Interpretable machine learning models classify minerals via spectroscopy

Interpretable machine learning models classify minerals via spectroscopy

Abstract Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, whic...

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Bibliographic Details
Main Authors: R. Smith, Tyler L. Spano, Marshall McDonnell, Lance Drane, Ian Gibbs, Andrew Miskowiec, J. L. Niedziela, Ashley E. Shields
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Machine learning
Raman spectroscopy
Uranium minerals
Material identification
Online Access:https://doi.org/10.1038/s41598-025-92686-2
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https://doi.org/10.1038/s41598-025-92686-2

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