Browsing by Author "Sudheendra, P."

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Fabrication and high-temperature structural characterization study of porous anodic alumina membranes
(2012) Choudhari, K.S.; Sudheendra, P.; Udayashankar, N.K.
Porous anodic alumina (PAA) membranes with highly ordered array of nanopores were prepared by twostep anodization process. Studies on structural and thermal properties and the thermal stability of the prepared PAA membranes were carried out. Investigation using scanning electron microscopy, atomic force microscopy, X-ray diffraction, thermal analysis and infrared spectroscopy was performed on the prepared PAA membranes at room temperature and in the temperature range 600-1,400 °C. The as-prepared PAA membranes revealed the amorphous nature. Polycrystalline PAA membranes were obtained by annealing carried out at different temperatures. Annealing study confirmed that the heat treatment transformed the amorphous PAA membranes to their crystalline phases, namely, ?-alumina at about 870 °C and then to ?-alumina around 1,250 °C. © Springer Science+Business Media, LLC 2011.
Quantification and morphology studies of nanoporous alumina membranes: A new algorithm for digital image processing
(2013) Choudhari, K.S.; Jidesh, P.; Sudheendra, P.; Kulkarni, S.D.
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. Copyright � Microscopy Society of America 2013.
Quantification and morphology studies of nanoporous alumina membranes: A new algorithm for digital image processing
(2013) Choudhari, K.S.; Jidesh, P.; Sudheendra, P.; Kulkarni, S.D.
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. Copyright Â© Microscopy Society of America 2013.