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Published on: February 1, 2018
β-Lactoglobulin Amyloid Fibrils-Poly(vinyl alcohol)-AgNPs Hydrogel as a Surface-Enhanced Raman Substrate for
Yaoyao Zhang1, Xinxin Zhang1, Chaotao Chen1
1Key Laboratory of Chemistry and Engineering of Forest Products, State Ethnic Affairs Commission; Guangxi Key Laboratory of Chemistry and Engineering of Forest Products; Engineering Research Center of Low-carbon and High-quality Utilization of Forest Biomass, University of Guangxi; Laboratory of Optic-electric Chemo/Biosensing and Molecular Recognition, Education Department of Guangxi Zhuang Autonomous Region; School of Chemistry and Chemical Engineering, Guangxi Minzu University, Nanning 530006, China.
Abstract:
A β-lactoglobulin amyloid fibrils-poly(vinyl alcohol)-Ag nanoparticles (β-LAFs-PVA-AgNPs) hydrogel was prepared as a surface-enhanced Raman scattering (SERS) substrate based on poly(vinyl alcohol) (PVA) with adsorbent β-lactoglobulin amyloid fibrils (β-LAFs) structured into the network structure of the hydrogel using the immersion reduction method. Due to the high swelling and contraction properties of the hydrogel in different states and the "sieving" nature of its network cavities, small molecular target analytes can more easily enter the space-confined hydrogel and rapidly bind with the amide bonds of the protein structure. During the contraction process of the hydrogel, the target analytes are enriched, and the Ag nanoparticles (AgNPs) come closer together to form Raman "hot spots", generating stronger SERS signals. The SERS performance of this hydrogel was evaluated using thiram and ibuprofen as target molecules. The results showed high detection sensitivity with limits of 37.1 μg/L for thiram and 85.6 μg/L for ibuprofen, respectively, and the entire sample pretreatment and detection process is completed within 11 min. The substrate also demonstrated excellent selectivity, uniformity, stability, and reproducibility. When applied to detect thiram in fruits and vegetables and ibuprofen in herbal tea, the recovery rates ranged from 90.1% to 114.7%, with the relative standard deviations (RSDs) of 0.61% to 5.8%. The SERS results matched those from HPLC analysis. This method offers simple and rapid sample pretreatment, high sensitivity, strong adsorption capacity for organic pollutants, and good selectivity, making it a promising candidate for on-site rapid detection applications.
