Detection and Identification of Pesticides in Fruits Coupling to an Au-Au Nanorod Array SERS Substrate and RF-1D-CNN Model Analysis

• Published in: Nanomaterials (Basel, Switzerland) Vol. 14; no. 8; p. 717
• Main Authors: Sha, Pengxing, Zhu, Chushu, Wang, Tianran, Dong, Peitao, Wu, Xuezhong
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 19.04.2024; MDPI
• Subjects: 1D-CNN model analysis; Algorithms; Analysis; Arrays; Artificial neural networks; Au–Au nanorod array; Biocompatibility; Carbendazim; Chloroauric acid; Electric potential; Electrolytic cells; Electromagnetic fields; Electromotive forces; Finite difference time domain method; Food safety; Fungicides; galvanic cell reaction; Gold; Identification and classification; Mathematical models; Methods; Nanoparticles; Nanorods; Nanostructure; Neural networks; pesticide; Pesticides; Properties; Raman scattering; Raman spectra; Raman spectroscopy; Reproducibility; Simulation; Spectrum analysis; Structure; Substrates; surface-enhanced Raman scattering; Thiabendazole; Thiram; China; United States > US; surface-enhanced Raman scattering; galvanic cell reaction; pesticide; 1D-CNN model analysis; Au–Au nanorod array
• DOI: 10.3390/nano14080717
• ISSN: 2079-4991

In this research, a method was developed for fabricating Au-Au nanorod array substrates through the deposition of large-area Au nanostructures on an Au nanorod array using a galvanic cell reaction. The incorporation of a granular structure enhanced both the number and intensity of surface-enhanced Raman scattering (SERS) hot spots on the substrate, thereby elevating the SERS performance beyond that of substrates composed solely of an Au nanorod. Calculations using the finite difference time domain method confirmed the generation of a strong electromagnetic field around the nanoparticles. Motivated by the electromotive force, Au ions in the chloroauric acid solution were reduced to form nanostructures on the nanorod array. The size and distribution density of these granular nanostructures could be modulated by varying the reaction time and the concentration of chloroauric acid. The resulting Au-Au nanorod array substrate exhibited an active, uniform, and reproducible SERS effect. With 1,2-bis(4-pyridyl)ethylene as the probe molecule, the detection sensitivity of the Au-Au nanorod array substrate was enhanced to 10 M, improving by five orders of magnitude over the substrate consisting only of an Au nanorod array. For a practical application, this substrate was utilized for the detection of pesticides, including thiram, thiabendazole, carbendazim, and phosmet, within the concentration range of 10 to 5 × 10 M. An analytical model combining a random forest and a one-dimensional convolutional neural network, referring to the important variable-one-dimensional convolutional neural network model, was developed for the precise identification of thiram. This approach demonstrated significant potential for biochemical sensing and rapid on-site identification.