Water is a basic human need and has been heavily contaminated. Therefore, it becomes a concern to remove the pollutant and monitor its quality. The removal methods include precipitation, filtration, adsorption, and photodegradation. Meanwhile, the monitoring can be done by measuring and analyzing the contaminant using spectrophotometry and chromatography. Nevertheless, those methods usually need a complicated preparation, and are expensive. Thus, a simple method is necessary to overcome these drawbacks by developing a sensor. In recent years, the sensor performance has been enhanced by using nanomaterials, such as silver nanoparticles (AgNPs). AgNPs can be synthesized using plant extracts through a green synthesis approach. Extracts of leaves, stems, roots, and fruits from various plants have been successfully used as reducing agents in synthesis process and stabilizing the AgNPs. More importantly, the published articles also reported that the green synthesized nanoparticles can be applied as the sensor component for monitoring various water pollutants (both organic and inorganic). We have critically reviewed the potential of plant extract as a reducing agent of silver ions using different green synthetic methods. The characterizations of silver nanoparticles include the initial characterization (UV-visible spectrophotometry) and the advanced characterizations (FTIR, XRD, SEM, EDS, TEM, and DLS). This review also provides information about applications of AgNPs in sensor for monitoring water pollution. Therefore, this review article delivers a point of view on the silver nanoparticle development in recent decades, and it can be a reference for further study, especially for sensors.
Serunting, Muhamad Allan; Zulfikar, Muhammad Ali; Setiyanto, Henry; Setyorini, Dian Ayu; and Saraswaty, Vienna
"Green synthesized silver nanoparticles-based sensing for monitoring water pollution: an updated review,"
Karbala International Journal of Modern Science: Vol. 9
, Article 12.
Available at: https://doi.org/10.33640/2405-609X.3332
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