Hu Zhenlin, Chen Feng, Zhang Deng, Chu Yanwu, Wang Weiliang, Tang Yun, Guo Lianbo
Wuhan National Laboratory for Optoelectronics (WNLO), Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
School of Physics and Electronics Science, Hunan University of Science and Technology, Xiangtan, Hunan, 411201, China.
Anal Chim Acta. 2021 Oct 23;1183:339008. doi: 10.1016/j.aca.2021.339008. Epub 2021 Sep 1.
The existence of the self-absorption effect results in a nonlinear relationship between spectral intensity and elemental concentration, which dramatically affect the quantitative accuracy of laser-induced breakdown spectroscopy (LIBS), especially calibration-free LIBS (CF-LIBS). In this work, the CF-LIBS with columnar density and standard reference line (CF-LIBS with CD-SRL) was proposed to improve the quantitative accuracy of CF-LIBS analysis by exploiting self-absorption. Our method allows using self-absorbed lines to perform the calibration-free approach directly and does not require self-absorption correction algorithms. To verify this method, the experiment was conducted both on aluminium-bronze and aluminium alloy samples. Compared with classical CF-LIBS, the average errors (AEs) of CF-LIBS with CD-SRL were decreased from 3.20%, 3.22%, 3.15% and 3.01%-0.95%, 1.00%, 1.16% and 1.78%, respectively for four aluminium-bronze alloy samples. The AEs were decreased from 0.66%, 0.70%, 0.89% and 1.30%-0.43%, 0.61%, 0.77% and 0.33%, respectively for four aluminium alloy samples. The experimental results demonstrated that CF-LIBS with CD-SRL provided higher quantitative accuracy and stronger adaptability than classical CF-LIBS, which is quite helpful for the practical application of CF-LIBS.
自吸收效应的存在导致光谱强度与元素浓度之间呈现非线性关系,这极大地影响了激光诱导击穿光谱技术(LIBS)的定量准确性,尤其是无标样激光诱导击穿光谱技术(CF-LIBS)。在这项工作中,提出了具有柱状密度和标准参考线的CF-LIBS(CF-LIBS with CD-SRL),以通过利用自吸收来提高CF-LIBS分析的定量准确性。我们的方法允许直接使用自吸收谱线来执行无标样方法,并且不需要自吸收校正算法。为了验证该方法,在铝青铜和铝合金样品上都进行了实验。与经典CF-LIBS相比,对于四个铝青铜合金样品,CF-LIBS with CD-SRL的平均误差(AE)分别从3.20%、3.22%、3.15%和3.01%降至0.95%、1.00%、1.16%和1.78%。对于四个铝合金样品,AE分别从0.66%、0.70%、0.89%和1.30%降至0.43%、0.61%、0.77%和0.33%。实验结果表明,CF-LIBS with CD-SRL比经典CF-LIBS具有更高的定量准确性和更强的适应性,这对CF-LIBS的实际应用非常有帮助。