Magnetic MOF Substrates for the Rapid and Sensitive Surface-Enhanced Raman Scattering Detection of Uranyl

铀酰 化学 检出限 吸附 基质(水族馆) 拉曼散射 表面等离子共振 拉曼光谱 纳米颗粒 分析化学(期刊) 纳米技术 色谱法 物理化学 冶金 材料科学 海洋学 物理 光学 地质学
作者
Ning Wang,Jingjing Du,Xue Li,Xunlong Ji,Yulin Wu,Zhenli Sun
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (34): 12956-12963 被引量:4
标识
DOI:10.1021/acs.analchem.3c02696
摘要

With the widespread use of uranium in the nuclear industry, achieving rapid and sensitive detection of uranium contaminants is critical for reducing environmental pollution. Surface-enhanced Raman scattering (SERS), with its high sensitivity and unique fingerprint properties, has been used for the analysis of uranyl. However, the weak affinity of Au for uranyl remains a challenge in the development of spherical Au-based SERS substrates. The metal–organic framework (MOF) material ZIF-8 exhibits excellent adsorption capacity for uranyl and could overcome this limitation. In this study, ZIF-8 porous structures were modified on a magnetic SERS substrate, Fe3O4@SiO2@Au (FA), for the rapid and sensitive detection and analysis of the uranyl species. Uranyl was adsorbed by ZIF-8, allowing ready access to the hot spots in the interstices of Au nanoparticles (AuNPs). Symmetrically stretched vibrating bonds of O═U═O were detected at 829 cm–1 as the characteristic peak of uranyl by surface plasmon resonance between the AuNPs. The ZIF-8 coating had minimal influence on target detection as the detection limit for 4-MPY was only half an order of magnitude lower than before modification. The enhancement factor for uranyl reached 106. The substrate showed excellent sensing performance in a neutral or alkaline environment. It was used to detect uranyl in tap water and river water; rapid separation of the species from the water samples was achieved using an external magnet to extract radioactive waste. The proposed substrate offers a route for monitoring and detecting uranyl contamination and an approach for achieving rapid on-site detection, providing a promising application for environmental contaminant detection.
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