荧光
罗丹明
吸光度
材料科学
荧光光谱法
分析化学(期刊)
荧光团
罗丹明6G
吸收(声学)
发射光谱
激光诱导荧光
反应杯
荧光互相关光谱
化学
谱线
光学
色谱法
物理
复合材料
天文
作者
Wanxiang Li,Yuchao Fu,Tianyuan Liu,Haochen Li,Meizhen Huang
标识
DOI:10.1016/j.saa.2022.122147
摘要
Fluorescence spectroscopy is a reliable and widely used analytical method. The fluorescence inner filter effect (IFE) is one of the main obstacles in the application of fluorescence spectroscopy and an error source in fluorescence analysis, resulting in the fluorescence spectrum distortion, the spectral shape distortion, and the nonlinearity between fluorescence intensity and fluorophore concentration. An optimized parameter reflecting the self-absorption effect - the fluorescence attenuation absorption index of secondary inner filter effect (sIFE) nopt - is proposed in this paper. Considering the received fluorescence in a direction perpendicular to the incident light, it is related to the solute–solvent system of the fluorescent substance, neither the geometric parameters of the cuvette and the light beam nor the concentration of the fluorescent substance. nopt can accurately reflect the degree to which the fluorescence is affected by the sIFE and correct for any non-ideality of the shapes of excitation/emission beams. The principle and determination method of nopt are explained in detail. Accordingly, an algorithm for the fluorescence spectroscopic correction by nopt is designed. To verify the method, the fluorescence spectra and absorbance spectra of the solutions of fluorescein sodium, rhodamine B, rhodamine 6G, and chlorophyll-a with a series of concentration gradients were measured, respectively. The influence of solvent effect on sIFE correction was also studied. The experiments show that different solute–solvent systems of the fluorescent substances have their own nopt. The novel algorithm can determine the nopt, correct the intensity attenuation and the peak red-shift of the fluorescence spectrum caused by the sIFE, expand the linear range of the concentration predicted by the fluorescence intensity, reduce the error of the prediction model, and improve the measurement accuracy.
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