Suppr超能文献

利用腔增强拉曼光谱技术进行环境安全监测的有害气体检测。

Hazardous Gas Detection by Cavity-Enhanced Raman Spectroscopy for Environmental Safety Monitoring.

机构信息

Chongqing University State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing 400044, China.

State Grid Jiangsu Electric Power Company Changzhou Power Supply Company, Jiangsu, Nanjing 213000, China.

出版信息

Anal Chem. 2021 Nov 23;93(46):15474-15481. doi: 10.1021/acs.analchem.1c03499. Epub 2021 Nov 14.

Abstract

We demonstrate the practicability of cavity-enhanced Raman spectroscopy (CERS) with a folded multipass cavity as a unique tool for the detection of hazardous gases in the atmosphere. A four-mirror Z-sharped multipass cavity results in a greatly extended laser-gas interaction length to improve the Raman signal intensity of gases. For Raman intensity maximization, the optimal number of intracavity beams of a single reflection cycle is calculated and then the cavity parameters are designed. A total of 360 intracavity beams are realized, which are circulated four times in the cavity based on the polarization. ppb-Level Raman gas sensing at atmospheric pressure for several typical explosive gases and toxic gases in ambient air, including hydrogen (H), methane (CH), carbon monoxide (CO), hydrogen sulfide (HS), and chlorine (Cl), is achieved at 300 s exposure time. Our CERS apparatus, which can detect multiple gases simultaneously with ultrahigh sensitivity and high selectivity, is powerful for detecting hazardous gases in the atmosphere, and it has excellent potential for environmental safety monitoring.

摘要

我们展示了具有折叠多通腔的腔增强拉曼光谱(CERS)的实用性,该腔作为一种独特的工具可用于检测大气中的有害气体。四镜 Z 形多通腔可大大延长激光-气体相互作用长度,从而提高气体的拉曼信号强度。为了实现拉曼强度最大化,计算了单个反射循环中腔内光束的最佳数量,然后设计了腔参数。总共实现了 360 个腔内光束,这些光束基于偏振在腔内循环四次。在 300 秒的暴露时间内,可在大气压力下对环境空气中的几种典型爆炸气体和有毒气体(包括氢(H)、甲烷(CH)、一氧化碳(CO)、硫化氢(HS)和氯(Cl))进行 ppb 级别的拉曼气体传感。我们的 CERS 仪器具有超高灵敏度和高选择性,可同时检测多种气体,非常适合检测大气中的有害气体,在环境安全监测方面具有巨大的潜力。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验