Can AI Locate Rare Minerals on Earth? Scientists Developed a Machine Learning Model To Locate Mineral Deposits

Rare minerals occur in a wide variety of deposits across the Earth. Their demand has grown rapidly, but they occur in limited minable deposits. Conventional technology allows searching for rare minerals using geochemical exploration as the main method. In this approach, X-ray fluorescence (XRF) is a very useful instrument for real-time qualitative and quantitative evaluation of rare minerals.

However, minerals and mineral-forming locations are usually difficult to predict due to the complicated features of nature with intertwined geological, chemical, and biological systems.

Researchers continue to look for new technologies that can easily locate mineral deposits as they use them to understand our planet's history and help meet the industry's demands.

Search for Valuable Minerals

Mineralogist Shaunna Morrison and geoinformatics scientist Anirudh Prabhu developed a machine learning model based on artificial intelligence (AI) that can potentially find the occurrences of specific minerals. Together with their research colleagues, the team created the tool using data from the Mineral Evolution Database to predict the mineral occurrences that were previously unknown. The database includes 295,583 locations of 5,478 mineral compounds, while the model took advantage of patterns based on association rules. These patterns are the result of the dynamic evolutionary history of the Earth.

To test the effectiveness of their AI-based model, the researchers explored the Tecopa basin in the Mojave Desert in eastern California. This Pleistocene geologic formation is known for having a Mars analog geographic condition.

At the end of their exploration, the machine learning model could predict the source of important minerals such as rutherfordine, bayleyite, and zippeite. It also located deposits of critical rare earth elements such as monazite-(Ce), allanite-(Ce), and spodumene.

The result of the study proves the effectiveness of mineral association analysis as a predictive tool that will potentially benefit mineralogists, economic geologists, and planetary scientists. The researchers hope that mineral association analysis will provide an understanding of mineralization on Earth and the mineralizing environments across the Solar System.

A Look into the Past With Minerals

According to the American Museum of Natural History, the Earth is home to 5,000 mineral species. Minerals are only used as raw materials for industry, but they also serve as the oldest surviving records about the formation and evolution of our Solar System. They are considered the lasting evidence for geologic events and ancient terrains. Understanding the factors that changed minerals over time can help the experts understand the questions about the history of our planet.

The International Mineralogical Association (IMA) established a standard for classifying minerals according to their composition and configuration. Grouping the minerals by origin based on IMA's system can tell a lot of information about the Earth and other planets.

The role of minerals in the scientific community is not limited to tracing the Earth's past since they are also involved in the current activities on our planet. The dynamics of the Earth's interior are reflected in tectonic activities such as volcanic eruptions and earthquakes. Chemically zoned minerals play an important role in understanding these catastrophic events.