Achieve Consistent Lithium Ore Characterization with TESCAN TIMA

Why Manual Mineral Workflows Compromise Data Reliability

Accurate lithium ore characterization depends on representative sampling and objective particle analysis. Yet many labs still rely on manual workflows and limited field coverage. Sampling bias and operator subjectivity become inevitable in critical datasets.

With inconsistent particle detection, varying interpretations, and insufficient statistics, mineral ratios become distorted. These limitations create a cascade of consequences:

• Unreliable mineral quantification across batches

• Inaccurate ore grading for process optimization

• Inefficient recovery from misjudged liberation

• Slower throughput due to manual workflows

• Inconsistent results between operators and labs

These constraints compromise analytical reliability and hinder the generation of consistent, process-relevant mineralogical data.

Automated Quantitative Mineralogy with TESCAN TIMA

Using TESCAN TIMA, lithium ore samples were analyzed through a fully automated quantitative mineralogy process. BSE imaging segmented thousands of particles, and EDS spectra were automatically matched to a reference library to assign mineral phases.

Over 40 mounted samples were analyzed in a single batch run. Automated stage movement and calibration delivered reproducible results without supervision. With image-based analysis, the system quantified mineral liberation, association, and grain size. This delivered critical data to guide grind size and evaluate processing performance.

Enhanced Data Reliability with Standardized, Particle-Based Mineralogy

TESCAN TIMA delivered consistent, high-throughput datasets across all lithium ore samples. Automated segmentation and classification generated statistically representative particle populations. This reduced sampling bias and minimized operator influence.

Using integrated EDS spectral matching, the system consistently assigned mineral phases across users and sessions. Quantitative data on liberation, association, and grain size revealed key textural patterns — guiding comminution strategies and improving mineral recovery.

These insights were visualized in mineral maps, where phase variability and liberation trends directly impacted separation efficiency. Quantitative analysis exposed inconsistencies introduced by manual workflows and limited sample coverage.

Through TESCAN TIMA’s advanced capabilities, these issues were minimized — enabling enhanced reliable mineral analysis and improving processing results.