Machine Learning-Assisted Pesticide Detection on a Flexible Surface-Enhanced Raman Scattering Substrate Prepared by Silver Nanoparticles

Abstract

Access to clean water is a pressing challenge affecting millions of lives and the aquatic body of the Earth. Sensitive detection of pollutants such as pesticides is particularly important to address this challenge. This study reports eco-friendly preparation of the surface-enhanced Raman scattering (SERS) substrate for machine learning-assisted detection of pesticides in water. The proposed SERS platform was prepared on a copy paper by reducing a silver salt using the extract of a natural plant, Cedrus libani. The fabricated SERS platform was characterized in detail using scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The high-density formation of silver nanoparticles with an average diameter of 41 nm on the surface of the paper enabled detection of analytes with a nanomolar level sensitivity. This SERS capability was used to collect Raman signals of four different pesticides in water: myclobutanil, phosmet, thiram, and abamectin. Raman spectra of the pesticides are highly complex, challenging accurate determination of the pesticide type. To overcome this challenge and distinguish pesticides, machine learning (ML) approach was used. The ML-mediated detection of harmful pesticides on a versatile, green, and inexpensive SERS platform appears to be promising for environmental applications.

Disintegration and Machine-Learning-Assisted Identification of Bacteria on Antimicrobial and Plasmonic Ag–CuxO Nanostructures

“…To confirm this finding, we fabricated copper oxide surfaces without silver which showed no SERS activity (Figure S9). It is also important to note that surfaces with only silver show a much higher SERS effect . Furthermore, it seems that the incorporation of copper oxide for high antibacterial activity reduces the SERS activity (Figure S9).…”

“…This process results in the growth of Ag–Cu x O nanostructures on the micro-structured surface of the paper, presumably via the reduction of salt ions by the polyphenols present in the C. libani extract. , As a result, the color of the paper changes from white to gray (Figure S1B). Furthermore, the produced surface also exhibits high antibacterial activity against Gram-negative and Gram-positive bacteria and can disintegrate the bacteria on the surface (Figure b).…”

“…It is also important to note that surfaces with only silver show a much higher SERS effect. 33 Furthermore, it seems that the incorporation of copper oxide for high antibacterial activity reduces the SERS activity (Figure S9). The strong antibacterial activity of copper oxide indirectly contributes to the detection of bacteria through leakage of intracellular components.…”

“…The detection is achieved by Raman spectroscopy assisted by machine learning techniques for multiplex, rapid, and low-cost identification of common bacteria. Specifically, Ag−Cu x O nanostructures were developed by combining the excellent antimicrobial property of paper decorated with in situ grown Cu x O nanoparticles 32 and flexible SERS surfaces 33 on a single platform. The presented platform exhibited over 99% bactericidal properties and high SERS activity, allowing detection of bacteria at a concentration as low as 10 3 cfu/mL.…”

Au–Ag Nanoparticles with Controllable Morphologies for the Surface-Enhanced Raman Scattering Detection of Trace Thiram

“…Thiram as a pesticide has been commonly used to protect crops from diseases. , However, the excessive use of thiram can contaminate food, soil, and water, leading to severe damage to human health. Accordingly, widespread studies have focused on the highly sensitive and reliable detection of thiram.…”