Progress of Complex System Process Analysis Based on Modern Spectroscopy Combined With Chemometrics

被引:2
作者
Li, Maogang [1 ]
Cai, Qi [1 ]
Zhang, Tianlong [2 ]
Tang, Hongsheng [2 ]
Li, Hua [1 ,2 ]
机构
[1] Xian Shiyou Univ, Coll Chem & Chem Engn, Xian, Peoples R China
[2] Northwest Univ, Coll Chem & Mat Sci, Key Lab Synthet & Nat Funct Mol, Minist Educ, Xian, Peoples R China
基金
中国国家自然科学基金;
关键词
Chemometrics; complex systems; process analysis; spectrometer; INDUCED BREAKDOWN SPECTROSCOPY; PROCESS ANALYTICAL TECHNOLOGY; NEAR-INFRARED SPECTROSCOPY; QUANTITATIVE-ANALYSIS; CALIBRATION TRANSFER; COMPONENT ANALYSIS; NIR SPECTROSCOPY; ONLINE DETECTION; POWDER FLOW; OPTIMIZATION;
D O I
10.1002/cem.70006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, the role of analytical chemistry has undergone a gradual transformation, evolving from a mere participant to a pivotal decision-maker in process optimisation. This shift can be attributed to the advent of sophisticated analytical instrumentation, which has ushered in a new era of analytical capabilities. This article presents a review of the developments in the application of intelligent analysis techniques, including infrared (IR) spectroscopy, Raman spectroscopy, and laser-induced breakdown spectroscopy (LIBS), in the processing of complex systems over the past decade. The review provides an introduction to the fundamental principles of these analytical techniques and examines the evolution of their instrumentation to accommodate online process monitoring. The analysis of spectral data in complex system processes represents a fundamental aspect of the attainment of on-site quality monitoring, process optimisation and control. Accordingly, the review provides a comprehensive overview of the methodologies employed in process chemometrics, encompassing spectral preprocessing, feature selection, modelling techniques, and optimisation strategies for model performance. Furthermore, this article presents a summary of three intelligent spectral analysis tools, namely infrared spectroscopy, Raman spectroscopy, and LIBS, which are widely employed in process simulation, monitoring, optimisation, and control across multiple disciplines, including the environment, energy, biology, and food. The objective of this review is to provide a valuable reference point and guidance for the further promotion and utilisation of spectral intelligent analysis instruments, with the aim of promoting their in-depth application and development in a greater number of fields.
引用
收藏
页数:20
相关论文
共 132 条
[1]   Characterization of farinographic kneading process for different types of wheat flours using fluorescence spectroscopy and chemometrics [J].
Ahmad, M. Haseeb ;
Nache, Marius ;
Waffenschmidt, Stephanie ;
Hitzmann, Bernd .
FOOD CONTROL, 2016, 66 :44-52
[2]   In-line monitoring and optimization of powder flow in a simulated continuous process using transmission near infrared spectroscopy [J].
Alam, Md Anik ;
Shi, Zhenqi ;
Drennen, James K., III ;
Anderson, Carl A. .
INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2017, 526 (1-2) :199-208
[3]   On-line measure of donkey's milk properties by near infrared spectrometry [J].
Altieri, Giuseppe ;
Genovese, Francesco ;
Admane, Naouel ;
Di Renzo, Giovanni Carlo .
LWT-FOOD SCIENCE AND TECHNOLOGY, 2016, 69 :348-357
[4]   Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data [J].
Balabin, Roman M. ;
Smirnov, Sergey V. .
ANALYTICA CHIMICA ACTA, 2011, 692 (1-2) :63-72
[5]   Process Analytical Chemistry in a Zinc Electroplating Bath: Automatic Sequential Injection for Additives Determination [J].
Barriola, Ainara ;
Gomez, Eduardo ;
Jimenez de Vicuna, Juan A. ;
Ostra, Miren ;
Ubide, Carlos ;
Zuriarrain, Juan .
JOURNAL OF THE ELECTROCHEMICAL SOCIETY, 2012, 159 (11) :H899-H904
[6]   A selective ensemble preprocessing strategy for near-infrared spectral quantitative analysis of complex samples [J].
Bian, Xihui ;
Wang, Kaiyi ;
Tan, Erxuan ;
Diwu, Pengyao ;
Zhang, Fei ;
Guo, Yugao .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2020, 197
[7]   Ensemble calibration for the spectral quantitative analysis of complex samples [J].
Bian, Xihui ;
Diwu, Pengyao ;
Liu, Yirui ;
Liu, Peng ;
Li, Qian ;
Tan, Xiaoyao .
JOURNAL OF CHEMOMETRICS, 2018, 32 (11)
[8]   Monitoring powder blending in pharmaceutical processes by use of near infrared spectroscopy [J].
Blanco, M ;
Bañó, RG ;
Bertran, E .
TALANTA, 2002, 56 (01) :203-212
[9]  
Bratchenko LA, 2025, J RAMAN SPECTROSC, V56, P353, DOI 10.1002/jrs.6764
[10]   Quantitative aspects of inductively coupled plasma mass spectrometry [J].
Bulska, Ewa ;
Wagner, Barbara .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2016, 374 (2079)