Robotics & Machine Learning Daily News2024,Issue(Feb.8) :87-88.DOI:10.1002/crat.202300173

Findings from Sri Sivasubramaniya Nadar College of Engineering Broaden Understanding of Nanocomposites (Machine Learning Assisted Metal Oxide-bismuth Oxy Halide Nanocomposite for Electrochemical Sensing of Heavy Metals In Aqueous Media)

Robotics & Machine Learning Daily News2024,Issue(Feb.8) :87-88.DOI:10.1002/crat.202300173

Findings from Sri Sivasubramaniya Nadar College of Engineering Broaden Understanding of Nanocomposites (Machine Learning Assisted Metal Oxide-bismuth Oxy Halide Nanocomposite for Electrochemical Sensing of Heavy Metals In Aqueous Media)

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Abstract

Investigators publish new report on Nanotechnology - Nanocomposites. According to news reporting from Chennai, India, by NewsRx journalists, research stated, “Heavy metal in excess quantity is one of the major inorganic pollutants in water. It causes several hazards to human life and ecosystem.” Financial supporters for this research include Department of Science & Technology (India), SSN Trust. The news correspondents obtained a quote from the research from the Sri Sivasubramaniya Nadar College of Engineering, “It exists in traces in most of the commonly available drinking water sources from lakes, ponds, wells, etc., However, their presence in treated water is relatively significant. As the treated water is primarily used for agricultural purposes, it is necessary to monitor and measure their concentration. This requires sensing of metals in aqueous medium with good sensitivity and stability. Recently, nanosensors coupled with electrochemical transducer is preferred for analyzing heavy metal in aqueous solutions. In this work, Silver oxide-bismuth oxy bromide coated with nafion is proposed as an electrochemical sensor for detection of heavy metal ions in aqueous solution. Cyclic voltammetry (CV) behavior of the proposed electrode is observed in different electrolytes. Further, Differential Pulse Voltammetry (DPV) study shows that current increases with trace nickel and copper metal ions of different concentration. Further, machine learning (ML) algorithms such as Naive Bayes, ANN, SVM and decision trees are employed for nickel ions to train the cyclic voltammetry data and evaluate its performance. Naive Bayes algorithm provides the best accuracy of 93.2% among all the models. In this article, Silver Oxide Bismuth OxyBromide nanocomposite is identified for the electrochemical detection of Nickel and Copper ions in aqueous solution. The CV and DPV analysis is carried out for with different electrolytes. Linear response is obtained with a correlation coefficient of 98%.”

Key words

Chennai/India/Asia/Bismuth/Chemicals/Cyborgs/Electrochemicals/Emerging Technologies/Heavy Metals/Machine Learning/Nanocomposites/Nanotechnology/Nickel/Transition Elements/Sri Sivasubramaniya Nadar College of Engineering

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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