Analysis of TNT，PA，Tetryl，RDX，PETN by Fluorescence Colorimetric Sensing Array Combines Metrology

LANG Yu-bo; LI Hong-da; YAN Shi; LIU Chun-qing

doi:10.19969/j.fxcsxb.23071802

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Analysis of TNT，PA，Tetryl，RDX，PETN by Fluorescence Colorimetric Sensing Array Combines Metrology

Experimental Techniques and Methods | 更新时间：2023-12-25

- Analysis of TNT，PA，Tetryl，RDX，PETN by Fluorescence Colorimetric Sensing Array Combines Metrology
- Journal of Instrumental Analysis Vol. 42, Issue 12, Pages: 1645-1651(2023)
- 作者机构：
  
  中国刑事警察学院，辽宁沈阳 110035
- 作者简介：
- 基金信息：
- DOI：10.19969/j.fxcsxb.23071802
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郎宇博,李宏达,阎石等.荧光比色传感阵列结合计量学分析TNT、PA、Tetryl、RDX和PETN[J].分析测试学报,2023,42(12):1645-1651.

LANG Yu-bo,LI Hong-da,YAN Shi,et al.Analysis of TNT，PA，Tetryl，RDX，PETN by Fluorescence Colorimetric Sensing Array Combines Metrology[J].Journal of Instrumental Analysis,2023,42(12):1645-1651.
郎宇博,李宏达,阎石等.荧光比色传感阵列结合计量学分析TNT、PA、Tetryl、RDX和PETN[J].分析测试学报,2023,42(12):1645-1651. DOI： 10.19969/j.fxcsxb.23071802.

LANG Yu-bo,LI Hong-da,YAN Shi,et al.Analysis of TNT，PA，Tetryl，RDX，PETN by Fluorescence Colorimetric Sensing Array Combines Metrology[J].Journal of Instrumental Analysis,2023,42(12):1645-1651. DOI： 10.19969/j.fxcsxb.23071802.

摘要

该文根据2，4，6-三硝基甲苯（TNT）、2，4，6-三硝基苯酚（PA）、特屈儿（Tetryl）、环三亚甲基三硝胺（RDX）、季戊四醇四硝酸酯（PETN）的结构和性质合成出5个碳量子点，构筑了荧光比色传感阵列，并基于酶标仪采集的数据，获得荧光比色传感阵列识别TNT、PA、Tetryl、RDX、PETN的指纹图谱。该荧光比色传感阵列具有较好的选择性和抗干扰能力，基本不受其他常见炸药离子的影响。最后，利用主成分分析（PCA）和Q型层次聚类分析（Q-HCA），进一步实现了对上述5种炸药的正确分类，准确率达100%。所建立的方法已成功应用于模拟样品中炸药浓度的测定。

Abstract

This paper synthesized five carbon quantum dots based on the structures and properties of 2，4，6-trinitrotoluene（TNT），2，4，6-trinitrophenol（PA），tetryl，cyclotrimethylenetrinitramine（RDX），and pentaerythritol tetranitrate （PETN）. A fluorescence colorimetric sensing array was constructed，and the fingerprints of TNT，PA，Tetryl，RDX and PETN were obtained using the data collected by microplate reader. The fluorescence colorimetric sensing array has good selectivity and anti-interference ability，which is basically unaffected by other common explosive ions. Finally，the correct classification of the above five explosives was further achieved with an accuracy rate of 100% by using principal component analysis（PCA） and Q-type hierarchical clustering analysis（Q-HCA）. The established method has been successfully applied to the determination of explosive concentration in simulated samples.

关键词

碳量子点荧光比色传感阵列计量学爆炸残留物检测公共安全

Keywords

carbon quantum dotsfluorescence colorimetric sensing arraysmetrologyexplosive residue detectionpublic safety

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Department of Chemistry and Chemical Engineering，Sichuan Institute of Arts and Science

Key Laboratory of Low-cost Rural Environmental Treatment Technology at Sichuan Institute of Arts and Science，Education Department of Sichuan Province

College of Chemistry and Chemical Engineering，Shihezi University

延安大学化学与化工学院

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