基于光束成型的光谱校正策略与图像辅助校准,以提高LIBS准确度
Guanghui Chen1, Peichao Zheng2, Jinmei Wang2
1School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
Talanta
|December 19, 2025
概括
这项研究引入了一种混合方法,结合了光束成型和图像辅助技术,以增强激光诱导分解光谱 (LIBS) 以实现更准确的材料分析. 新方法显著提高了定量准确性,克服了传统LIBS方法的关键局限性.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 材料科学 材料科学 材料科学
背景情况:
- 精确的材料成分检测对于工业,环境和地质应用至关重要.
- 激光诱导分解光谱 (LIBS) 提供远程,多元件检测,但由于等离子体进化干扰而存在定量准确性问题.
- 现有的LIBS改进策略包括等离子体调制 (光束成形) 和数据处理 (图像辅助方法).
研究的目的:
- 开发和评估一种混合方法,整合光束塑形和图像辅助技术,以全面改进LIBS.
- 评估混合方法对不同元素的定量分析准确性的影响.
- 调查光束成型在减少用图像辅助方法观察到的特定元素依赖性的作用.
主要方法:
- 建议采用混合方法,将用于等离子调制的光束成型与用于数据处理的图像辅助方法相结合.
- 该方法通过使用校准曲线分析各种元素 (Si,Cr,Ni,Mn) 的定量准确性来评估.
- 分析了关键性能指标,包括确定系数 (R2),根平均平方误差 (RMSE) 和平均相对误差 (ARE).
主要成果:
- 混合方法在LIBS定量分析准确度方面显示出显著的改善.
- 对Si,Cr,Ni和Mn的确定系数 (R2) 接近0.99.
- 大多数元素的最大RMSE和ARE大大降低,分别从0.1556重%和151.13%降低到0.0435重%和38.00%.
- 梁造型被发现可以减少元素特定的依赖性,从而导致更一致的增强.
结论:
- 拟议的混合方法提供了一个有希望的策略,以提高LIBS的分析能力.
- 这种方法有效地解决了定量准确性的局限性,为LIBS技术更广泛的商业化铺平了道路.
- 物理调制和分析优化的整合导致了更强大,更可靠的材料组成分析.
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