Emerging Trends in Laser-Induced Breakdown Spectroscopy: From Plasma Stability to Smart Technology

A special issue of Spectroscopy Journal (ISSN 2813-446X).

Deadline for manuscript submissions: 31 March 2027 | Viewed by 1512

Special Issue Editors


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Guest Editor
Laser Institute, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250014, China
Interests: LIBS; spectral analysis; machine learning; optical fiber sensing; safety monitoring

E-Mail Website
Guest Editor
Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
Interests: laser matter interaction; laser-induced plasmas

Special Issue Information

Dear Colleagues,

Laser-Induced Breakdown Spectroscopy (LIBS) has emerged as a versatile, real-time analytical technique with growing impact across scientific, industrial, and environmental domains. This Special Issue of Spectroscopy Journal will explore recent advances in LIBS, particularly focusing on the dual aspects of fundamental plasma behavior and applied analytical enhancement. Key topics of interest include the characterization and stabilization of transient plasmas, which are critical for reproducibility and quantitative accuracy. The integration of LIBS with complementary spectroscopic techniques (e.g., Raman, absorption spectroscopy)—so-called hyphenated approaches—will also be discussed as a pathway to improved elemental and molecular analysis.

Furthermore, this issue will highlight the transformative role of data science, especially chemometrics and machine learning, in interpreting complex LIBS spectra and enhancing detection limits, classification performance, and calibration models. Contributions addressing industrial-scale LIBS applications, such as material sorting, metallurgy, and process control, are also welcomed.

By drawing together fundamental studies and applied innovations, this issue aims to provide a comprehensive view of the state of the art in LIBS and its future directions in both academic and applied research settings.

Dr. Wenhao Zhang
Dr. Syed Zaheer Ud Din
Guest Editors

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Keywords

  • stability of transient plasmas
  • industrial applications of LIBS
  • hyphenated spectroscopic techniques
  • chemometrics in LIBS analysis
  • machine learning and LIBS

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Published Papers (1 paper)

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Research

19 pages, 7431 KB  
Article
Coal Quality Analysis Based on Laser-Induced Breakdown Spectroscopy
by Rongzhou Zhang, Syed Zaheer Ud Din, Chunling Dang, Xiangming Kong, Rongxin Ma, Jianli Ning, Guangtao Fu, Jiancai Leng and Wenhao Zhang
Spectrosc. J. 2025, 3(4), 32; https://doi.org/10.3390/spectroscj3040032 - 1 Dec 2025
Viewed by 988
Abstract
The study presents a novel approach that integrates laser-induced breakdown spectroscopy (LIBS) data with machine learning algorithms for the rapid evaluation of coal quality. The developed framework enables the determination of three critical parameters: Ash Content (Aad), Carbon Content (Cd [...] Read more.
The study presents a novel approach that integrates laser-induced breakdown spectroscopy (LIBS) data with machine learning algorithms for the rapid evaluation of coal quality. The developed framework enables the determination of three critical parameters: Ash Content (Aad), Carbon Content (Cd), Sulfur Content (Stad). The experimental implementation utilized an optimized dataset to construct and evaluate the predictive model. The LIBS prototype system enables spectral data acquisition under controlled experimental conditions. Data preprocessing is carried out by systematically removing background interference and substrate effects using adaptive filtering techniques. Characteristic emission peaks corresponding to target elements are identified through multivariate analysis, and Partial Least Squares Regression (PLSR) serves as the core algorithm for analysis. Systematic iterative optimization of multivariate preprocessing parameters and adaptive peak selection strategies yields substantial improvements in both predictive accuracy and computational efficiency, with determination coefficients (R2 > 0.90) demonstrated for all target analytes. This enhanced accuracy validates the viability of LIBS as a robust alternative to conventional analytical methods for coal composition analysis. The LIBS demonstrates substantial advantages in coal quality assessment, thereby enhancing the overall efficiency of both coal extraction and quality evaluation processes. Full article
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