基于声学特征标注的多模型标定LIBS定量分析方法

IF 3.1 2区 化学 Q2 CHEMISTRY, ANALYTICAL
Shihang Chen, Zhongqi Hao, Yuanhang Wang, Yu Rao, Li Liu, Jiulin Shi and Xingdao He
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引用次数: 0

摘要

为了提高LIBS定量分析的准确性和长期重复性,提出了一种基于声学特征标记的多模型校准方法(AFL-MMC)。通过分析合金钢试样中微量Mn、Mo、V和Cr,比较了单模型定标法和AFL-MMC法的定量分析能力。在声学特征标注中,选取等离子体第一峰值声幅(AA)、第一次回波前的声能(AE)和第一次回波前的声波带(AW)。结果表明,首峰AA和前首回波AE均与光谱强度呈较强的线性相关。以前一次回波AE作为特征标号时,平均相对误差分别为14%、17%、15%、17%和19%,最大平均相对误差由29%降至16%。AE表现出最明显的改善,其次是AA,而AW表现出相对有限的效果。这些结果表明,AFL-MMC的整合显著提高了LIBS定量检测的准确性和长期重复性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

LIBS quantitative analysis method based on multi-model calibration with acoustic feature labeling

LIBS quantitative analysis method based on multi-model calibration with acoustic feature labeling

To improve the accuracy and long-term reproducibility of LIBS quantitative analysis, a method based on multi-model calibration with acoustic feature labeling (AFL-MMC) was proposed. The quantitative analytical capabilities of single-model calibration and AFL-MMC methods were comparatively investigated by analyzing trace-level Mn, Mo, V, and Cr in alloy steel specimens. For acoustic feature labeling, the first peak acoustic amplitude (AA), the acoustic energy (AE) before the first echo, and the acoustic wave (AW) band before the first echo from the plasma were selected. The results demonstrated a strong linear correlation between both the first peak AA and the pre-first echo AE with spectral intensity. When the pre-first echo AE was used as a feature label, the average relative errors were 14%, 17%, 15%, 17% and 19%, with the maximum average relative error decreasing from 29% to 16%. AE demonstrated the most pronounced improvement, followed by AA, whereas AW exhibited comparatively limited effectiveness. These results indicate that the integration of AFL-MMC significantly improves the accuracy and long-term reproducibility of LIBS quantitative detection.

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来源期刊
CiteScore
6.20
自引率
26.50%
发文量
228
审稿时长
1.7 months
期刊介绍: Innovative research on the fundamental theory and application of spectrometric techniques.
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