Metal ore deposits, such as porphyry Cu–Au systems, orogenic Au deposits, volcanogenic massive sulfide deposits, and alkaline and carbonatite REE–HFSE systems, form through complex processes involving the transport of metals from source regions, followed by their concentration and deposition in the crust. Understanding ore-forming processes and their associated dynamics is crucial for assessing economic potential and guiding exploration strategies. Across these diverse systems, fluid–rock interactions play a fundamental role in ore formation. They control the formation of ore minerals and the mobilization of metals from source zones to depositional sites, and they leave diagnostic records that help decipher how metals are transported and concentrated.

At nano- and microscales, physical patterns in ore deposits, including dendritic structures, banding, fractures, mineral replacement textures, growth patterns and deformation features, provide fundamental records of fluid–rock interaction processes. At meso- to macroscales, these interactions manifest as hydrothermal alteration zones characterized by systematic mineral replacement, overgrowth and mineral zoning. The spatial and temporal organization of these patterns records the physicochemical evolution of ore-forming environments. Concurrently, the chemical reactions that drive ore formation control mineral dissolution and precipitation, as well as the redistribution of ore-forming components. These processes are recorded petrologically as elemental transfer and exchange during fluid–rock interactions, which collectively contribute to the formation of ore deposits.

Such observations provide key constraints for thermodynamic and kinetic simulations of fluid–rock interaction processes, thereby deepening our understanding of the underlying mechanisms. Moreover, recent advances in machine-learning techniques have significantly enhanced geochemical quantification and helped uncover hidden physicochemical relationships during the spatiotemporal evolution of ore minerals and deposits.

In this session, we invite multidisciplinary contributions that investigate ore deposits and their associated formation dynamics using fieldwork, microstructural and petrographic analyses, geochemistry, machine-learning techniques, and thermodynamic and numerical modelling. Case studies of economic ore deposits are also warmly welcomed.