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基于轮线的图像模式识别技术用于光激发-发射矩阵图的解释:质量和量化

Xiulian Yin¹, Yingjin Li¹, Mingjie Wei²

¹School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, PR China.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

|July 30, 2025

概括

一种新的光谱检索方法,CLIPR,解释光EEM光谱用于环境监测. 这种技术在识别和量化污染物方面达到很高的准确性,证明了未来应用的稳定性和通用性.

科学领域:

分析化学分析化学
频谱学是一种光谱学.
环境科学环境科学

背景情况:

光谱检索对于光谱分析至关重要,但对于光激发发射矩阵 (EEM) 光谱学缺乏进展.
在环境监测中,EME光谱被广泛使用.

研究的目的:

开发一种先进的光谱检索方法来解释EEM光谱.
为了提高消除噪声,特征提取和EEM数据的图像检索的准确性和效率.

主要方法:

开发了基于轮线的图像模式识别 (CLIPR) 技术.
实现了一个三级检索机制 (Lib1,Lib2,Lib3).
使用模型污染物和MOF-74 (Zn) 与28x4 EEM地图图像以及留出一个漏洞的交叉验证来验证该方法.

主要成果:

对于验证集 (>50μM),CLIPR实现了>79.61%的类内相似性和98.81%的准确性.
最好的定量结果显示RMSE/True值为3.09%,PhNH2-S1.1.的R2为0.99.
在特定度值下的未知样本集 (第1批>35μM,第2批>50μM) 中,获得了100%的识别精度.

结论:

该CLIPR方法证明了稳定性和概括能力,用于解释EEM光谱信息.
开发的光谱检索方法对于EEM数据分析是可行的.
这项工作为在EEM光谱分析中大规模准备参考数据奠定了基础.

关键词:

3D光光谱 3D光光谱在EMM的轮线上.图像模式识别图像模式识别频谱检索频谱检索

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