Block Modeling of the Carbonation Potential of Ore Deposits Using Cutting-Edge Core Scanning Technology and Advanced Machine Learning Algorithms

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Golden, Colorado
Project Term:
02/14/2023 - 02/13/2026

Technology Description:

The Colorado School of Mines (Mines) will develop a novel technological solution and workflow to enable mining companies to quantitatively model the carbonation potential of entire ore deposits using cutting-edge X-ray fluorescence core scanning technology and advanced machine learning techniques. The project will demonstrate how the carbonation potential of a copper-nickel-platinum group element (Cu-Ni-PGE) deposit can be determined involving block modeling of the amount of CO2 that can be sequestered in situ in an ore body and its surrounding host rocks. Mines will perform a cost-benefit analysis to show that evaluation of the total carbonation potential of ore deposits should become an integral part of mine feasibility studies. The technology and methodology will allow mine operators to objectively assess the economic benefit of adapting negative emission technologies. Such assessments are not currently possible as existing models estimating the carbonation potential of rock formations are too uncertain and do not take mineralogical heterogeneities into account.

Potential Impact:

The MINER program aims to use the reactive potential of CO2-reactive ore materials to decrease mineral processing energy and increase the yield of energy-relevant minerals via novel negative emission technologies.


MINER metrics meet the U.S. need for net-zero, commercial-ready technologies that provide energy-relevant minerals for economic and national security.


In addition to demonstrating carbon negativity, the proposed technologies will quantify and reduce our impact on environmental and human health by addressing ecotoxicity, acidification of air, smog, water pollution, and more.


MINER metrics specify increasing the yield of energy-relevant minerals by reducing unrecovered energy-relevant minerals in tailings in by 50% compared with state of the art.


ARPA-E Program Director:
Dr. Douglas Wicks
Project Contact:
Prof. Thomas Monecke
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