Automated, Not Autonomous: Integrating Automated Mineralogy with Complementary Techniques to Refine and Validate Phase Libraries in Complex Mineral Systems

Accurate phase identification is essential for characterising complex mineral systems but remains a challenge in SEM-based automated mineralogy (AM) for compositionally variable rock-forming or accessory minerals. While platforms such as the Tescan Integrated Mineral Analyzer (TIMA) offer high-resolution phase mapping through BSE-EDS data, classification accuracy depends on the quality of the user-defined phase library. Generic libraries often fail to capture site-specific mineral compositions, resulting in misclassification and unclassified pixels, particularly in systems with solid solution behaviour, compositional zoning, and textural complexity. We present a refined approach to developing and validating custom TIMA phase libraries. We outline strategies for iterative rule refinement using mineral chemistry, textures, and BSE-EDS responses. Phase assignments were validated using complementary microanalytical techniques, primarily electron probe microanalysis (EPMA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS). Three Queensland case studies demonstrate this approach: amphiboles in an IOCG deposit; cobalt-bearing phases in a sediment-hosted Cu-Au-Co deposit; and Li-micas in an LCT pegmatite system. Targeted refinement of phases improves identification, reduces unclassified phases, and enables rare phase recognition. Expert-guided phase library development strengthens mineral systems research and downstream applications in geoscience, ore deposits, and critical minerals while integrating datasets across scales from cores to mineral mapping.

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Publication Details

Journal
Minerals
Published
2025-10-27
DOI
https://doi.org/10.3390/min15111118
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Automated, Not Autonomous: Integrating Automated Mineralogy with Complementary Techniques to Refine and Validate Phase Libraries in Complex Mineral Systems

Vladimir Lisitsin, Benjamin R. Hines, Mitchell de Bruyn, Henrietta E. Cathey et al.
Minerals
Geochemistry and Geologic Mapping
article

Automated, Not Autonomous: Integrating Automated Mineralogy with Complementary Techniques to Refine and Validate Phase Libraries in Complex Mineral Systems

Vladimir Lisitsin, Benjamin R. Hines, Mitchell de Bruyn, Henrietta E. Cathey, Елена Белоусова, Andrew G. Christy, Alkiviadis Kontonikas-Charos, Lisa Kearney
article en

Abstract

Accurate phase identification is essential for characterising complex mineral systems but remains a challenge in SEM-based automated mineralogy (AM) for compositionally variable rock-forming or accessory minerals. While platforms such as the Tescan Integrated Mineral Analyzer (TIMA) offer high-resolution phase mapping through BSE-EDS data, classification accuracy depends on the quality of the user-defined phase library. Generic libraries often fail to capture site-specific mineral compositions, resulting in misclassification and unclassified pixels, particularly in systems with solid solution behaviour, compositional zoning, and textural complexity. We present a refined approach to developing and validating custom TIMA phase libraries. We outline strategies for iterative rule refinement using mineral chemistry, textures, and BSE-EDS responses. Phase assignments were validated using complementary microanalytical techniques, primarily electron probe microanalysis (EPMA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS). Three Queensland case studies demonstrate this approach: amphiboles in an IOCG deposit; cobalt-bearing phases in a sediment-hosted Cu-Au-Co deposit; and Li-micas in an LCT pegmatite system. Targeted refinement of phases improves identification, reduces unclassified phases, and enables rare phase recognition. Expert-guided phase library development strengthens mineral systems research and downstream applications in geoscience, ore deposits, and critical minerals while integrating datasets across scales from cores to mineral mapping.

MineralsVol. 15(11)
Queensland Department of Natural Resources, Mines and Energy (AU), Queensland University of Technology (AU)
Openalex Percentile: Top 83%
Geochemistry and Geologic Mapping
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