LIBS as a Spectral Sensor for Monitoring Metallic Molten Phase in Metallurgical Applications—A Review

Abstract

This review article discusses the latest advances on molten phase monitoring in metallurgical processes by using Laser-Induced Breakdown Spectroscopy (LIBS). LIBS is an analytical laser-based technique, where a pulsed laser is focused on a sample to create a plasma. The optical emission from the plasma can be transferred through open-path optical configuration or via an optical fiber to a spectrometer to receive analytical information in the form of elemental composition. Thus, a relatively long-distance analysis can be performed using LIBS. Several modern experimental arrangements, patents and industrial notes are assessed, and the literature is reviewed. The review includes applications of LIBS to analyze steel, iron, aluminum, copper, slags, metal melts, and other materials. Temperature, pressure, and atmospheric composition are crucial parameters of any melting process. Hence, past studies on molten phases describing these parameters have been discussed. Finally, the review addresses the last technological advances for these types of applications. It also points out the need of development in some fields and some limitations to overcome. In addition, the review highlights the use of modern machine learning and data processing techniques to increase the effectiveness of calibration and quantification approaches. These developments are expected to improve the performance of LIBS systems already implemented at an industrial scale and ease the development of new applications in pyrometallurgical processes to address the stringent market and environmental regulations.

Detection of Al, Mg, Ca, and Zn in copper slag by LIBS combined with calibration curve and PLSR methods

“…On the other hand, Laser-Induced Breakdown Spectroscopy (LIBS) is an atomic emission spectroscopy technology that enables quantitative or qualitative analysis of sample elemental composition. With its remote non-contact detection capabilities, absence of any complex sample pretreatment requirements, rapid analysis speed, simultaneous analysis of multiple elements, lack of radiation, and robust adaptability to harsh environments [4], it has been extensively applied in various fields [5] such as environmental monitoring [6], resource exploration [7][8][9], metal smelting [10], and agricultural production [11].…”

Microstructure classification of steel samples with different heat-treatment processes based on laser-induced breakdown spectroscopy (LIBS)

“…6 Notably, in the realm of industrial inspection, it serves as a discerning instrument for coal analysis, 7 alloy categorization, 8 and metallurgical analysis. 9…”

“…6 Notably, in the realm of industrial inspection, it serves as a discerning instrument for coal analysis, 7 alloy categorization, 8 and metallurgical analysis. 9 In the eld of metallurgical analysis, steel stands as a paramount metallic substance widely utilized in both industrial and everyday settings. A meticulous classication and analysis of this alloy can enhance material selection and optimize process parameters tailored to specic applications.…”

Quantitative analysis of fertilizer using laser-induced breakdown spectroscopy combined with random forest algorithm

“…Compared with the traditional analysis method, LIBS has the advantages of rapidness, real-time assessment (Ding et al, 2020), on-site micro-loss analysis (Qi et al, 2018), remote detection (Agresti et al, 2022), no need for complex sample preparation (Gupta et al, 2020), and simultaneous analysis of multiple elements (Shukla et al, 2022). In recent years, LIBS has been successfully used in geological exploration (Rethfeldt et al, 2021), metallurgical analysis (Myakalwar et al, 2021), medical diagnosis (Alsharnoubi et al, 2020), archaeology (Wallace et al, 2020), environmental monitoring (Ding et al, 2019), and other fields, including fertilizer detection. Danie et al converted liquid fertilizer into a solid and used LIBS to analyze Cu, K, Mg, Mn, Zn, As, Cd, Cr, and Pb contents in the fertilizer, with a detection error of .02%-.06% (Andrade et al, 2017);Sha.…”