Liu Wei, Wang Zihan, Liu Zhongping, Chen Junxue, Shi Lingyan, Huang Longjin, Liu Yu, Cui Sheng, He Xuan
Institute of Chemical Materials, China Academy of Engineering Physics, Mianyang 621900, China.
State Key Laboratory of Materials-Oriented Chemical Engineering, College of Material Science and Engineering, Nanjing Tech University, Nanjing 211816, China.
ACS Sens. 2023 Apr 28;8(4):1733-1741. doi: 10.1021/acssensors.3c00012. Epub 2023 Mar 22.
The surface-enhanced Raman scattering (SERS) technique is a promising method for the detection of explosives such as 2,4,6-trinitrotoluene (TNT) and 3-nitro-1,2,4-triazol-5-one (NTO) because of its high sensitivity to trace substances. However, most SERS detection processes are often nonautomated as well as exhibit low efficiency and toxic exposure, which often poses potential danger to operators. Herein, we propose the integration of SERS with digital microfluidics (SERS-DMF) for automated, high-throughput, and high-sensitivity detection of explosives. First, we carefully designed a DMF chip comprising 40 drive electrodes and 8 storage electrodes to achieve a high-throughput process. And different concentrations of target molecules, silver nanoparticles (Ag NPs), and salts were loaded into the DMF chip. Then, the droplet aggregation, incubation, and detection processes were automatically controlled using the SERS-DMF platform. In addition, Ag NPs were efficiently aggregated by screening different types and concentrations of salts, resulting in "hotspots" and the SERS effect. With the help of the SERS-DMF platform, two explosive samples were automatically detected with high throughput and high sensitivity. The detection limits of TNT and NTO were 10 and 10 M, respectively. In addition, compared with nonautomatic operations, the SERS-DMF platform exhibited better reproducibility and higher efficiency for the detection of explosives. The proposed SERS-DMF thus has considerable potential as an analytical technique for detecting hazardous substances.
表面增强拉曼散射（SERS）技术因其对痕量物质具有高灵敏度，是检测2,4,6-三硝基甲苯（TNT）和3-硝基-1,2,4-三唑-5-酮（NTO）等爆炸物的一种很有前景的方法。然而，大多数SERS检测过程往往是非自动化的，并且效率低、存在有毒暴露问题，这常常给操作人员带来潜在危险。在此，我们提出将SERS与数字微流控技术（SERS-DMF）相结合，用于爆炸物的自动化、高通量和高灵敏度检测。首先，我们精心设计了一个包含40个驱动电极和8个存储电极的数字微流控芯片，以实现高通量过程。然后将不同浓度的目标分子、银纳米颗粒（Ag NPs）和盐加载到数字微流控芯片中。接着，利用SERS-DMF平台自动控制液滴聚集、孵育和检测过程。此外，通过筛选不同类型和浓度的盐，Ag NPs能够有效聚集，从而产生“热点”和SERS效应。借助SERS-DMF平台，两个爆炸物样品被自动进行了高通量和高灵敏度检测。TNT和NTO的检测限分别为10⁻⁸和10⁻⁹ M。此外，与非自动化操作相比，SERS-DMF平台在爆炸物检测方面表现出更好的重现性和更高的效率。因此，所提出的SERS-DMF作为一种检测有害物质的分析技术具有相当大的潜力。
