Integration of Materials Characterization and Process Modeling for Predicting Recovery Outcomes in Complex Ores

Abstract

This research integrates advanced materials characterization techniques with process modeling to develop a predictive framework for hydrometallurgical recovery outcomes in complex ore bodies. By combining Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), and Fourier Transform Infrared Spectroscopy (FTIR) data with computational models, this study establishes correlations between mineralogical variations and leaching performance. The methodology demonstrates significant improvements in predicting reagent consumption and metal recovery rates across variable ore compositions, with validation results showing 92% accuracy in predicting copper recovery from polymetallic sulfide ores. This integrated approach offers mining operations a powerful tool for process optimization and reagent selection based on real-time mineralogical data.