: Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS), particularly in its time-of-flight (TOF) configuration, enables rapid, high-resolution elemental imaging across complex geological materials, offering spatial and chemical insights at the micrometer scale. However, quantitative accuracy is often limited in fine-grained or mineralogically heterogeneous matrices due to the failure of global normalization strategies, such as 100 wt % oxide assumptions, to account for mixed-phase compositions. Here, we present a workflow that leverages Uniform Manifold Approximation and Projection (UMAP) for unsupervised dimensionality reduction and k-means clustering to segment mineralogical phases directly from per-pixel elemental concentration maps. Cluster compositions are matched to known minerals based on stoichiometric similarity, enabling pixel-wise, phase-specific normalization (e.g., oxides vs carbonates). Validated with dawsonite-bearing sandstones from Mt. Amiata, Italy, this approach significantly reduces quantification errors, correcting systematic over- or underestimations of up to 60%. The method also enables a consistent, phase-resolved geochemical comparison across depth profiles. This study establishes UMAP not only as an exploratory tool but also as a practical guideline for accurate and interpretable quantification in multielemental imaging.
Umfahrer, B., Buday, J., Pořízka, P., Kaiser, J., Garofalo, P.S., Günther, D. (2026). Mineral Phase-Resolved Quantification in LA-ICP-MS Imaging. ANALYTICAL CHEMISTRY, 98(1), 581-589 [10.1021/acs.analchem.5c05398].
Mineral Phase-Resolved Quantification in LA-ICP-MS Imaging
Garofalo, Paolo S.
Penultimo
Membro del Collaboration Group
;
2026
Abstract
: Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS), particularly in its time-of-flight (TOF) configuration, enables rapid, high-resolution elemental imaging across complex geological materials, offering spatial and chemical insights at the micrometer scale. However, quantitative accuracy is often limited in fine-grained or mineralogically heterogeneous matrices due to the failure of global normalization strategies, such as 100 wt % oxide assumptions, to account for mixed-phase compositions. Here, we present a workflow that leverages Uniform Manifold Approximation and Projection (UMAP) for unsupervised dimensionality reduction and k-means clustering to segment mineralogical phases directly from per-pixel elemental concentration maps. Cluster compositions are matched to known minerals based on stoichiometric similarity, enabling pixel-wise, phase-specific normalization (e.g., oxides vs carbonates). Validated with dawsonite-bearing sandstones from Mt. Amiata, Italy, this approach significantly reduces quantification errors, correcting systematic over- or underestimations of up to 60%. The method also enables a consistent, phase-resolved geochemical comparison across depth profiles. This study establishes UMAP not only as an exploratory tool but also as a practical guideline for accurate and interpretable quantification in multielemental imaging.| File | Dimensione | Formato | |
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Umfahrer_etal_2025_UMAP.pdf
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Umfahrer_etal_2025_UMAP_supplementary.pdf
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