化学计量学
风化作用
高光谱成像
黄铁矿
化学成像
主成分分析
拉曼光谱
矿物学
分析化学(期刊)
表征(材料科学)
化学
材料科学
地质学
人工智能
遥感
环境化学
光学
计算机科学
纳米技术
地球化学
色谱法
物理
作者
Enmanuel Cruz Muñoz,Fabio Gosetti,Davide Ballabio,Sergio Andò,Olivia Gómez-Laserna,José Manuel Amigo,Eduardo Garzanti
标识
DOI:10.1016/j.microc.2023.108655
摘要
In this study, we propose a new approach based on Raman hyperspectral imaging and chemometrics for the analysis of chemically heterogeneous surfaces of weathered minerals. A pyrite sample showing a heterogeneous surface with different alteration products, is used to test the validity of the technique. Principal Component Analysis (PCA) was initially used to evaluate data structure and identify Raman phases and vibrational modes related to minor and major weathering features. Afterwards, Multivariate Curve Resolution-alternating least squares (MCR-ALS) was carried out to identify the specific chemical components of the major weathering phases. Finally, for the analysis of the minor weathering phases, K-means clustering was carried out to identify groups of similar pixels of low percentage of variance in the image. Three major components are found in the analyzed sample, corresponding to pyrite and hematite vibrational modes, as well as features of an amorphous alteration product patina. Four additional spectral signatures revealing the presence of sulfates were found after the analysis of minor components. The proposed method enables a semi-quantitative threshold-based characterization of chemical features and provides a visual representation of the phase distribution on the surface of the sample.
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