Prospecting by Luck in the Clean Energy Age

The U.S. imported 80% of its rare earth elements in 2024, and the clean energy transition requires massive quantities of critical minerals (lithium, cobalt, rare earths, gallium, germanium) whose geology of formation, concentration, and distribution is poorly understood at a fundamental level. We lack basic knowledge of how hydrothermal and magmatic processes concentrate these elements, what controls leaching from mine tailings and anthropogenic deposits, and where undiscovered deposits exist on the continental crust and ocean floor. This is not a mining engineering problem — it is a geoscience knowledge gap. Without understanding the geochemical processes that create ore deposits, exploration remains empirical rather than predictive.

The International Energy Agency projects that meeting Paris Agreement targets requires a 4–6x increase in critical mineral supply by 2040. Current exploration success rates are declining as surface-accessible deposits are exhausted and remaining resources lie under cover or at depth. The geopolitical concentration of critical mineral processing (China controls ~60% of lithium processing, ~70% of cobalt refining, ~90% of rare earth processing) creates strategic vulnerability for all nations pursuing the energy transition. Every EV battery, wind turbine, and semiconductor depends on minerals whose supply cannot be rapidly expanded because we do not know where to look.

Traditional prospecting methods rely on surface geochemistry and geologic mapping, which miss deposits at depth or under sedimentary cover — and most surface-accessible deposits in well-explored regions have already been found. The geochemistry of critical mineral concentration in hydrothermal systems is not well constrained experimentally — thermodynamic data for rare earth element-bearing fluids at high pressure and temperature conditions are sparse and contradictory. Ocean floor deposits (polymetallic nodules, seafloor massive sulfides) are mapped at extremely coarse resolution with no systematic geochemical characterization. Environmental impacts of extraction (groundwater contamination, induced seismicity from subsurface stress redistribution) are poorly modeled, creating regulatory uncertainty that deters exploration investment. Research has been fragmented across geochemistry, mineralogy, economic geology, and environmental science communities without convergent approaches.

Fundamental experimental work on mineral stability and solubility at conditions relevant to ore-forming systems, filling the thermodynamic data gaps. Integration of AI/ML with geochemical datasets for predictive prospecting (supported by NSF's CAIG program). The 2024 Hydrothermal Geochemistry and Critical Minerals Meeting built a new network spanning experimental geochemistry, thermodynamic modeling, reactive transport modeling, and extraction technologies. Systematic geochemical characterization of ocean floor mineral deposits. Coupled models of ore formation, groundwater interaction, and environmental impact to enable responsible exploration.

A student team could compile published thermodynamic data for a specific critical mineral (e.g., lithium or cobalt) across the pressure-temperature conditions relevant to hydrothermal ore formation, identify gaps in the experimental database, and use computational chemistry to predict missing values. Alternatively, a team could use publicly available geochemical survey data (USGS, state geological surveys) and machine learning to identify geochemical signatures predictive of undiscovered critical mineral deposits in a specific region. Relevant skills: geochemistry, thermodynamics, data science, machine learning, environmental science.