Geometallurgical Recovery Prediction Models for U.S. Critical Minerals: A Critical Review of Current Approaches for Copper, Cobalt, Lithium and Rare Earth Element Ore Systems

Pierre Mensah () and Andrews Ayim Oduro ()

International Journal of Innovative Science and Research Technology (IJISRT), 2026, vol. 11, issue 07, 1057-1064

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. (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijisrt.com/geometallurgical-recovery-p ... -element-ore-systems (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cvr:ijisrt:2026:07:ijisrt26jul574

DOI: 10.38124/ijisrt/26jul574

Access Statistics for this article

More articles in International Journal of Innovative Science and Research Technology (IJISRT) from IJISRT Publication
Bibliographic data for series maintained by Rahul Goyel ().