摘要
2,4,6‑三硝基甲苯(TNT)是军事活动中最重要的武器能源体,其不仅具有强大的毁伤作用,同时还具有化学毒性,即使是痕量的TNT,也会对自然环境、人类健康造成严重威胁。因此,发展具有高灵敏、高准确性、快响应的痕量炸药检测技术,对保护生态环境、维护人类健康具有深远研究意义。在众多痕量检测技术中,生物传感技术具有选择性好,合成简单,响应快,灵敏度高等优势,具有良好的应用前景。本文综述了近年来生物传感技术在痕量炸药检测中的研究进展,重点讨论了抗体免疫、肽、适配体、酶以及多参量加载5大类生物传感器的优势以及局限性。其中基于适配体制备的传感器对炸药分子具有良好的亲和力以及特异性,检出限相较于其他几类传感器低1000倍,且稳定性良好,易于改造修饰,结构拓展能力强。今后研究的重点为基于适配体等生物受体元件构筑的高通量痕量炸药传感系统,结合神经网络算法,机器学习技术,构筑具有多重检测以及仿生遥感性能的痕量炸药生物传感技术。
Explosive TNT is the most important weapon energy source in military activities.It not only has a powerful damaging effect,but also has chemical toxicity.Even a trace amount of TNT will pose a serious threat to the natural environment and human health.Therefore,the development of trace explosive detection technology with high sensitivity,high accuracy and fast response has far‑reaching research significance for protecting the ecological environment and maintaining human health.Among many trace detection technologies,biosensing technology has the advantages of good selectivity,simple synthesis,fast response and high sensitivity,and has good application prospects.This paper reviews the research progress of biosensor technology in the detection of trace explosives in recent years,focusing on the advantages and limitations of five types of biosensors:antibody im‑munity,peptides,aptamers,enzymes and multi‑parameter loading.Among them,the sensor prepared based on aptamer has good affinity and specificity for explosive molecules,the detection limit is 1000 times lower than other types of sensors,and has good stability,easy modification and modification,and strong structural expansion ability.Future research will focus on the construction of high‑throughput trace explosives sensing systems based on bioreceptor components such as aptamers,combined with neural network algorithms and machine learning to construct biosensors with multiple detection and bionic remote sensing properties.
作者
王子寒
刘伟
施玲艳
何璇
崔升
WANG Zi-han;LIU Wei;SHI Ling-yan;HE Xuan;CUI Sheng(Institute of Chemical Materials,CAEP,Mianyang 621999,China;College of Materials Science and Engineering,Nanjing Tech University,Nanjing 211800,China)
出处
《含能材料》
EI
CAS
CSCD
北大核心
2022年第10期1047-1054,共8页
Chinese Journal of Energetic Materials
基金
中国工程物理研究院院长基金(YZJJLX2020004)。
关键词
炸药检测
生物传感
多参量加载
特异性
高灵敏
explosives detection
biosensors
multi‑parameter loading
specificity
high sensitivity