The formation of metal ore deposits (e.g., porphyry Cu-Au systems, orogenic Au deposits, volcanogenic massive sulfide deposits, alkaline and carbonatite REE-HFSE systems) is a complex process that typically requires original ore sources to be transported from the mantle, followed by ore concentration and deposition in the crust. Understanding ore formation processes and the associated dynamics is crucial for assessing economic potential and guiding exploration strategies. Regardless of the specific processes involved, reactions between fluids and rocks fundamentally impact ore deposits. These reactions affect the formation of ore minerals, the mobilization of metallic materials from the source zone to the deposit, leaving significant footprints that aid in understanding how these metals are transported and concentrated to form the deposit. At nano- and microscales, physical patterns in ore deposits provide fundamental records of fluid-rock interaction processes, including dendritic structures, banding, fractures, mineralogical replacement textures, growth patterns, and deformation features. At meso- to macroscales, the interactions manifest as alteration zones characterized by systematic mineral replacement, overgrowth, and hydrothermal alteration. The spatial and temporal regularity of these patterns elucidates the physicochemical evolution of ore-forming environments during ore formation. Concurrently, accompanying chemical reactions that drive ore formation control mineral dissolution and precipitation, and the redistribution of ore-forming components. These phenomena petrologically reflect the processes of elemental transfer and exchange during fluid-rock interactions that contribute to the formation of ore deposits. Such natural observations enable thermodynamic and kinetic simulations of the fluid-rock interaction processes responsible for ore formation, deepening our understanding of the underlying mechanisms. Moreover, recent advances in machine-learning methods have significantly enhanced geochemical quantification and uncovered hidden physicochemical relationships during the spatiotemporal evolution of ore minerals and deposits.
In this session, we invite multidisciplinary contributions that investigate various ore deposits and their associated formation dynamics, using fieldwork, microstructural and petrographic analyses, geochemistry, machine learning, thermodynamic and numerical modeling. Case studies of economic ore deposits are welcomed.