Using artificial intelligence, researchers can now identify zircons derived from valuable copper deposits.
Elevated copper isotope ratios in arc magmas from fluid-rich cold subduction zones support the role of oxidizing fluids from the subducted lithospheric serpentinite in the oxidization of arc magmas.
Using a global data set of zircon trace elements, new research demonstrates the power of machine learning algorithms to accurately identify and locate porphyry copper deposits.
Copper ores were long thought to form through purely chemical processes, but a recent study provides the strongest evidence yet that microbial metabolism drives mineral production.
By using hyperspectral imaging, researchers test their ability to find copper in remote areas.