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- 저자 : Chatterjee Kingshuk (검색결과 2 건)
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Viney Ghai,Kingshuk Chatterjee,Prabhat K. Agnihotri 한국탄소학회 2021 Carbon Letters Vol.31 No.3
Vertically Aligned Carbon Nanotubes (VACNTs)-coated flexible aluminium (Al) foil is studied as an electrode for supercapacitor applications. VACNTs are grown on Al foil inside thermal Chemical Vapor Deposition (CVD) reactor. 20 nm thick layer of Fe is used as a catalyst while Ar, H2 and C2H2 are used as precursor gases. The effect of growth temperature on the structure of CNTs is studied by varying the temperature of CVD reactor from 550 °C to 625 °C. Better alignment of VACNTs arrays on Al foil is recorded at 600 °C growth temperature in comparison to other processing temperatures. Cyclic voltammetry results shows that VACNTs-coated Al foil has a specific capacitance of ~ 3.01 F/g at a scan rate of 50 mV/s. The direct growth of VACNT array results in better contact with Al foil and thus low ESR values observed in impedance spectroscopy analysis. This leads to a fast charge–discharge cycle as well as a very high value of power density (187.79 kW/ kg) suitable for high power applications. Moreover, wettability study shows that the fabricated VACNT electrode has a contact angle of more than 152° which signifies that it is a superhydrophobic surface and hence shows lower specific capacitance in comparison to reported values for VACNT array. Therefore, it is necessary to develop suitable post-processing strategies to make VACNTs hydrophilic to realize their full potential in supercapacitor applications.
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Freshness Assessment of Indian Gooseberry (Phyllanthus emblica) Using Probabilistic Neural Network
Mukherjee Alok,Sarkar Tanmay,Chatterjee Kingshuk 한국농업기계학회 2021 바이오시스템공학 Vol.46 No.4
Purpose In this paper, a probabilistic neural network (PNN)-based simple model for the detection of freshness in Indian gooseberry or amla (Phyllanthus emblica) samples has been developed. Methods The amla images have been analyzed using two features: hue histogram, which is a kind of color representative of the image, and entropy analysis, which corresponds to texture analysis of the sample images. Three freshness classes have been assigned depending on the freshness of the samples and governed by the Hedonic scale. Results The proposed PNN model is also tested with five different activation functions; out of which, radial and triangular basis functions are found to yield the most accurate results. Moreover, the hue-PNN model is found to possess marginal superiority over the entropy-PNN model, thus signifying the higher effectiveness of the former in the proposed work. The proposed work is computationally lighter as it contains PNN as the single analysis tool, aided by the image histograms. Moreover, the experiments have been conducted with the images captured using smartphones only, which establishes the portability of capturing images. Conclusions High freshness classification accuracy of 97.5%, ease of implementation, and use of smartphone captured images widen its practical applicability of developing into a smartphone application-based module.
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