Fabrication of Nanoporous Alumina and Their Structural Characteristics Study Using SEM Image Processing and Analysis

Choudhari, K.S.; Jidesh, P.; Udayashankar, N.K.

doi:10.1080/15533174.2011.611206

Cited by 13 publications

(15 citation statements)

References 26 publications

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“…Applications of image processing algorithms for images obtained from scanning electron microscopy (SEM) in materials science are shown on examples of qualitative (Choudhari et al ., ) and quantitative (Raimundo et al ., ) analysis of alumina porous. In the work of Choudhari et al .…”

Section: Introductionmentioning

confidence: 99%

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Qualitative and quantitative interpretation of SEM image using digital image processing

Saladra

Kopernik

2016

Journal of Microscopy

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The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations.

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Section: Introductionmentioning

confidence: 99%

“…In the work of Choudhari et al . (), qualitative algorithms like binarization, Otsu thresholding, connected‐feature labelling and erosion were used, but also the most characteristic stereological parameters were calculated. In the paper of Raimundo et al .…”

Section: Introductionmentioning

confidence: 99%

Qualitative and quantitative interpretation of SEM image using digital image processing

Saladra

Kopernik

2016

Journal of Microscopy

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“…Nanoporous anodic alumina (NAA) membranes have attracted considerable scientific interest due to their potential applications in areas such as production of one-dimensional nanomaterials including magnetic memory, optoelectronic devices, chemical sensors and electrolytic capacitors (Masuda & Fukuda, 1995; Choudhari et al, 2012 a , 2012 b ), gas separation, bone fixation, hemodialysis (Belwalkar et al, 2008), dye-sensitized solar cells (Sahu et al, 2012), and biomedical applications such as separation and purification of biomolecules (Osmanbeyoglu et al, 2009). These inorganic nanoporous membranes with a self-organized hexagonally packed pore-arrangement possess special properties such as ideal cylindrically shaped pores with an extremely narrow pore-size distribution, high pore density, and controllable pore diameter and periodicity.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the pore properties of these membranes, namely, pore-size distribution, porous area fraction, pore density, interpore distance, etc. can be easily controlled by varying the anodization process parameters (Choudhari et al, 2012 a ).…”

Section: Introductionmentioning

confidence: 99%

“…One of the important analytical tools usually used for such characterization, particularly for nanostructural morphological studies, is scanning electron microscopy (SEM). Image analysis has also been extensively used for estimation of pore properties (Hernandez et al, 1997; Masselin et al, 2001; Raimundo et al, 2009; Choudhari et al, 2012 a ).…”

Section: Introductionmentioning

confidence: 99%

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Quantification and Morphology Studies of Nanoporous Alumina Membranes: A New Algorithm for Digital Image Processing

Choudhari

Jidesh

et al. 2013

Microsc Microanal

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A new mathematical algorithm is reported for the accurate and efficient analysis of pore properties of nanoporous anodic alumina (NAA) membranes using scanning electron microscope (SEM) images. NAA membranes of the desired pore size were fabricated using a two-step anodic oxidation process. Surface morphology of the NAA membranes with different pore properties was studied using SEM images along with computerized image processing and analysis. The main objective was to analyze the SEM images of NAA membranes quantitatively, systematically, and quickly. The method uses a regularized shock filter for contrast enhancement, mathematical morphological operators, and a segmentation process for efficient determination of pore properties. The algorithm is executed using MATLAB, which generates a statistical report on the morphology of NAA membrane surfaces and performs accurate quantification of the parameters such as average pore-size distribution, porous area fraction, and average interpore distances. A good comparison between the pore property measurements was obtained using our algorithm and ImageJ software. This algorithm, with little manual intervention, is useful for optimizing the experimental process parameters during the fabrication of such nanostructures. Further, the algorithm is capable of analyzing SEM images of similar or asymmetrically porous nanostructures where sample and background have distinguishable contrast.

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Experimental methods in chemical engineering: Scanning electron microscopy andX‐ray ultra‐microscopy—SEMandXuM

Davies

Bessette

et al. 2022

Can J Chem Eng

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Scanning electron microscopy (SEM) produces images at 500 000 times magnification and better than 1 nm resolution to characterize inorganic and organic solid morphology, surface topography, and crystallography. An electron beam interacts with the material and generates secondary electrons (SE) and backscattered electrons (BSE) that detectors capture. Coupled with X-ray energydispersive spectroscopy (X-EDS), SEM-EDS identifies elemental composition. X-ray ultra-microscopy (XuM) traverses particles to identify phase changes and areas of high density and voids without slicing through the solids by microtome. Although SEM instrument capability continuously evolves with higher magnification and better resolution, desktop SEMs are becoming standard in laboratories that require frequent imaging and lower magnification. Hand-held cameras (800-1500Â) have the advantage of low cost, ease of use, and better colours. SEM depth of field is better than visible light microscopy, but image stacking software has narrowed the gap between the two. Modern user interfaces mean that today's SEM instruments are easier to operate and data acquisition is faster, but operators must be able to select the right technique for the application (e.g., SE vs. BSE). Furthermore, they must understand how operating parameters like probe current, accelerating voltage, spot-diameter, convergence angle, and working distance compromise sample integrity. The number of articles the Web of Science indexes that mention SEM has grown from 1000 in 1990 to over 40 000 in 2021. A bibliometric map identified four clusters of research: mechanical properties and microstructure; nanoparticles, composites, and graphene; antibacterial and green synthesis; and adsorption and wastewater.

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Fabrication of Nanoporous Alumina and Their Structural Characteristics Study Using SEM Image Processing and Analysis

Cited by 13 publications

References 26 publications

Qualitative and quantitative interpretation of SEM image using digital image processing

Qualitative and quantitative interpretation of SEM image using digital image processing

Quantification and Morphology Studies of Nanoporous Alumina Membranes: A New Algorithm for Digital Image Processing

Experimental methods in chemical engineering: Scanning electron microscopy andX‐ray ultra‐microscopy—SEMandXuM

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