A Novel SERS Label-Free Sensing Strategy for DON and NIV : A DFT Study on the Interaction between DON/NIV and Ag/Au

In this study, we propose a novel label-free detection strategy based on surface-enhanced Raman spectroscopy (SERS) for detecting deoxynivalenol (DON) and nivalenol (NIV), analyzing the interactions between these fungal toxins and Ag/Au substrates using density functional theory (DFT). The DFT calcu...

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Veröffentlicht in:Langmuir : the ACS journal of surfaces and colloids. - 1985. - 40(2024), 40 vom: 08. Okt., Seite 20954-20965
1. Verfasser: Lian, Shuai (VerfasserIn)
Weitere Verfasser: Li, Xiaoqiong, Lv, Xuefei
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:Langmuir : the ACS journal of surfaces and colloids
Schlagworte:Journal Article Silver 3M4G523W1G Gold 7440-57-5 Trichothecenes deoxynivalenol JT37HYP23V nivalenol 5WOP02RM1U
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520 |a In this study, we propose a novel label-free detection strategy based on surface-enhanced Raman spectroscopy (SERS) for detecting deoxynivalenol (DON) and nivalenol (NIV), analyzing the interactions between these fungal toxins and Ag/Au substrates using density functional theory (DFT). The DFT calculation results indicate that the oxygen atoms in DON and NIV molecules exhibit high electronegativity, suggesting that they can serve as active sites in interaction with the metal surfaces in the SERS effect. By constructing DON/NIV-Ag6/Au6 complex models and evaluating their binding energies, we demonstrate the formation of stable complexes, showing characteristic frequency shifts, broadening, and selective enhancement in theoretical Raman spectra. The results indicate that the structural differences between DON and NIV lead to significant variations in the characteristic frequencies of their theoretical SERS spectra, providing a reproducible and interference-resistant method for the label-free detection of these fungal toxins. This work enhances the understanding of molecular-substrate interactions in SERS effects and provides a theoretical basis for the application of label-free SERS sensing strategies based on characteristic frequency shifts 
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