Issue 2, 2023

Applying plasma acoustic and image information for underwater LIBS normalization

Abstract

Improving the stability of underwater LIBS is a key point for its practical use in oceanic applications. The traditional normalization method of using the internal standard element is often limited in some practical cases due to the lack of a suitable element as a reference. In this study, we compared three external normalization strategies by using plasma acoustic signals, plasma images, and the acoustic-image combination. The acoustic signals were measured with two types of hydrophone (needle hydrophone and spherical hydrophone), and the plasma images were recorded with a low-cost CCD camera. The characteristics of the acoustic signals were studied first, and the correlations of the acoustic intensities and image intensities with the LIBS spectral intensities were analyzed. Then, three normalization models were established respectively based on the acoustic data, image data, and acoustic-image combined data using the partial least squares regression (PLSR). It shows that acoustic normalization has a comparable performance on the reduction of spectral fluctuation versus image normalization, while the acoustic-image combined normalization works more efficiently than using the acoustic or image normalization only. Calibration curves of Mn, Sr, and Li were also built with the three normalization methods, and the obtained results demonstrated the availability of applying plasma acoustic signals and plasma images in improving the analytical performances of underwater LIBS.

Graphical abstract: Applying plasma acoustic and image information for underwater LIBS normalization

Article information

Article type
Paper
Submitted
08 Oct 2022
Accepted
13 Dec 2022
First published
14 Dec 2022

J. Anal. At. Spectrom., 2023,38, 281-292

Applying plasma acoustic and image information for underwater LIBS normalization

B. Wang, W. Song, Y. Tian, Y. Lu, Y. Li, J. Guo, W. Ye and R. Zheng, J. Anal. At. Spectrom., 2023, 38, 281 DOI: 10.1039/D2JA00329E

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