拉曼散射
拉曼光谱
太赫兹辐射
化学
信号(编程语言)
纳米技术
化学成像
检出限
拉曼光学活性
纳米材料
福瑞姆
光电子学
分子
散射
纳米颗粒
生物分子
化学传感器
分析化学(期刊)
作者
Lixin Ma,Ruiyun Zhou,Xiaonan Yang,Zijie Dai,Qian Xu,Yang Zhang,Chen Wang,Zhiming Guo,Yunxia Ye,Xiaobo Zou,Jianrong Cai
标识
DOI:10.1021/acs.analchem.5c02689
摘要
Surface-enhanced Raman scattering (SERS) technique offers detailed chemical structure information on molecules and has been widely applied in the detection of chemical pesticide molecules. The molecular structures of different pesticides vary significantly, and their Raman scattering cross-sections are typically low and significantly different. The low concentrations of pesticide residues and the complexity of sample matrices often pose challenges for direct Raman detection. Especially in mixed pesticides, it is difficult for the SERS technology to obtain effective spectral information from molecules with lower Raman scattering cross-sections. Herein, a SERS-terahertz dual-modal sensor based on a carbon nanotubes/Au@Ag nanoparticles (CNTs/Au@AgNPs) cross-wavelength hierarchical metamaterial device was constructed. Unlike conventional single-signal enhancement devices, this sensor achieves synergistic enhancement of Raman and terahertz signals by integrating composite nanomaterials into one micronano-sensing chip, rationally arranging the terahertz local electric field enhancement region and Raman "hotspots." Leveraging heterologous signal amplification, the sensor enables the effective detection of pesticide molecules through complementary information provided by Raman and terahertz spectroscopies and dual-modal signal enhancement. As a verification, the dual-modal device realizes the simultaneous detection of thiram and imidacloprid, and the limit of detection reaches 0.0149 and 0.0721 mg/kg, respectively. Additionally, the device can restore its sensing ability through simple washing and demonstrates good reusability. This integrated micronano-sensing device, comprising cross-wavelength hierarchical metamaterials, exhibits excellent sensing performance and offers a novel approach for multisubstance chemical analysis.
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