|
|
|
|
|
|
Rapidly Detection of Chemical Warfare Agent Simulants by Surface Enhanced Raman Spectroscopy |
ZHANG Lin1, WEN Bao-ying2, LIU Wei-wei1, FU Wen-xiang1, KONG Jing-lin1*, LI Jian-feng2* |
1. State Key Laboratory of NBC Protection for Civilian, Beijing 102205, China
2. State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China |
|
|
Abstract Nerve chemical agents have the characteristics of high toxicity, good volatility and fast action, which can cause great casualties in the case of low concentration, so it becomes difficulty to rapid detection in the field. The chemical poison Sarin (Isopropyl Mefluronate, GB) is a commonly used military neurotoxic agent, which can destroy the function of the nervous system by inhibiting acetylcholinesterase, and the degradation rate in the human body is very slow. Based on this, to avoid and reduce the pollution of such poisons and harm to personnel, it is urgent to develop a detection technology with high sensitivity, good accuracy, short response time and portability to detect GB. There are many methods for detecting chemical poisons and their simulants, including spectroscopy, chromatography, surface acoustic wave (SAW) sensors and so on. However, the above methods generally have long response time, poor accuracy, and low detection sensitivity. Therefore, the development of a highly sensitive, simple and fast spectroscopic technique to detect GB has become an important task in chemical weapons detection. Surface-enhanced Raman spectroscopy (SERS) is one of the effective methods to detect trace chemical agents in water due to its high sensitivity, simple operation and fast response time. In this paper, the purchased Ag nano-sol is centrifuged and then assembled on the surface of the silicon-based Au film to prepare a high SERS enhanced substrate to quickly detect the chemical toxicant simulant dimethyl methyl phosphate (DMMP). In the experiment, the detection conditions were optimized and screened by optimizing the ionic strength of the agglomerating agent, test methods and other conditions. By comparing different agglomerating agents HCl, KI, MgSO4, NaCl and NaOH, the optimal ionic strength is finally obtained, and it is determined that 1 mol·L-1 KI has the best effect as the agglomerating agent. In addition, different detection methods were optimized accordingly. By comparing the solid substrate method and the liquid sol method, it was finally found that the improved chip method can obtain better detection results. The final detection method is to mix 1 mol·L-1 of KI with the solution to be measured (DMMP), and then drop it on a pre-prepared SERS chip made of Ag nano-sol as a matrix, using a portable laser with a wavelength of 785 nm Raman directly performs detection, and it can measure as low as 10 μg·L-1. However, it is reported in the literature that the US military’s short-term (less than 7 days) drinking water maximum exposure safety guidelines stipulate that the limit of detection for neurochemical poisons is 10 μg·L-1. Therefore, using this SERS detection method meets the military’s response to chemical warfare or The need for terrorist attacks. The experimental results show that this method breaks through the limitation of the low sensitivity of portable Raman spectrometer, solves the problem of rapid detection of trace nerve agents on-site, and expands the application of SERS technology in the field of chemical reconnaissance.
|
Received: 2020-12-23
Accepted: 2021-03-09
|
|
Corresponding Authors:
KONG Jing-lin, LI Jian-feng
E-mail: jlkong@sina.com;Li@xmu.edu.cn
|
|
[1] Lakshmi K, Mathusalini S, Arasakumar T, et al. Journal of Materials Science: Materials in Electronics,2017, 28(17): 12944.
[2] NAN Di-na, FU Wen-xiang, LI Bao-qiang, et al(南迪娜, 傅文翔, 李宝强, 等). Environmental Chemistry(环境化学), 2020, 39(7): 1949.
[3] Chong Eugene, Park Byeonghwang, Kim Ju Hyun. Journal of the Korea Institute of Military Science and Technology,2014, 17(1): 8.
[4] Davide Barreca, Alberto Gasparotto, Filippo Gri, et al. Advanced Materials Interfaces,2018, 5(23): 1800792.
[5] ISABEL Sayago, DANIEL Matatagui, MARíA Jesús Fernández, et al. Talanta,2016, 148: 393.
[6] XUE Chang-guo, TANG Yu, LI Shi-qin, et al(薛长国, 唐 毓, 李世琴, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2020, 40(12): 3722.
[7] YANG De-hong, ZHANG Lei-lei, ZHU Cheng(杨德红, 张雷蕾, 朱 诚). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2020, 40(10): 3048. |
[1] |
FU Qiu-yue1, FANG Xiang-lin1, ZHAO Yi2, QIU Xun1, WANG Peng1, LI Shao-xin1*. Research Progress of Pathogenic Bacteria and Their Drug Resistance
Detection Based on Surface Enhanced Raman Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1339-1345. |
[2] |
FU Ying-ying, ZHANG Ping, ZHENG Da-wei , LIN Tai-feng*, WANG Hui-qin, WU Xi-hao, SONG Jia-chen. Preparation and SERS Performance of Au-Nylon Flexible Membrane Substrate[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 692-698. |
[3] |
SONG Hong-yan, ZHAO Hang, YAN Xia, SHI Xiao-feng, MA Jun*. Adsorption Characteristics of Marine Contaminant Polychlorinated Biphenyls Based on Surface-Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 704-712. |
[4] |
XU Yang1, LEI Lei2, YAN Jun1*, CHEN Yu-yun1, TAN Xue-cai1, LIU Yu-qian1, WANG Qi3. Determination of Glutaraldehyde in Water by Surface Enhanced Raman Spectroscopy Based on Metal Organic Framework Composite Substrate[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(01): 115-123. |
[5] |
SHI Si-qian, YANG Fang-wei, YAO Wei-rong, YU Hang, XIE Yun-fei*. Rapid Detection of Levamisole Residue in Pork by Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3759-3764. |
[6] |
QIU Meng-qing1, 2, XU Qing-shan1*, ZHENG Shou-guo1*, WENG Shi-zhuang3. Research Progress of Surface-Enhanced Raman Spectroscopy in Pesticide Residue Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(11): 3339-3346. |
[7] |
TAN Ai-ling1, ZHAO Rong1, SUN Jia-lin1, WANG Xin-rui1, ZHAO Yong2*. Detection of Chlorpyrifos Based on Surface-Enhanced Raman Spectroscopy and Density Functional Theory[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(11): 3462-3467. |
[8] |
ZHANG Yan-jun, KANG Cheng-long, LIU Ya-qian, FU Xing-hu*, ZHANG Jin-xiao, WANG Ming-xue, YANG Liu-zhen. Rapidly Detection of Total Nitrogen and Phosphorus Content in Water by Surface Enhanced Raman Spectroscopy and GWO-SVR Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3147-3152. |
[9] |
JIN Xiang-peng, LI Xing-jia, ZHANG Chen-jie, YUAN Ya-xian, YAO Jian-lin*. Surface Enhanced Raman Spectroscopic Investigation on SPR Catalyzed Decarboxylation of Ortho-Mercaptobenzoic Acid at Au Nanoparticles Monolayer Film[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3153-3158. |
[10] |
ZOU Jing-xin1, LIU Yan-qin1, YUAN Ming-zhe1, WANG Qi-hang1, FAN Zhou2, WAN Fu3. Study on the Raman Spectral Characteristics in Ageing Condition Discrimination of Oil-Paper Insulation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(10): 3159-3165. |
[11] |
LIU Yan-mei1, PEI Yuan1, LI Bo2, LI Hui-yan3, WANG Xue-pei4, XIAN Hao-han1, WEI Ying-na4, CHEN Ying5, DI Zhi-gang6, WU Zhen-gang1*, WEI Heng-yong4*. Preparation of Gold/Silver/Titanium Nitride Suface-Enhanced Raman Substrate and Its Effect on Nicotinic Acid Quantitative Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(07): 2092-2098. |
[12] |
NAN Di-na, DONG Li-qiang, FU Wen-xiang, LIU Wei-wei, KONG Jing-lin*. Fast Identification of Hazardous Liquids Based on Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(06): 1806-1810. |
[13] |
XU Ning1, 2, LIU Mu-hua1, 2, YUAN Hai-chao1, 2, HUANG Shuang-gen1, 2, WANG Xiao1, 2, ZHAO Jin-hui1, 2*, CHEN Jian1, 2, WANG Ting1, 2, HU Wei1, 2, SONG Yi-xin1, 2. Rapid Identification of Sulfamethazine and Sulfadiazine Residues in Chicken Based on SERS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(03): 924-931. |
[14] |
SHEN Zheng-dong, KONG Xian-ming*, YU Qian, YANG Zhan-xu. Research Progress of Thin Layer Chromatography and Surface Enhanced Raman Scattering Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(02): 388-394. |
[15] |
YAN Shuai1, LI Yong-yu1*, PENG Yan-kun1, LIU Ya-chao1, HAN Dong-hai2. A Method for Correcting Nitrofurantoin Raman Signal in Honey Based on Internal Standard of Substrate[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(02): 546-551. |
|
|
|
|