Suppr超能文献

基于差分积分球的光声光谱气体传感

Differential integrating sphere-based photoacoustic spectroscopy gas sensing.

作者信息

Zhang Chu, He Ying, Qiao Shunda, Ma Yufei

出版信息

Opt Lett. 2023 Oct 1;48(19):5089-5092. doi: 10.1364/OL.500214.

Abstract

In this Letter, a differential integrating sphere-based photoacoustic spectroscopy (PAS) gas sensor is proposed for the first time to our knowledge. The differential integrating sphere system consists of two integrating spheres and a tube. Based on differential characteristics, the photoacoustic signal of the designed differential integrating sphere was doubly enhanced and the noise was suppressed. Compared with a single channel integrating sphere, the differential integrating sphere sensing system had a 1.86 times improvement in signal level. An erbium-doped fiber amplifier (EDFA) was adopted to amplify the output of diode laser to enhance the optical excitation. The second harmonic (2f) signal of differential integrating sphere-based acetylene (CH) PAS sensor with an amplified 1000 mW optical output power was 104.67 mV, which was 22.80 times improved compared to the sensing system without EDFA. When the integration time was 100 s, the minimum detection limit (MDL) of the differential integrating sphere-based CH PAS sensor was 416.7 ppb. The differential integrating sphere provides a new method, to the best of our knowledge, for the development of PAS sensor, which has the advantages of photoacoustic signal enhancement, strong noise immunity, and no need for optical adjustment.

摘要

据我们所知,本文首次提出了一种基于差分积分球的光声光谱(PAS)气体传感器。差分积分球系统由两个积分球和一根管子组成。基于差分特性,所设计的差分积分球的光声信号得到了双重增强,噪声得到了抑制。与单通道积分球相比,差分积分球传感系统的信号电平提高了1.86倍。采用掺铒光纤放大器(EDFA)对二极管激光器的输出进行放大,以增强光激发。基于差分积分球的乙炔(CH)PAS传感器在光输出功率放大到1000 mW时的二次谐波(2f)信号为104.67 mV,与无EDFA的传感系统相比提高了22.80倍。当积分时间为100 s时,基于差分积分球的CH PAS传感器的最低检测限(MDL)为416.7 ppb。据我们所知,差分积分球为PAS传感器的开发提供了一种新方法,具有光声信号增强、抗噪声能力强和无需光学调整等优点。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验