Background

Rapid and accurate detection of the biomass potassium (K) content in biomass is crucial for mitigating ash deposition and fouling issues in biomass fuel combustion processes. Laser-induced breakdown spectroscopy (LIBS) offers a promising approach for rapid analysis of biomass elemental. However, the accuracy of LIBS detection is susceptible to chemical matrix effects. Particularly in the case of biomass, characterized by its complex composition, the absence of pertinent studies on effect mechanisms impedes the enhancement of analytical accuracy.

Results

In this study, we investigated and compared two types of matrix effects related to chemical properties in biomass samples (analyte forms and matrix composition). Firstly, the inconsistency of K spectral response among different chemical properties samples and the performance of univariate models were analyzed. The results indicate that, compared to the chemical forms, differences in composition are the dominant factor of chemical matrix effects. Moreover, the compositional content of biomass samples is analyzed to correlate the matrix effect in LIBS measurements to a chemical property of the specimen. It is indicated that differences in volatile and ash content may lead to variations in the plasma excitation process, resulting in distinct spectra. Finally, a knowledge-based regression approach was employed to attenuate chemical matrix effects, the main influencing factors identified were analyzed as a priori knowledge for variable selection and inputting them into a partial least squares model. And 13 real solid biomass fuels were measured, resulting in root mean square error of prediction (RMSEP), R^2, and average standard deviation (ASD) of 0.99, 0.050%, and 0.001%, respectively.

Significance

This study investigated the influence of matrix effects related to biomass chemical properties on LIBS measurements, achieving rapid measurement of K. It promotes the application of LIBS in solid fuels and provides a methodological reference for LIBS analysis of complex matrix materials.

中文翻译：

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激光诱导击穿光谱法测定固体生物质燃料中的碱金属元素：化学基质效应的分析和还原

 背景

快速准确地检测生物质中的生物质钾 （K） 含量对于缓解生物质燃料燃烧过程中的灰分沉积和结垢问题至关重要。激光诱导击穿光谱 （LIBS） 为生物质元素的快速分析提供了一种很有前途的方法。然而，LIBS 检测的准确性容易受到化学基质效应的影响。特别是在生物质的情况下，其特点是成分复杂，缺乏对效应机制的相关研究阻碍了分析准确性的提高。

 结果

在这项研究中，我们调查并比较了与生物质样品中化学性质相关的两种类型的基质效应（分析物形式和基质组成）。首先，分析了不同化学性质样品之间 K 光谱响应的不一致和单变量模型的性能。结果表明，与化学形式相比，成分的差异是化学基质效应的主要因素。此外，还分析了生物质样品的成分含量，以将 LIBS 测量中的基质效应与样品的化学性质相关联。结果表明，挥发物和灰分含量的差异可能导致等离子体激发过程的变化，从而产生不同的光谱。最后，采用基于知识的回归方法来减弱化学基质效应，将确定的主要影响因素作为变量选择的先验知识进行分析，并将其输入到偏最小二乘模型中。对 13 种真实固体生物质燃料进行了测量，预测均方根误差 （RMSEP） 和 R ^2, 和平均标准差 （ASD） 分别为 0.99、0.050% 和 0.001%。

 意义

本研究调查了与生物质化学性质相关的基质效应对 LIBS 测量的影响，实现了 K 的快速测量。它促进了 LIBS 在固体燃料中的应用，为复杂基质材料的 LIBS 分析提供了方法学参考。