凝胶自愈过程中R6G二聚化的表面增强拉曼散射

IF 5.3 2区 化学 Q1 CHEMISTRY, ANALYTICAL Microchimica Acta Pub Date : 2025-01-02 DOI:10.1007/s00604-024-06918-9
Yun Zhou, Minqiang Wang, Junnan Wang, Jindou Shi, Chen Zhang, Zheyuan Da, Youlong Xu, Yongqiang Ji, Nikolai V. Gaponenko, Arshad Saleem Bhatti
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引用次数: 0

摘要

传统的表面增强拉曼散射(SERS)衬底寻求拉曼信号的均匀性和再现性,通常假设并要求在拉曼测试过程中热点保持稳定。近年来,SERS样品预浓缩策略中的非均匀积累启发了自修复贵金属气凝胶(NMAs)的直接使用,作为本工作中提出的样品预处理,揭示了物质在激光辐照动态过程中的更多样化的拉曼信息。在特定的浓度范围内,观察到R6G的820 cm - 1等罕见的特征峰,并分析了R6G二聚化和脱附的潜在过程。这些结果为如何在常规条件下获得更多不同分子形态的拉曼信息来区分聚集状态提供了新的思路,从而将低浓度或单分子水平的信号闪烁转化为有用的信息。图形抽象
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Surface-enhanced Raman scattering of R6G dimerization during self-healing of gel

Traditional surface-enhanced Raman scattering (SERS) substrates seeking uniformity and reproducibility of the Raman signal often assume and require that hot spots remain consistently stable during Raman testing. Recently, the non-uniform accumulation in SERS sample pre-concentration strategies have inspired the direct use of self-healing noble metal aerogels (NMAs), as the sample pretreatment presented in this work, and uncovered more diverse Raman information of substances during the dynamic process of laser irradiation. Rare characteristic peaks such as 820 cm⁻1 for R6G within a specific concentration range were observed, and potential processes including R6G dimerization and desorption were analyzed. These results provide insights into how to obtain more Raman information of diverse molecule forms under conventional conditions to distinguish the aggregation state, which turn the blinking of signals at low concentration or single molecule level into useful information.

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来源期刊
Microchimica Acta
Microchimica Acta 化学-分析化学
CiteScore
9.80
自引率
5.30%
发文量
410
审稿时长
2.7 months
期刊介绍: As a peer-reviewed journal for analytical sciences and technologies on the micro- and nanoscale, Microchimica Acta has established itself as a premier forum for truly novel approaches in chemical and biochemical analysis. Coverage includes methods and devices that provide expedient solutions to the most contemporary demands in this area. Examples are point-of-care technologies, wearable (bio)sensors, in-vivo-monitoring, micro/nanomotors and materials based on synthetic biology as well as biomedical imaging and targeting.
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