ZEISS Phase Identifier is an AI-enhanced software platform designed for automated phase segmentation, classification, and quantification of mineralogical samples in both 2D and 3D. It operates with ZEISS scanning electron microscopes (SEM) and X-ray microscopes (XRM), providing data-led, not library-enforced, mineral identification and texture analysis. The software enables fast, reliable, and unbiased mineral classification and quantification, supporting workflows in mining, metallurgy, and geoscience. Phase Identifier AI automates chemistry-based mineral classification, liberation, and association analysis, while Phase Identifier 3D extends these capabilities to volumetric datasets, allowing non-destructive, high-throughput analysis of complex samples. The platform is designed to maximize efficiency, reduce manual intervention, and deliver comprehensive mineralogical and textural information for process optimization and research.

Key Features

AI-Driven Phase Segmentation and Classification Automated, unbiased identification and quantification of mineral phases.

• Data-led, not library-enforced, mineral classification.
• Chemistry-based segmentation and quantification.

2D and 3D Analysis Supports both planar and volumetric mineralogical investigations.

• 2D phase segmentation and texture analysis with SEM.
• 3D classification and measurement with XRM, revealing true sample composition and relationships.

Automated Workflows Streamlines mineralogical analysis for efficiency and reproducibility.

• Fast, reliable, and repeatable chemistry-based classification.
• Automated quantification of mineral liberation and association.

Non-Destructive Imaging Preserves valuable or rare samples during analysis.

• No need for mechanical alteration to expose flat surfaces in 3D workflows.

High Throughput and Simple Sample Handling Enables large-scale, unattended analysis.

• Increased throughput with minimal manual intervention.

Benefits

Unbiased and Reliable Mineral Classification Removes user bias and library limitations from mineral identification.

• Data-driven approach ensures objective results.
• Consistent, reproducible quantification for process optimization.

Comprehensive Texture and Association Analysis Delivers detailed insights into mineral relationships and liberation.

• Supports metallurgical process evaluation and ore characterization.

Efficiency and Productivity Automates time-consuming tasks, freeing users for higher-level analysis.

• Maximizes workflow efficiency in research and industrial settings.

Non-Destructive, High-Value Sample Analysis Allows analysis of precious or irreplaceable samples without damage.

• Supports correlative workflows and multi-modal imaging.