期刊
SENSORS AND ACTUATORS B-CHEMICAL
卷 390, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2023.133888
关键词
Surface enhancement Raman Scattering; MXene; Ag nanoparticles; Flexible substrate; Multiplexed detection
This article introduces a surface-enhanced Raman scattering (SERS) sensor that achieves reliable and sensitive large-scale rapid screening of target analytes. The sensor demonstrates ultralow limit of detection, outstanding sensitivity, and high stability. It also allows for the multiplexed detection of pesticide residues and the recognition of target molecules in a wide range of fields.
Sensors integrated with sampling and analysis processes are the key in analytical chemistry, environmental protection and national security. However, achieving reliable and sensitive large-scale rapid screening of target analytes is still challenging. Herein, we demonstrate a robust surface-enhanced Raman scattering (SERS) sensor by constructing dense and uniform plasmonic hotspots on the flexible Ti(3)C(2)Tx MXene/graphene oxide (MG) fibers through a self-assemble strategy at the oil-water interface. The produced SERS substrates exhibited an ultralow limit of detection (LOD, 1 x10(- 15) M for R6G), outstanding sensitivity (EF = 1.53 x10(12)) and high stability for R6G molecules (RSD = 9.47%, over 60 days storage). SERS experiments and theoretical simulations suggested that acidified Ti(3)C(2)Tx MXene further excited charge-transfer (CT) resonance of the system, while the assembled Ag nanostructures produced a large electromagnetic (EM) field enhancement. Thus, the fiber sensor not only realizes the multiplexed and powerful detection of pesticide residues (LOD of 10(-11) M) with an error < 7.3% via an established concentration-dependent standard color barcodes, but also allows the recognization of target molecules in a wide range of fields, such as methylene blue, crystal violet and nikethamide. This work provides new insights in the development of versatile label-free sensors for the rapid multiplexed analysis of target molecules in real samples.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据