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        Synthesis and development of a highly adhesive graphene coating to improve the corrosion resistance of zinc in aggressive environment

        Sahu Deepak Kumar,Das Amlan,Das Sanjeev,Mallik Archana 한국탄소학회 2024 Carbon Letters Vol.34 No.1

        The current study explores the possibility of graphene as a protective layer on the zinc substrate through an optimized electrophoretic deposition process. Graphene has been synthesized from H2SO4, HNO3, and HClO4 solutions by an electrochemical exfoliation route. This method is known for providing a scalable and economical approach to the synthesis of graphene. The exfoliated graphene nano-sheets were characterized by X-ray diffraction, Fourier-transform infrared spectroscopy, UV–visible, and field emission scanning electron microscope to evaluate its properties. The three different synthesized forms of graphene nano-sheets were electrophoretically deposited onto Zn substrates at two different potentials. Scratch testing was employed to check the adhesion quality of the coatings. The corrosion behaviour of Zn and graphene-coated Zn substrates was studied in borate buffer and 3.5 wt% NaCl solutions through potentiodynamic polarization and electrochemical impedance spectroscopy. It was observed that graphene synthesized from H2SO4 exhibited superior anti-corrosion properties in comparison to others.

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        Estimation of chlorophyll-a concentration and trophic states in Nalban Lake of East Kolkata Wetland, India from Landsat 8 OLI data

        Pulak Priti Patra,Sourabh Kumar Dubey,Raman Kumar Trivedi,Sanjeev Kumar Sahu,Sangram Keshari Rout 대한공간정보학회 2017 Spatial Information Research Vol.25 No.1

        Landsat operational land imager (OLI) data and consequent laboratory measurements were used to predict chlorophyll-a (Chl-a) concentration and the trophic states for an inland lake within the East Kolkata Wetland, India (a Ramsar site). The most suitable band ratio was identified by performing Pearson correlation analysis between Chla concentrations and possible OLI band and band ratios from the study points. The results showed highest correlation coefficient from the band ratio OLI5/OLI4 with an R value of 0.85. The prediction model was then developed by applying regression analysis between the band ratio OLI5/OLI4 and Chl-a concentration of the study points. The reflectance ratios of the validation points were given as input on the prediction model and the model output was considered as predicted Chl-a values of the validation points to check the efficiency of the prediction model. The regression model between laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points revealed a high correlation with an R2 value of 0.78. Trophic State Index (TSI) of the lake was also calculated from laboratory-derived Chl-a value and model-fitted Chla value of the validation points. The study presented a high correlation of TSI determined from predicted data with TSI from laboratory reference data (R = 0.88). The TSI values of the lake ranged from 65 to 75 which indicate that the lake is appeared to be eutrophic to hypereutrophic conditions. This empirical study showed that Landsat 8 OLI imagery can be effectively applied to estimate Chla levels and trophic states for inland lakes.

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