buades et al ...
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... F * 1 stands for the inverse 1D Fourier Transform. The EWT was later generalized to 2D images for vari- ous kinds of wavelet transform, specifically tensor wavelets, Littlewood-Paley wavelet transform, the ridgelet transform, and the curvelet transform (Gilles et al ...
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... this paper, we proposed a framework to segment STM im- ages, combining variational methods and a clustering algo- rithm based on features extracted by the empirical wavelet transform. The expected information of microscopy images led us to first apply a cartoon+texture decomposition and then run a modified version of the multiphase CV model on the cartoon part, and a clustering of features extracted by the empirical curvelet transform on the texture part. The results in Section 5 demonstrate the proficiency of this framework to analyze STM images. Guttentag et al (2016a) have al- ready used the proposed approach to characterize patterns of cyanide molecules on Au{111}, complementing the results in another related work (Guttentag et al ...
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... order to obtain a scanning tunneling microsopy im- age of a SAM, an atomically sharp conducting probe tip is brought within one or two atomic diameters of the surface of the sample so that electrons can tunnel from the surface to the tip. A voltage bias is applied between the two and the tip-sample separation is typically adjusted while scan- ning to maintain a constant tunneling current of electrons. Since the current is extremely sensitive to the tip-sample sep- aration, better than atomic resolution is often obtained and apparent height differences across the surface are recorded, thereby acquiring nanoscale images with molecular features. The scanning procedure is shown in Figure 2 and examples of STM images of cyanide (CN) monolayers on Au{111} are shown in Figure 3. These images show the varying textures and different apparent heights (displayed as intensities) as a result of the structure and chemical properties of the SAM. Partitioning the images according to the apparent heights and texture patterns would help facilitate the understanding and analyses of SAMs and other surfaces studied. We note that not only are the ordered regions important but also are the Fig. 1 In self-assembled monolayers, a single layer of molecules is chemically bound to a solid or liquid substrate. The wide range of substrates (e.g., metals, semiconductors, insulators, glasses, superconductors, nanoparticles) that can be used call for complementary chemistries of attachment of the molecular layers. The exposed functional group at the ends of the molecules typically dominates the interactions of the substrate with the surrounding chemical, physical, and biological environment boundaries between them (Poirier 1997) since these domain boundaries determine access of other molecules to the sub- strate and can be used to isolate single molecules, or pairs, lines, or clusters of molecules (Bumm et al 1996;Kim et al 2011;Claridge et al ...
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... the current is extremely sensitive to the tip-sample sep- aration, better than atomic resolution is often obtained and apparent height differences across the surface are recorded, thereby acquiring nanoscale images with molecular features. The scanning procedure is shown in Figure 2 and examples of STM images of cyanide (CN) monolayers on Au{111} are shown in Figure 3. These images show the varying textures and different apparent heights (displayed as intensities) as a result of the structure and chemical properties of the SAM. ...
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... nonlinear version of (2) relies on a classifier which determines whether a pixel of the original image belongs to the cartoon or the texture component (Buades et al 2011). The idea consists of measuring the rate of change of the lo- cal total variation (LTV) between the original image and its lowpass filtered version, defined by ...
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... F * 1 stands for the inverse 1D Fourier Transform. The EWT was later generalized to 2D images for vari- ous kinds of wavelet transform, specifically tensor wavelets, Littlewood-Paley wavelet transform, the ridgelet transform, and the curvelet transform (Gilles et al 2014). ...
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... parameter leads to more appealing segmenta- tion results compared to other values of σ . Moreover, σ = 3 is the minimum value for which humans could perceive re- gion as textures (Buades et al 2011). ...
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... results in Section 5 demonstrate the proficiency of this framework to analyze STM images. Guttentag et al (2016a) have al- ready used the proposed approach to characterize patterns of cyanide molecules on Au{111}, complementing the results in another related work (Guttentag et al 2016b). ...
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