Magmatic-Hydrothermal Processes of Vein-Type Haman-Gunbuk-Daejang Copper Deposits in the Gyeongnam Metallogenic Belt in South Korea

Haman, Gunbuk, and Daejang deposits are neighboring vein-type hydrothermal Cu deposits located in the SE part of the Korean Peninsula. These three deposits are formed by magmatic-hydrothermal activity associated with a series of Cretaceous granodioritic intrusions of the Jindong Granitoids, which have created a series of veins and alterations in a hornfelsed shale formation. The copper deposits have common veining and alteration features: 1) a pervasive chlorite-epidote alteration, cut by 2) Cu-Pb-Zn-bearing quartz veins with a tourmaline-biotite alteration, and 3) the latest barren calcite veins. Chalcopyrite, pyrite, and pyrrhotite are common ore minerals in the three deposits. Whereas magnetite is a dominant mineral in the Haman and Gunbuk deposits, no magnetite is present, but sphalerite and galena are abundant in the Daejang deposit. Ore-bearing quartz veins have three types of fluid inclusions: 1) liquid-rich, 2) vapor-rich, and 3) brine inclusions. Hydrothermal temperatures obtained from the brine inclusion assemblages are about 340–600, 250–500, and 320–460°C in the Haman, Gunbuk, and Daejang deposits, respectively. The maximum temperatures (from 460 to 600°C) recorded in the fluid inclusions of the three deposits are higher than those of the Cu ore precipitating temperature of typical porphyry-like deposits (from 300 to 400°C). Raman spectroscopy of vapor inclusions showed the presence of CO2 and CH4 in the three deposits, which indicates relatively reduced hydrothermal conditions as compared with typical porphyry deposits. The Rb/Sr ratios and Cs concentrations of brine inclusions suggest that the Daejang deposit was formed by a later and more fractionated magma than the Haman and Gunbuk deposits, and the Daejang deposit has lower Fe/Mn ratios in brine inclusions than the Haman and Gunbuk deposits, which indicates contrasting redox conditions in hydrothermal fluids possibly caused by an interaction with a hosting shale formation. In brines, concentrations of base metals do not change significantly with temperature, which suggests that significant ore mineralization precipitation is unlikely below current exposure levels, especially at the Haman deposit. Ore and alteration mineral petrography and fluid inclusions suggest that the Haman deposit was formed near the top of the deep intrusion center, whereas the Gunbuk deposit was formed at a shallower intrusion periphery. The Daejang deposit was formed later at a shallow depth by relatively fractionated magma.

Porous Electrodeposited Cu as a Potential Electrode for Electrochemical Reduction Reactions of CO2

In the present study, a systematic investigation is performed to assess the relationship between electroplating parameters, pore morphology and internal surface area of copper deposits which are promising to serve as electrodes for electrochemical reduction reactions of carbon dioxide (CO2). A set of porous copper deposits are fabricated with the dynamic hydrogen bubble template method. The microstructural and Brunauer–Emmett–Teller (BET) analysis demonstrate that current density, deposition time, and bath composition control pore size, strut size, and hence surface area which could be as high as 20 m2/g. Selected sets of porous copper electrodes are then employed in the electrochemical reduction reaction test to determine their conversion performance in comparison to a monolithic copper surface. From the gas chromatography (GC) and nuclear magnetic resonance (NMR) analysis, porous copper is shown to provide higher rates of production of some important chemicals, as compared to copper foil electrodes. Porous copper with fern-like morphology serves as a promising electrode that yields relatively high amounts of acetaldehyde, acetate and ethanol. The study thus presents the opportunities to enhance the electrochemical reduction reaction of CO2 through microstructural engineering of the copper surface, which benefits both CO2 reduction and generation of chemical products of high value.

Application of Dirichlet Process and Support Vector Machine Techniques for Mapping Alteration Zones Associated with Porphyry Copper Deposit Using ASTER Remote Sensing Imagery

The application of machine learning (ML) algorithms for processing remote sensing data is momentous, particularly for mapping hydrothermal alteration zones associated with porphyry copper deposits. The unsupervised Dirichlet Process (DP) and the supervised Support Vector Machine (SVM) techniques can be executed for mapping hydrothermal alteration zones associated with porphyry copper deposits. The main objective of this investigation is to practice an algorithm that can accurately model the best training data as input for supervised methods such as SVM. For this purpose, the Zefreh porphyry copper deposit located in the Urumieh-Dokhtar Magmatic Arc (UDMA) of central Iran was selected and used as training data. Initially, using ASTER data, different alteration zones of the Zefreh porphyry copper deposit were detected by Band Ratio, Relative Band Depth (RBD), Linear Spectral Unmixing (LSU), Spectral Feature Fitting (SFF), and Orthogonal Subspace Projection (OSP) techniques. Then, using the DP method, the exact extent of each alteration was determined. Finally, the detected alterations were used as training data to identify similar alteration zones in full scene of ASTER using SVM and Spectral Angle Mapper (SAM) methods. Several high potential zones were identified in the study area. Field surveys and laboratory analysis were used to validate the image processing results. This investigation demonstrates that the application of the SVM algorithm for mapping hydrothermal alteration zones associated with porphyry copper deposits is broadly applicable to ASTER data and can be used for prospectivity mapping in many metallogenic provinces around the world.

Construction and applications of knowledge graph of porphyry copper deposits

A knowledge graph is becoming popular due to its ability to describe the real world by using a graph language that can be understood by both humans and machines using computer technologies. A case study to construct the knowledge graph of porphyry copper deposits is presented in this paper. First of all, the raw text data is collected and integrated from selected porphyry copper deposits and porphyry-skarn copper deposits in the Qinzhou Bay – Hangzhou Bay metallogenic belt, South China. Second, the text's entities, relations, and attributes are labeled and extracted with reference to the conceptual model of porphyry copper deposits in the study area. The third, a knowledge graph of porphyry copper deposits, was constructed using Neo4j 4.3. The resulted knowledge graph of porphyry copper deposit has the basic functions of an application. Furthermore, as part of a planned integrated knowledge graph from a single deposit, through an upper-geared metallogenic series, to a high-top metallogenic province, the understanding from the present study may be extended to mineral resource prospectivity and assessment beyond today. The interrelationship between the earth system, the metallogenic system, the exploration system, and the prospectivity and assessment (ES-MS-ES-PS) should be completely understood, and a knowledge graph system for ES-MS-ES-PS is needed. The key scientific and technological problems for achieving the ES-MS-ES-PS knowledge graph system are included in the progressively relative system of the domain ontology and knowledge graph of ES-MS-ES-PS, the automatic construction technology of complicated ESMS-ES-PS domain ontology and knowledge graph, the self-evolution and complementary techniques for multi-modal correlation data embedding in the ES-MS-ES-PS knowledge graph, and the knowledge graph, big data mining and artificial intelligence based on ES-resource prospectivity, and assessment theory, and methods.