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连续运行下拉曼光谱中未极化背景干扰的抑制

Suppression of unpolarized background interferences for Raman spectroscopy under continuous operation.

作者信息

Kim Haisol, Aldén Marcus, Brackmann Christian

出版信息

Opt Express. 2021 Jan 18;29(2):1048-1063. doi: 10.1364/OE.414677.

DOI:10.1364/OE.414677
PMID:33726327
Abstract

A time-resolving filtering technique developed to improve background suppression in Raman spectroscopy is presented and characterized. The technique enables separation of signal contributions via their polarization dependency by the addition of a waveplate to a normal measurement system and data post-processing. As a result, background interferences of broadband laser-induced fluorescence and incandescence, as well as flame luminosity and blackbody radiation, were effectively suppressed from Raman spectra. Experimental setting parameters of the method were investigated under well-controlled conditions to assess their impact on the background-filtering ability, and the overall trend was understood. The fluorescence background was effectively suppressed for all investigated settings of modulation period, number of accumulations, and recording duration, with the spectrum quality preserved after the filtering. For practical application, the method was tested for measurements in a sooting flame accompanied by a strong luminosity and interfering laser-induced background signals. The technique resulted in a 200-fold decrease of the background and allowed for quantitative analyses of concentrations and temperatures from the filtered data. Thus, the method shows strong potential to extend the applicability of Raman spectroscopy, in particular for in situ diagnostics under challenging experimental conditions.

摘要

本文介绍并表征了一种为改善拉曼光谱中的背景抑制而开发的时间分辨滤波技术。该技术通过在常规测量系统中添加一个波片并进行数据后处理,能够根据信号的偏振依赖性分离信号贡献。结果,宽带激光诱导荧光和白炽、火焰发光度以及黑体辐射等背景干扰从拉曼光谱中得到了有效抑制。在严格控制的条件下研究了该方法的实验设置参数,以评估它们对背景滤波能力的影响,并了解总体趋势。对于调制周期、累加次数和记录持续时间的所有研究设置,荧光背景都得到了有效抑制,滤波后光谱质量得以保留。为了实际应用,该方法在伴有强光和干扰激光诱导背景信号的烟炱火焰测量中进行了测试。该技术使背景降低了200倍,并允许从滤波后的数据对浓度和温度进行定量分析。因此,该方法在扩展拉曼光谱的适用性方面显示出强大潜力,特别是在具有挑战性的实验条件下进行原位诊断时。

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