Alvarez-Llamas César, Purohit Pablo, Moros Javier, Laserna Javier
UMALASERLAB, Departamento de Química Analítica, Universidad de Málaga, C/Jiménez Fraud 4, Málaga 29010, Spain.
Anal Chem. 2022 Jan 25;94(3):1840-1849. doi: 10.1021/acs.analchem.1c04792. Epub 2022 Jan 12.
The shockwave produced alongside the plasma during a laser-induced breakdown spectroscopy event can be recorded as an acoustic pressure wave to obtain information related to the physical traits of the inspected sample. In the present work, a mid-level fusion approach is developed using simultaneously recorded laser-induced breakdown spectroscopy (LIBS) and acoustic data to enhance the discrimination capabilities of different iron-based and calcium-based mineral phases, which exhibit nearly identical spectral features. To do so, the mid-level data fusion approach is applied concatenating the principal components analysis (PCA)-LIBS score values with the acoustic wave peak-to-peak amplitude and with the intraposition signal change, represented as the slope of the acoustic signal amplitude with respect to the laser shot. The discrimination hit rate of the mineral phases is obtained using linear discriminant analysis. Owing to the increasing interest for in situ applications of LIBS + acoustics information, samples are inspected in a remote experimental configuration and under two different atmospheric traits, Earth and Mars-like conditions, to validate the approach. Particularities conditioning the response of both strategies under each atmosphere are discussed to provide insight to better exploit the complex phenomena resulting in the collected signals. Results reported herein demonstrate for the first time that the characteristic sample input in the laser-produced acoustic wave can be used for the creation of a statistical descriptor to synergistically improve the capabilities of LIBS of differentiation of rocks.
在激光诱导击穿光谱（LIBS）事件中，与等离子体同时产生的冲击波可记录为声压波，以获取与被检测样品物理特性相关的信息。在本工作中，开发了一种中级融合方法，利用同时记录的激光诱导击穿光谱（LIBS）和声数据，以增强对不同铁基和钙基矿物相的区分能力，这些矿物相具有几乎相同的光谱特征。为此，将主成分分析（PCA）-LIBS得分值与声波峰峰值幅度以及以相对于激光脉冲的声信号幅度斜率表示的位置内信号变化连接起来，应用中级数据融合方法。使用线性判别分析获得矿物相的判别命中率。由于对LIBS+声学信息原位应用的兴趣日益增加，在远程实验配置中并在两种不同的大气特性（地球和类火星条件）下对样品进行检测，以验证该方法。讨论了每种大气条件下影响两种策略响应的特殊性，以提供深入了解，从而更好地利用导致采集信号的复杂现象。本文报道的结果首次证明，激光产生的声波中的特征样品输入可用于创建统计描述符，以协同提高LIBS区分岩石的能力。
