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Electrochemical study of Magnetite-CH composite carbon paste modified electrode
AL. Kavitha,Kumanan Bharathi Yazhini 한국화학공학회 2016 Korean Journal of Chemical Engineering Vol.33 No.6
Magnetite nanoparticles were synthesized by coprecipitation and characterized. The average particle size was 22-50 nm by XRD and AFM. Chitosan was prepared from crab shells and characterized. Magnetite-chitosan composite carbon paste modified electrode was prepared and characterized by using XRD, FT-IR and SEM technique. The electrochemical responses of this Magnetite-CH composite electrode were studied in potassium ferrocyanide/KCl system using cyclic voltammetry and electrochemical impedance spectroscopy. The cyclic voltammetric and EIS studies indicated better electron transfer of magnetite-CH composite (3 : 1) carbon paste modified electrodes compared to bare, magnetite, chitosan composite electrodes. The surface parameters like surface coverage (τ), Diffusion coefficient (D0), and rate constant (kS) were studied. The shelf-life of the developed electrode system is about 12 weeks under refrigerated conditions.
An Ingenious Multiple Communicator Concept for Next Generation Smart Metering Communication System
Wahidah Hashim,Ahmad Fadzil Ismail,Rajina M. A. Raj Mohamed,Mohammad Kamrul Hasan,Muhammad Idham Abdul Halim,Kavitha Kumanan 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.7
In this article, we propose and study a self-switching network concept known as an ingenious multiple communicator mechanism which can be applied to energy provider’s smart metering device. We outline reasons why such multiple connections networks are required through real case study scenarios and key components that drive towards such concept. We have gathered actual measurement values for a particular network and identified in what situation this is most suitable and applicable. We have come out with the basic system model for this multiple communicator. We also observed that a less fluctuating and similar pattern of network performance helps to design better network predictive analytics function. Finally numerical examples and analysis of the results are presented.