面向无机炸药痕量检测的ZnS量子点气敏性能的掺杂调控及机理研究

Due to the complex composition and low volatility of inorganic explosives, the on-site detection of them has been a worldwide problem up to now. In order to achieve the highly sensitive, identifiable detection towards four types of inorganic explosives and the six main ingredients at room temperature, it is proposed to tailor the defect sites, the oxygen adsorption volume, the surface potential barrier as well as the space-charge-layer thickness of ZnS quantum dots by in-situ doping transition metal ions, alkali metal ions and halogen ions. Thus, not only the sensitivity and selectivity towards inorganic explosives would be improved, but also the response time and the working temperature of ZnS quantum dots-based resistive gas sensors would be reduced. At the same time, the tailoring mechanisms of the sensing properties and and the structure of ZnS quantum dots by doping will be discussed. Finally, the ZnS quantum dots-based sensory array will be built, and according to the principal component analysis method, the identifiable detection towards inorganic explosives and its six main ingredients will be achieved. This study will not only enrich the knowledge of gas-sensing properties tailoring of semiconductor quantum dots by in situ doping, but also expand the application of ZnS quantum dots to the field of room-temperature trace detection. Most important of all, this study will shine light on the on-site detection of inorganic explosives.

无机炸药由于成分复杂、挥发性低，其现场检测一直是一个世界难题。为实现室温下对常见四类无机炸药及其六种主要成分的高灵敏、可识别检测，本项目拟在ZnS量子点电阻式气敏传感检测的基础上，通过原位掺杂过渡金属离子、碱金属离子和卤素离子，调控ZnS量子点表面的缺陷位点、氧离子吸附量、表面势垒以及电子耗尽层深度，进而提高基于ZnS量子点的电阻型气敏传感器对无机炸药的灵敏度和选择性，降低其工作温度和响应时间。深入分析掺杂对ZnS量子点结构和气敏性能的调控机理以及掺杂ZnS量子点对无机炸药的响应机理。构建基于ZnS量子点的气敏传感器阵列，并根据主成分法分析，实现对常见无机炸药及其主要成分的可识别检测。本项目的实施将深化掺杂对半导体量子点气敏性能调控机理的认识，使ZnS量子点的应用拓展到室温下的电阻型气敏检测领域，而且为无机炸药的可识别检测提供新的思路和方法。

首先，针对纯的金属硫化物半导体作为传感材料灵敏度低、响应速度慢等缺点，本项目利用Mn2+掺杂对ZnS 纳米晶（NCs）的表面氧吸附量、载流子浓度及电子耗尽层进行调控，合成Mn2+掺杂的ZnS NCs传感材料，制备了基于ZnS NCs的传感器阵列，研究了Mn2+掺杂对ZnS NCs基传感器对制式爆炸物三硝基甲苯（TNT）、二硝基甲苯（DNT）以及非制式爆炸物尿素（Urea）、高锰酸钾（PP）、硝酸钾（PN）、农用尿素化肥（UF）和黑火药（BP）的响应性能的影响，并对其响应机理进行了分析，首次实现了在室温下对制式爆炸物TNT、DNT以及非制式爆炸物Urea、PP、PN、UF、BP、FC和火柴识别检测，检测响应时间不超过13秒，并对其气敏性能的调控机理进行了分析。其次，针对薄膜传感器敏感材料团聚导致的灵敏度低以及单根纳米线传感器制备工艺复杂、稳定性低、重复性差等问题，本项目采用分级结构设计和表面态掺杂调控的协同方案，研究了调控方案和构建基于分级结构ZnS薄膜型传感器阵列的可行性，实现了对制式爆炸物TNT、DNT以及非制式爆炸物及其原料Urea、PP、PN、SP、UF和BP气氛的识别检测，检测响应时间不超过5s。再者，针对大气中臭氧和水蒸汽对检测信号的干扰，探索了在物联网、大数据、图像识别等技术快速发展的背景下，对气敏传感器的抗干扰能力、检测灵敏度和应用前景进行了深入的研究，实现在14秒内对O3和NO2等多种分析物的识别检测。最后基于本项目，共发表SCI文章2篇，申请国家发明专利2项，协助培养硕士研究生2名，完成了项目提出的预期目标。