S. Narasimman was born in sholinghur, India on January 4, 1992. He received the B. E. degree in Electronics and Communication Engineering from Anna University, Trichy, India in 2013, and the M. Tech. in Sensor Systems Technology from VIT University, Vellore, India in 2015. He completed the Ph.D. degree at School of Electronics Engineering, VIT University, Vellore, India in 2020. He was also the recipient of CSIR-SRF during 2018-2020 from Government of India. He was completed his post-doctoral fellowship at Missouri University of Science and Technology, USA during 2023-2024. He is currently an Assistant Professor at the Department of Electronics and Communication Engineering, Sri Ramachandra Faculty of Engineering and Technology (SRET),SRIHER (DU), Porur, Chennai, India. His current research interests include fiber optic-based sensors (Evanescent mode, SPR, LMR, FBGs, FPI, Rayleigh and Raman Scattering) for Ultra high temperature, Strain, Chemical, VOC and Biomedical sensing Applications.
B.E., M.Tech., MBA., PhD., PDF (USA)
In recent years, rapid industrialization has led to widespread water pollution, posing serious health risks due to contaminants like pesticides, bacteria, inorganic compounds, and heavy metal ions (HMIs). Toxic metals such as mercury (Hg), lead (Pb), cadmium (Cd), chromium (Cr) and arsenic (As) are especially hazardous even at low concentrations. Given the hazardous nature of HMIs, developing and implementing effective detection methods is crucial. This research proposes a novel sensor platform using metal-organic frameworks (ZIF-MOFs) integrated with conducting polymers—polyaniline (PANI), polypyrrole (PPy), and polyvinylpyrrolidone (PVP)—as chemoreceptors for HMI detection. These hybrid materials will be synthesized via in situ MOF growth followed by dip-coating of polymers onto a fiber optic sensor (FOS) surface. Material characterization will be performed using SEM, XRD, and EDAX. The sensor will function based on evanescent wave absorption changes upon HMI interaction with the sensing layer. Sensor performance will be evaluated using dynamic HMI concentrations, with a focus on absorption spectra, sensitivity, selectivity, detection limits, response time, and dynamic range. This work aims to develop a stable, sensitive, and selective dip-type sensor for real-time water quality monitoring, offering an effective alternative to pristine MOFs.