Authors : Pierre Mensah; Andrews Ayim Oduro

Volume/Issue : Volume 11 - 2026, Issue 7 - July

Google Scholar : https://tinyurl.com/ycywazpb

Scribd : https://tinyurl.com/2fc5ftnt

DOI : https://doi.org/10.38124/ijisrt/26jul574

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The United States is working hard to scale up domestic critical mineral production, and the goal is to reduce import dependence. Executive Order 14241 and the 2025 List of Critical Minerals set the federal framework, and that framework rests on credible domestic production projections. The projections then rest on the accuracy of recovery prediction models that operators run at mine level. This paper reviews the published geometallurgical recovery prediction literature for four critical mineral systems of U.S. strategic importance. The systems are copper, cobalt, lithium, and rare earth elements. It compares the geostatistical, machine-learning, and process-mineralogy methods that are now in use. And it identifies where the underlying physical complexity, the data availability, and the published methodology align to support credible federal projections. It also shows where they do not. The conclusion is that the methodology maturity is highly uneven across the four mineral systems, and that this unevenness has direct consequences for U.S. critical mineral supply chain credibility.

Keywords : Geometallurgy; Recovery Prediction; Critical Minerals; Lithium; Cobalt; Copper; Rare Earth Elements; Geostatistics; Non-Additivity; U.S. Mining.

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