首页|化学计量学赋能现代光谱分析技术—理论、仪器和应用进展

化学计量学赋能现代光谱分析技术—理论、仪器和应用进展

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近些年,现代光谱分析技术与时代发展特征(如人工智能、大数据、云计算和物联网等)的结合越来越紧密,已被广泛地用于农业、食品、制药、石化、冶金和地质等领域,在一些领域取得了规模化的应用成效,为科技和经济的发展做出了贡献.本文主要介绍结合化学计量学的现代光谱分析技术的构成和特点,总结用于光谱定量和定性分析的化学计量学方法与进展.基于典型实例,分不同的应用场景介绍了现代光谱分析技术在不同领域的应用现状,如原油快评、种粒筛选、口岸铁矿石分类等实验室高通量分析场景;土壤检测、矿产勘探、水果采摘判断、司法鉴定等现场快速分析场景;汽油调和、冶炼过程物料分析、煤质在线分析、废塑料分类等工业在线分析场景.未来,以光谱仪微型化、光谱新理论的深入研究、深度学习算法与光谱技术的深入结合为基础,精细农业、智能工厂、精准医疗和智慧环保等领域的快速发展为现代光谱分析技术提供了强大的牵引力量,将会带来更多的创新和先进的应用.
Modern spectral analysis technology empowered by chemometrics:Theory,instrument and application progress
In recent years,the integration of modern spectroscopic analysis technologies with development characteristics of the times(such as artificial intelligence,big data,cloud computing and the internet of things)is closer and closer,and it has been widely used in various fields including agriculture,food,petro-chemicals,petrochemical engineering,metallurgy and geology.Some large-scale application achievements have been obtained in several fields,which makes a contribution to the development of technology and e-conomy.This paper mainly introduces the constitution and characteristics of modern spectroscopic analysis technologies integrated with chemometrics,and summarizes the chemometric methodologies and advance-ments employed for quantitative and qualitative analysis in spectroscopy.Based on some representative in-stances,the application status of modern spectroscopic analysis technologies in various fields were intro-duced according to the application scenarios,for example,the laboratory high-throughput analysis scenarios such as rapid crude oil evaluation,grain sorting and port iron ore classification;on-site rapid analysis sce-narios such as soil detection,mineral exploration,fruit picking assessment,and forensic identification;the industrial on-line analysis scenarios such as gasoline blending,smelting process material analysis,on-line coal quality analysis,and waste plastic classification.In the future,grounded in the miniaturization of spec-trometers,in-depth exploration of new spectroscopic theories,and the profound amalgamation of deep learning algorithms with spectroscopic technology,the rapid developments in precision agriculture,smart facto-ries,precision medicine,and intelligent environmental protection will offer robust impetus for the progressive evolu-tion of modern spectroscopic analysis technologies,thus heralding further innovations and advancements.

chemometricsmachine learningnear infrared spectroscopy(NIR)Raman spectroscopylaser-induced breakdown spectroscopy(LIBS)on-site analysison-line analysis

李敬岩、褚小立、陈瀑、许育鹏、刘丹

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中石化石油化工科学研究院有限公司,北京 100083

化学计量学 机器学习 近红外光谱(NIR) 拉曼光谱(Raman) 激光诱导击穿光谱(LIBS) 现场分析 在线分析

2024

冶金分析
中国钢研科技集团有限公司(钢铁研究总院) 中国金属学会

冶金分析

CSTPCD北大核心
影响因子:1.124
ISSN:1000-7571
年,卷(期):2024.44(10)