The efficiency of mineral extraction is governed by microstructural features that current industry methods cannot adequately characterize or model. Recovery from low-grade and complex ores hinges on details measured in microns and nanometers – pore connectivity, mineral liberation, reactive surface area, and the way dissolution propagates through a heterogeneous grain assembly.
The recovery of critical minerals from heap leach pads and in-situ recovery operations depends on the interaction of lixiviant with mineralized rock at the pore scale. Continuum reactive-transport models used in mine planning predict performance by averaging fluid-rock interaction across grid cells of meters or larger, using effective parameters that cannot yet be predicted from rock structure. Laboratory-measured mineral dissolution rates routinely exceed field-measured rates by two to five orders of magnitude, and predictions of recovery and breakthrough diverge from operational data.
Demand for critical minerals is rising faster than the industry's ability to characterize the ores it processes. Predictive, image-based science is the route from empirical heap-leach trials to engineered recovery systems – better grade prediction, lower reagent consumption, safer operations, and cleaner reclamation.
Our research targets the underlying mechanism. Reactive transport in heterogeneous ore bodies is governed by the coupled evolution of pore geometry, mineral surface accessibility, and the dynamic factors that reshape the pore space during flow: mineral dissolution and precipitation, confinement effects in nanoporous matrices, and overburden pressure in in-situ systems. We resolve this coupling by direct multi-scale 3D imaging of reacting ore samples and engineered analogs, integrated with AI-assisted image-based modeling and reactive-transport simulation.
We characterize rock microstructure across scales using a hierarchical imaging workflow: micro-CT, SEM/EDS, FIB-SEM nanotomography, and S/TEM. Correlative registration across modalities produces unified multi-scale representations of rock samples, capturing pore/fracture networks, mineral-phase distributions, and accessible reactive surfaces.
AI-assisted segmentation and 3D model reconstruction that converts segmented 3D volumes into digital pore-and-mineral models suitable for direct simulation.
Coupled fluid flow, species transport, and mineral dissolution and precipitation on the digital rock, capturing the dynamic geometry evolution as leaching proceeds.
Validation against engineered analog materials of known geometry and against real-time 4D synchrotron micro-CT imaging of tracer-aided reaction-front propagation.
Universities, national labs, and research institutions:
We welcome partnership on current and future research projects in critical mineral recovery, subsurface transport, and digital rock physics.