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Recent Advances in Laser-induced Breakdown Spectroscopy Quantification: From Fundamental Understanding to Data Processing

Zhe Wang received his Ph.D. in mechanics engineering from The Pennsylvania State University in 2007 and then joined the faculty of Tsinghua University. He devoted his academic career towards promoting laser-induced breakdown spectroscopy (LIBS) in real industrial application by focusing on improving its quantification performance. He published more than 90 peer reviewed papers and holds over 30 patents.  He is the deputy director and general secretary of the LIBS committee of Chinese Society of Optical Engineering and initiated LIBS Summit in 2019

Recent Advances in Laser-induced Breakdown Spectroscopy Quantification: From Fundamental Understanding to Data Processing

Laser-induced breakdown spectroscopy (LIBS) is regarded as the future superstar for chemical analysis, but the relatively high measurement uncertainty and error remain the persistent challenges for its technological development as well as wide applications. In this presentation, I will summarize the generation mechanisms of measurement uncertainty and explain how signal uncertainty and matrix effects impact quantification performance. Furthermore, I will discuss the methods for raw signal improvement including sample preparation, system optimization, and especially plasma modulation, which modulates the laser-induced plasma evolution process for higher signal repeatability and signal-to-noise ratio. I will also discuss different mathematical quantification methods including calibration-free methods and calibration methods, which can be classified into physical-principle based calibration model, data-driven based calibration model, and hybrid model. Finally, I will summarize and recommend a framework of quantification improvement strategy including key steps and main way-out for LIBS future development.

Learning objectives:

  • Mechanisms of signal uncertainty generation
  • Impact of matrix effect and signal uncertainty on quantification performance
  • Systematic summary of raw signal improvement methods and mathematical quantification models
  • Framework of quantification improvement strategy for future development

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Category: Andor Academy

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