Abstract Colorimetric, selective and sensitive screening of explosives is important not only to military action but also to public security. Normal explosives detection is mainly targeted for nitroaromatic compounds, however, ntiramine explosive is used more widely due to its outstanding performance. Herein, molecularly imprinted photonic crystal (MIPC) sensors were made to detect typical nitramine explosives: 1,3,5-trinitro-1,3,5-triazacyclohexane (RDX), cyclotetramethylenete-tranitramine (HMX) and 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20). And 2,4,6-trinitrotoluene (TNT) templated MIPC was also made to discriminate not only nitramines but also nitrobenzene explosives. With explosives concentration increase, the diffraction peak and structure color of MIPC sensors both red shifted within 5 min. By adding alkaline solution, the MIPC sensors were softened, and the mass transfer and the sensitivity were improved. The MIPC sensors could respond to lower than 0.05 mM explosives with the limit of detection of 0.01 mM. A MIPC sensor array with the above MIPCs was constructed to achieve a semi-quantitative detection, and Pattern Recognition with a 48 × 4 multivariate data matrix was using to discriminate different explosive molecules. According to principal component analysis, the response of RDX, HMX, CL-20 and TNT scattered in separate areas, and the sensor array could discriminate with a LOD of 1 mM.

中文翻译：

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分子印迹光子晶体阵列比色筛选硝胺炸药

摘要 爆炸物的比色、选择性和灵敏筛选不仅对军事行动而且对公共安全都很重要。普通爆炸物检测主要针对硝基芳香族化合物，而尼拉敏爆炸物因其优异的性能而得到更广泛的应用。在本文中，分子印迹光子晶体 (MIPC) 传感器用于检测典型的硝胺炸药：1,3,5-三硝基-1,3,5-三氮杂环己烷 (RDX)、环四亚甲基三硝胺 (HMX) 和 2,4,6， 8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20)。还制作了 2,4,6-三硝基甲苯 (TNT) 模板化 MIPC，不仅可以识别硝胺，还可以识别硝基苯炸药。随着炸药浓度的增加，MIPC传感器的衍射峰和结构颜色均在5分钟内发生红移。通过加入碱性溶液，MIPC 传感器软化，传质和灵敏度提高。MIPC 传感器可以响应低于 0.05 mM 的爆炸物，检测限为 0.01 mM。构建具有上述 MIPC 的 MIPC 传感器阵列以实现半定量检测，并使用具有 48 × 4 多元数据矩阵的模式识别来区分不同的爆炸物分子。根据主成分分析，RDX、HMX、CL-20 和 TNT 的响应分散在不同的区域，传感器阵列可以以 1 mM 的 LOD 进行区分。构建了具有上述 MIPC 的 MIPC 传感器阵列以实现半定量检测，并使用具有 48 × 4 多元数据矩阵的模式识别来区分不同的爆炸物分子。根据主成分分析，RDX、HMX、CL-20 和 TNT 的响应分散在不同的区域，传感器阵列可以以 1 mM 的 LOD 进行区分。构建具有上述 MIPC 的 MIPC 传感器阵列以实现半定量检测，并使用具有 48 × 4 多元数据矩阵的模式识别来区分不同的爆炸物分子。根据主成分分析，RDX、HMX、CL-20 和 TNT 的响应分散在不同的区域，传感器阵列可以以 1 mM 的 LOD 进行区分。