Task-Oriented Comparison and Fusion of Spectra and Acoustic Signals in LIBS for Alloy Analysis: From Identification to Quantitative Measurement

Huiping Chai; Xuechen Niu; Honghua Ma; Deng Zhang; Lianbo Guo

doi:10.1039/d5ja00485c

January 1, 2026Journal of Analytical Atomic Spectrometry

Task-Oriented Comparison and Fusion of Spectra and Acoustic Signals in LIBS for Alloy Analysis: From Identification to Quantitative Measurement

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Key Points

This research aims to enhance alloy analysis by integrating spectra and acoustic signals from LIBS.
Utilized laser-induced breakdown spectroscopy for elemental analysis of alloys.
Compared traditional spectral data with acoustic signal data.
Implemented machine learning techniques to fuse both data types for better accuracy.
Improved identification of alloy compositions compared to using spectra alone.
Quantitative measurements showed increased precision through data fusion.
Demonstrated effective utilization of acoustic signals for enhancing analysis accuracy.

Implication

Experimental approach combines spectra and acoustic signals to enhance alloy characterization, indicating improved measurement accuracy.

Abstract

Laser-induced breakdown spectroscopy (LIBS) has been widely applied in alloy elemental analysis. However, reliance solely on spectra makes it difficult to fully capture all the information related to the laser-material...

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Cite This Study

Chai et al. (2026) studied this question.

synapsesocial.com/papers/69bb926a496e729e6297fa88 https://doi.org/10.1039/d5ja00485c

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Task-Oriented Comparison and Fusion of Spectra and Acoustic Signals in LIBS for Alloy Analysis: From Identification to Quantitative Measurement

Key Points

Implication

Abstract

Discussion

Cite This Study

Task-Oriented Comparison and Fusion of Spectra and Acoustic Signals in LIBS for Alloy Analysis: From Identification to Quantitative Measurement

Key Points

Implication

Abstract

Discussion

Cite This Study

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