Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laser-induced breakdown spectroscopy method

• Published in: Plasma science & technology Vol. 26; no. 9; pp. 95502 - 95510
• Main Authors: HAN, Weiwei, SUN, Duixiong, ZHANG, Guoding, WANG, Honglin, GUO, Kai, ZHANG, Yuzhuo, WANG, Haoliang, ZHANG, Denghong, DONG, Chenzhong, SU, Maogen
• Format: Journal Article
• Language: English
• Published: Plasma Science and Technology 01.09.2024
• Subjects: laser-induced breakdown spectroscopy; multielement; quantitative analysis; standard curve
• ISSN: 1009-0630
• DOI: 10.1088/2058-6272/ad5119

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve (SC) and calibration-free laser-induced breakdown spectroscopy (CF-LIBS) technology to achieve synchronous, rapid, and accurate measurement of elements in a large number of samples, namely, SC-assisted CF-LIBS. Al alloy standard samples, divided into calibration and test samples, were applied to validate the proposed method. SC was built based on the characteristic line of Pb and Cr in the calibration sample, and the contents of Pb and Cr in the test sample were calculated with relative errors of 6% and 4%, respectively. SC built using Cr with multiple characteristic lines yielded better calculation results. The relative contents of ten elements in the test sample were calculated using CF-LIBS. Subsequently, the SC-assisted CF-LIBS was executed, with the majority of the calculation relative errors falling within the range of 2%–5%. Finally, the Al and Na contents of the Al alloy were predicted. The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples. Furthermore, this quantitative analysis method was successfully applied to soil and Astragalus samples, realizing an accurate calculation of the contents of multiple elements. Thus, it is important to advance the LIBS quantitative analysis and its related applications.