Article

Advancing TOF-SIMS Workflows for Automated Mineral Grain Identification in Complex Samples

Surface Analysis Spotlight: TOF-SIMS

by Amy Ferryman Analytical Lab and Marketing Manager

In mineral exploration and processing, the surface chemistry of individual mineral particles plays a critical role in separation efficiency and process performance, particularly for complex ores. Time of Flight Secondary Ion Mass Spectrometry (TOF-SIMS) provides a unique capability to probe this chemistry at the scale of individual grains. However, the practical application of TOF-SIMS to large, heterogeneous mineral samples has been limited by the time and effort required to locate, analyze, and identify particles of interest, which restricts throughput and statistical representativity.

Through a collaborative program with the Sustainable Minerals Institute, University of Queensland in Brisbane, Australia, advances in a more scalable analytical approach for mineral processing applications via TOF-SIMS was trialed and validated, including:

• AI-assisted software development to rapidly prototypes automated TOF-SIMS workflows for scalable mineral analysis and region-of-interest identification.
• Automated region-of-interest detection using large-area Mosaic imaging to systematically survey complex samples and locate grain-scale minerals of interest.
• Data driven spectral analysis extracts TOF-SIMS spectra from targeted mineral grains and compares them with curated spectral reference data.
• Consistent mineral identification reduces manual spectral interpretation while improving accuracy, reproducibility, and consistency across large datasets.
• Statistically representative measurements increase the confidence in data applicability to industrial processes.

This approach enables particle-specific surface chemistry measurements across statistically meaningful populations, including fine and sparsely distributed target phases.