Electrochemical sensing of nickel using modified silver nanoparticles/bismuth oxybromide graphite electrode

Vijayalakshmi, K; Radha, S; Muthumeenakshi, K; Sreeja, B S

doi:10.1007/s10854-023-11130-1

J Mater Sci: Mater Electron

2023

DOI: 10.1007/s10854-023-11130-1

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Electrochemical sensing of nickel using modified silver nanoparticles/bismuth oxybromide graphite electrode

K Vijayalakshmi,

S Radha,

K Muthumeenakshi

et al.

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Cited by 4 publications

References 43 publications

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Machine Learning Assisted Metal Oxide‐Bismuth Oxy Halide Nanocomposite for Electrochemical Sensing of Heavy Metals in Aqueous Media

Kailasam,

Sankararajan,

Kailasam

et al. 2024

Cryst. Res. Technol.

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Heavy metal in excess quantity is one of the major inorganic pollutants in water. It causes several hazards to human life and ecosystem. 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 Naïve Bayes, ANN, SVM and decision trees are employed for nickel ions to train the cyclic voltammetry data and evaluate its performance. Naïve Bayes algorithm provides the best accuracy of 93.2% among all the models.

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Machine Learning Assisted Metal Oxide‐Bismuth Oxy Halide Nanocomposite for Electrochemical Sensing of Heavy Metals in Aqueous Media

Kailasam,

Sankararajan,

Kailasam

et al. 2024

Cryst. Res. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

Chronoamperometry and Differential Pulse Analysis of Nickel Ions in Aqueous Solution Using Carbon Nanotubes with Nanosheet Shaped Bismuth Oxychloride Sensor

Vijayalakshmi,

Radha,

Muthumeenakshi

et al. 2024

J Inorg Organomet Polym

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Room temperature analysis of vanillin and folic acid in food samples using a BiOBr/GCE sensor: An empathetic and efficient approach

et al. 2025

Materials Science in Semiconductor Processing

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Electrochemical sensing of nickel using modified silver nanoparticles/bismuth oxybromide graphite electrode

Cited by 4 publications

References 43 publications

Machine Learning Assisted Metal Oxide‐Bismuth Oxy Halide Nanocomposite for Electrochemical Sensing of Heavy Metals in Aqueous Media

Machine Learning Assisted Metal Oxide‐Bismuth Oxy Halide Nanocomposite for Electrochemical Sensing of Heavy Metals in Aqueous Media

Chronoamperometry and Differential Pulse Analysis of Nickel Ions in Aqueous Solution Using Carbon Nanotubes with Nanosheet Shaped Bismuth Oxychloride Sensor

Room temperature analysis of vanillin and folic acid in food samples using a BiOBr/GCE sensor: An empathetic and efficient approach

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