Abstract:
This paper is the result of mineral exploration engineering.
Objective Apatite is a mineral commonly present in volcanic, metamorphic, and sedimentary rocks. Its crystal structure can host various elements such as Sr, Mn, REEs, U, Th, F, Cl, and others. Apatite's chemical composition is dictated by magma and hydrothermal processes, which makes it a subject of interest for many researchers.
Methods This paper reviews common methods and the latest research achievements of apatite in mineralogy, isotope chronology, deposit geochemistry, artificial intelligence, and exploration indication.
Results Elemental (e.g., Sr, Y, and REEs) and Sr−Nd isotopic compositions of magmatic apatite can help identify the source of its parental magma. Elements such as Ce, Eu, Ga, and Mn can indicate the oxidation state of the magma, while F and Cl can be used to estimate the volatile content of the melt. The U−Pb isotope system of apatite can record the crystallization age of its host rock. Low−temperature thermochronology is often used to study the degree of denudation after ore deposit formation. Hydrothermal apatite's structure and composition bear information about the fluid, which can indicate the fluid source, properties, and other information related to magmatic−hydrothermal mineralization processes. Artificial intelligence techniques such as machine learning can process massive amounts of apatite data to discriminate rock types and deposit types.
Conclusions Apatite is a mineral that is crucial for studying mineral deposits and exploring ore deposits. Future researches should focus on the relationship between hydrothermal apatite and the metallogenic process. Additionally, combining artificial intelligence with apatite analyses to trace the diagenetic and metallogenic process is a promising avenue for further study.