Experimental and Computational Insights into SERS-Based Ultrasensitive Detection of the Pesticide Fenazaquin: Towards Food Safety and Environmental Analysis
- 1Intelligent System Design Laboratory, Optics, Material and Systems Team, Faculty of Sciences, Abdelmalek Essâadi University, B.P. 2121, M’ Hannech II, Tétouan 93030, Morocco
- 2Instituto de Estructura de la Materia, Consejo Superior de Investigaciones Científicas (IEM-CSIC), Serrano 121, 28006 Madrid, Spain
Abstract
In this work, SERS is employed as an effective detection technique for Fenazaquin (FEN) due to its notable specificity and sensitivity. The investigation involves a comprehensive analysis using UV–Vis spectroscopy, Raman spectroscopy and SERS on solutions containing varying concentrations of FEN. Different experimental conditions were examined to optimize the detection process, with Raman spectra acquired for FEN powder. SERS analyses were conducted across a concentration range of 9.9 × 10−8 to 1.9 × 10−6 mol/L. The selection of suitable substrates is crucial for optimizing SERS performance. Herein, the SERS signals of FEN were studied on Ag nanoparticles reduced by hydroxylamine (AgSH), with aggregation induced by KNO3 salt. To support the experimental data, the molecular structure and theoretical Raman spectra of FEN were calculated using Density Functional Theory (DFT). Furthermore, to gain insights into the interaction mechanisms between FEN and the Ag substrate, Adsorption Locator Monte Carlo simulations were employed. These simulations predicted the most favorable adsorption configurations and identified the probable site of attack of FEN on the silver surface, revealing key adsorption geometries contributing to SERS enhancement. The theoretical results were essential for assigning the vibrational modes of FEN. The combination of experimental and theoretical analyses led to the successful detection of FEN, with a remarkable limit of quantification (LOQ) of 9.9 × 10−8 mol/L (30 ppb). This integrated approach provides precise insights into the molecular properties and detection capabilities of FEN.
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BibTeX
@article{douass2026experimental,
title = {{Experimental and Computational Insights into SERS-Based Ultrasensitive Detection of the Pesticide Fenazaquin: Towards Food Safety and Environmental Analysis}},
author = {Oumaima Douass and Ibrahim Saadouni and Bousselham Samoudi and Ana Crespo and Santiago Sanchez-Cortes},
journal = {Molecules},
year = {2026},
month = nov,
doi = {10.3390/molecules31214009},
url = {https://www.mdpi.com/1420-3049/31/21/4009},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Experimental and Computational Insights into SERS-Based Ultrasensitive Detection of the Pesticide Fenazaquin: Towards Food Safety and Environmental Analysis
AU - Oumaima Douass
AU - Ibrahim Saadouni
AU - Bousselham Samoudi
AU - Ana Crespo
AU - Santiago Sanchez-Cortes
PY - 2026
DA - 2026/11/06
JO - Molecules
DO - 10.3390/molecules31214009
UR - https://www.mdpi.com/1420-3049/31/21/4009
AB - In this work, SERS is employed as an effective detection technique for Fenazaquin (FEN) due to its notable specificity and sensitivity. The investigation involves a comprehensive analysis using UV–Vis spectroscopy, Raman spectroscopy and SERS on solutions containing varying concentrations of FEN. Different experimental conditions were examined to optimize the detection process, with Raman spectra acquired for FEN powder. SERS analyses were conducted across a concentration range of 9.9 × 10−8 to 1.9 × 10−6 mol/L. The selection of suitable substrates is crucial for optimizing SERS performance. Herein, the SERS signals of FEN were studied on Ag nanoparticles reduced by hydroxylamine (AgSH), with aggregation induced by KNO3 salt. To support the experimental data, the molecular structure and theoretical Raman spectra of FEN were calculated using Density Functional Theory (DFT). Furthermore, to gain insights into the interaction mechanisms between FEN and the Ag substrate, Adsorption Locator Monte Carlo simulations were employed. These simulations predicted the most favorable adsorption configurations and identified the probable site of attack of FEN on the silver surface, revealing key adsorption geometries contributing to SERS enhancement. The theoretical results were essential for assigning the vibrational modes of FEN. The combination of experimental and theoretical analyses led to the successful detection of FEN, with a remarkable limit of quantification (LOQ) of 9.9 × 10−8 mol/L (30 ppb). This integrated approach provides precise insights into the molecular properties and detection capabilities of FEN.
SN - 1420-3049
ER -