Ore Types Research Articles

Study on fluid inclusions and stable isotopics of W–Mo ore deposits in the Ningshan–Zhen’an area, South Qinling, China

The study of the fluid inclusions of W–Mo deposits in the mineralization area of Ningshan–Zhen’an , Shaanxi Province, China shows that the gas–liquid two-phase inclusions are mainly present in W–Mo deposits, and the ore-forming fluid can be divided into four types: high-temperature type, middle–high-temperature type, middle-temperature type and low-temperature type. The formation depths of the W–Mo mineralization range from 4.2 to 8.4 km. The boiling and mixing of fluid may have been important mechanisms for the formation of W–Mo mineralization. The skarn-type mineralization is dominated by magmatic water, the quartz-vein-type mineralization includes both magmatic water and meteoric water, and the meteoric water is more involved in the quartz-fluorite-vein-type, beryl-quartz-vein-type and pegmatite-type mineralization. Magma is the main source of sulfur; that is, magma is the main source of mineralization. Combined with the metallogenic setting and geological characteristics of typical ore deposits, in the process of structural system transformation in South Qinling, the ore-forming magma fluid in the Late Indosinian–Yanshanian period was uplifted and emplaced along the NW–WNW direction and NE–NNE direction, and eventually, NW–WNW fault-controlled skarn-type W–Mo mineralization and quartz-vein-type W–Mo deposits accompanied by greisenization, albitization and potash feldspathization formed.

The Formation Conditions of the Volga Basin Oil Shales in Relation to Their Metallogeny on Rhenium and Other Valuable Elements

The Volga oil shales are located on the Russian platform and represent a potential non-traditional and promising source of rhenium and other valuable metals. Concentrations of rhenium at the level of industrial types of ores have been identified at the Perelyubskoe and Kotsebinskoe deposits. The complex of lithological and geochemical studies suggests that the metallogeny of the Volga oil shales is associated with the influence of volcanism and anoxic conditions during the sedimentation period. The main criteria have been identified by which high concentrations of rhenium in the Volga oil shales can be predicted: the content of organic carbon, molybdenum, and the DOPr indicator. Based on the analyzed data, promising layers have been identified for the Perelyubskoe and Kotsebinskoe deposits to detect industrial concentrations of rhenium.

Обоснование модели прогнозирования контуров рудного тела и содержания полезных компонентов в запасах на основе искусственных нейронных сетей

The ores of the Talnakh deposit are complex, from them they extract: copper, nickel, cobalt, metals, platinum groups, gold, silver, as well as selenium, tellurium, ruthenium and sulfur. Ores have a complex mineral composition and are characterized by a variety of forms of finding useful components. The main ore minerals of all types of ores are: pyrrhotite, chalcopyrite and its varieties, pentlandite and cubanite. Nickel, copper, platinum, palladium, gold and silver are represented mainly by their own minerals; rhodium, ruthenium, osmium, iridium, selenium, and tellurium are in scattered form. As a result of the fact that the ore deposits of the Skalistaya mine lie at a considerable depth (more than 700 m), its ores are classified as dangerous for mountain impacts. Purpose of the study. The commissioning of disseminated ore mine field sections, taking into account the risk of mining impacts, determines the need for accurate information on the content of useful components in a particular section of the deposit, which in turn will increase the efficiency and safety of mining reserves, as well as increase the economic efficiency of the mine. Research methods and materials. Constant geological control, taking samples, rock samples is not always possible or difficult as a result of the high complexity of both field and office work. In addition, the cost of additional exploration of deposits (field sites, production blocks) is significantly high, and the period for obtaining results can reach up to several months. The model developed by the authors for predicting the contours of the ore body and the content of useful components in reserves based on the use of an artificial neural network will make it possible to accurately predict the shape of the ore body, the conditions for its occurrence, as well as the composition and value of the content of useful components in the contours of the mining unit. Research results. The forecast model is based on an artificial neural network of direct distribution, which allows predicting the desired parameters with an error value not higher than 5–10 %. The model developed by the authors allows us to obtain high accuracy of forecasting the conditions of occurrence, the shape of the ore body and the content of components from the forecast data of each forecast well. The period for obtaining geodata on the condition of occurrence, shape and content of useful components is much shorter than the period for detailed exploration of reserves (several hours versus several months, respectively). Discussion of research results. The obtained forecast data are presented in the form of a table on the content of useful components in the disseminated ore reserves on each meter of each forecast exploration well of the grid of forecast wells of the forecast production block. The ore body contours are determined by the predicted content of useful components in the reserves of disseminated ores of the production block, taking into account the data of the grid of forecast exploration wells. Conclusions. To obtain timely and highly accurate information on reserves for both rich ores and disseminated ores, taking into account the depth of development and the presence of danger from mountain impacts, it is necessary to use the forecast model developed by the authors based on an artificial neural network of direct distribution. The model developed by the authors allows us to obtain high accuracy of forecasting the conditions of occurrence, the shape of the ore body and the content of components from the forecast data of each forecast well.

Mineralogical Method as an Effective Way to Predict Gold Ore Types of Deposits in Platform Areas (East of the Siberian Platform)

Mineralogical Method as an Effective Way to Predict Gold Ore Types of Deposits in Platform Areas (East of the Siberian Platform)

Distribution and Enrichment of Au, Hg, and Tl in the Lanmuchang Deposit, Guizhou, China

Mineralization characterized by Au, Hg, and Tl enrichment is rare, and research on Au, Hg, and Tl mineralization is limited. The Lanmuchang Au–Hg–Tl deposit is located in the “Golden Triangle” of Yunnan, Guizhou, and Guangxi Provinces in China. In this study, we used scanning electron microscopy (SEM), electron microprobe analysis (EPMA), and a Tescan integrated mineral analyzer (TIMA) to analyze the mineral composition and distribution of the different types of ores and identify the occurrence state and enrichment mechanism of ore-forming elements in the Lanmuchang deposit. The results show that the primary ore minerals in the Lanmuchang deposit are pyrite, cinnabar, and lorandite. Cinnabar is the primary carrier of Hg (>90%), and pyrite is the primary carrier of Tl (>60%). Gold, Hg, and Tl primarily occur as solid solutions in hydrothermal pyrite, whereas they primarily occur as nano-scale particles in diagenetic pyrite. The substitution of As for S in hydrothermal pyrite promotes Au enrichment. The coupled substitution of 2Fe2+ ⇔ Tl+ + As3+ may be a significant Tl incorporation mechanism and promotes the occurrence of Hg in pyrite. The As and Se contents and Cu/Au and Co/Ni ratios of the hydrothermal pyrite demonstrate that the ore-forming fluid was mostly in a low-temperature, low-salinity, almost-neutral pH, and nearly reducing environment. The results show that the mineralization of the Lanmuchang deposit is associated with the cooling, oxidation, water–rock interaction, and boiling processes of the ore-forming fluid(s).

Decoupling of Cu and Zn in sediment-hosted base metal deposits: Evidence from LA-ICP-MS analyses of fluid inclusions and trace elements in minerals at Baiyangping, China

Copper and lead–zinc mineralization in basinal rocks worldwide commonly shows distinct spatiotemporal zonation. The Baiyangping deposit in the Lanping Basin, southwest China, is a large sediment-hosted polymetallic deposit that shows clear and pronounced zoning of Cu versus Pb-Zn mineralization. Here, we analyzed trace elements in pyrite and sphalerite and fluid inclusions in sphalerite, celestine, quartz, and dolomite to seek insights into the origins of the ore-forming fluids and the processes that govern the separation of Cu- from Zn-rich ores. We show that while the later Zn-rich mineralization is characterized by fluid inclusions showing typical hallmarks of basinal brine composition (low homogenization temperature < 230 °C, high salinity > 20 wt% NaCl eq., dominated by Na-K-Ca-Mg chlorides), the earlier Cu-rich mineralization shows markedly distinct composition that more closely resembles deeply-circulated water that has equilibrated with crystalline basement rocks (higher homogenization temperature of 210–280 °C, variable but lower salinity of ∼ 5–15 wt% NaCl, dominated by Na-K-Li chlorides). Pyrites formed during the earlier Cu-rich stage show elevated Cu, Co, Sb and Zn, while pyrites formed during the later Pb-Zn stage are more enriched in As, Pb and Mn. We interpret that the earlier-formed Cu-rich ores were deposited by deeply sourced fluids that ascended along basement-penetrating reverse faults, whereas the later Zn-rich ores were formed by subsequent circulation of fluid from within the basin, whose flux was promoted by shallower strike-slip faults. Hence, the two ore types reflect discrete pulses of chemically distinct hydrothermal fluids. We suggest that the evolving structural controls and fluid pathways during prolonged ore formation allowed sequential pulses of fluids that had acquired different metal budgets by equilibration with different sources. We suggest that this type of two-step process may be more common in sediment-hosted base metal deposits than single-fluid cooling sequential order of precipitation.

Recovery of rare earth elements from sedimentary rare earth ore via sulfuric acid roasting and water leaching

Rare earth elements were extracted using a sulfuric acid roasting-water leaching process. The effect of acid roasting on a new type of low-grade sedimentary rare earth ore found in Guizhou Province, China was analyzed using X-ray diffraction and scanning electron microscopy. A systematic study was conducted on process parameters such as amount of acid, roasting temperature, roasting time, water leaching temperature, and leaching time. The results reveal that the total recovery of rare earth elements reaches 81.37%, which is 3.1 times higher than that achieved through direct acid leaching, under the optimal conditions. In addition, the leaching rate of heavy rare earth elements reaches 72.53%. Rare earth elements and some other valuable metals are transformed into soluble sulfate through the local decomposition of clay minerals under the action of the sulfuric acid attack. The dissolution rates of aluminum, iron, and titanium ions are 34.94%, 17.05%, and 62.77%, respectively. The precipitation rate of Ti reaches 99%, and the loss of rare earth ions in the solution is less than 1%. Meanwhile, the results of a leaching kinetics analysis indicate that the leaching process of rare ions is controlled by diffusion. Precious metal ions such as iron and aluminum in the leaching solution can reduce the adsorption of rare earth ions by kaolinite. This study efficiently recovered rare earth ions under conditions of low calcination temperature and direct water leaching, resulting in reduced energy consumption of the extraction process and acidity of the leaching solution. These findings provide a solid foundation for the further separation and extraction of rare earth ions.

Formation of the giant Maoping Mississippi Valley-type Pb–Zn (Ge) deposit via fluid mixing: Evidence from trace element and sulfur isotope geochemistry of pyrite

The SYG (Sichuan–Yunnan–Guizhou) area is one of the most economically significant Mississippi Valley Type (MVT) ore provinces, providing approximately 27 % of the Pb–Zn resources in China. The Pb-Zn deposits in this region are renowned for their high grade, and the Maoping deposit with 20.3 % Pb-Zn grade is one prime example. However, the mechanism of such high-grade mineralization remains unclear, and pyrite may record valuable ore-forming information before and during Pb-Zn mineralization. Based on field geology and petrography, three hydrothermal stages were identified in the Maoping deposit: dolomite–pyrite vein (stage I), dolomite–sphalerite–galena vein (stage II), and calcite vein (stage III). Three types of pyrite are recognized: Py1 and Py2 occur in stage I, and Py3 is closely associated with sphalerite and galena in stage II. Py1 exhibits the highest concentrations of S, Pb, Sb, Cu, Co, Ni, V, Ag, Mn, Se, and Mo, and Py3 shows the highest Fe and As contents but the lowest levels of S, Pb, Sb, Cr, Ti, Co, Ni, Mn, and Mo. The element composition of Py2 shows transitional characteristics between those of Py1 and Py3. The Co and Ni contents gradually decrease from Py1 through Py2 to Py3, while their ratios remain within the range of 0.1–1.0. Compared with Py1 and Py2, Py3 exhibits suddenly elevated As levels and apparent acicular structures, indicating that a rapidly precipitating environment was likely triggered by an abrupt temperature decrease. Py1 exhibits δ34S values of 19.7–21.5 ‰, followed by Py2 between 18.6 and 21.1 ‰; both indicate that the sulfur was sourced from sulfates by thermochemical sulfate reduction (TSR). In contrast, Py3 exhibits lower δ34S values ranging from 7.5 to 11.0 ‰, potentially attributed to bacterial sulfate reduction (BSR). The differences in mineral structure, element composition, and sulfur isotopes among the three pyrite types indicate the involvement of two distinct fluids: metal-bearing basin brine and fluid containing reduced sulfur. The former was derived from basin brine that extracted ore metals (Pb2+ and Zn2+) from host sedimentary piles. The latter originated from carbonate strata in the Maoping area containing reduced sulfur formed by BSR. We propose that the ore-bearing basin brine reacted with organic matter in the wallrock through TSR to generate Py1 and Py2 in stage I and then mixed with the positioned fluid containing reduced sulfur via BSR to precipitate Py3, sphalerite, and galena in stage II. Hence, fluid mixing is the primary ore-forming mechanism and effectively accounts for the high-grade Pb–Zn ores in the Maoping deposit.

Boron isotopes of Manganese ores from the northern part of the Kalahari Manganese Deposit, South Africa

Abstract The world-class deposits of the Kalahari Manganese Field (KMF) in South Africa constitute a key resource of manganese (Mn) ore for the global steel industry. Many aspects of the origin of high metal-grade ores in the northernmost KMF remain unresolved, especially with respect to the complex hydrothermal history of these ores and the source/s of fluids responsible for epigenetic metal enrichment. In this study, the geochemistry of boron (B) is employed as a potential proxy for such processes, and the results are contextualised against an assumed low metal-grade precursor. Samples collected from the northern part of the Kalahari Manganese Deposit allow for the distinction of three Mn ore types, of which the precursor ore is the closest candidate, petrographically and geochemically, to primary/diagenetic Mn deposition. This precursor ore is dominated by Mn-carbonate and braunite, and records B concentrations in the order of a few 100s to 1 000s ppm and positive δ11B values at an average of 11 ± 6‰. Ferruginous Mn ores appear to have formed from decarbonation of precursor ore and metasomatic ferric iron addition, particularly in the stratigraphically upper Mn ore bed, which is closest to the overlying Olifantshoek and Kalahari unconformities. Ferruginous Mn ores appear depleted in B (ca. 500 ppm on average) and have lower boron isotope values (δ11B: 0 ± 3‰). Hydrothermally Mn-enriched ores, in contrast, are dominated by hausmannite, braunite-II and bixbyite and record highest B concentrations (up to 10 000s ppm) and δ11B values as high as 41‰, pointing to metasomatic introduction of B by circulating evaporitic brines. While further research is needed to comprehensively unravel the geochemical intricacies of B within the complex interplay of fluids and rocks in the Hotazel region, the findings of this study still strongly suggest that B holds promise as a tracer for alteration processes in the KMF.

Influence of Mineralogy and Mineralogy Approach to Optimize Processing: A Case Study of Tin–Copper Polymetallic Ore

Tin-Copper polymetallic ore is a type of typical ore that cassiterite is closely associated with sulfide minerals. In mineral processing of tin–copper polymetallic ore, flotation is generally used to recover valuable sulfide minerals, while gravity separation is used to recover cassiterite. A mine in Yunnan, China, uses the traditional “flotation–gravity separation” process to recover copper and tin but faces several problems during processing, such as an insufficient copper grade in Cu concentrate, a much higher grade of As in S concentrate, and a grade of S in Sn concentrate that exceeds the standard. A process mineralogy study was conducted, with a focus on Cu–S mixed concentrate, S concentrate, and Sn rough concentrate. It was determined that the main cause of these problems is not the liberation or size distribution of valuable minerals but the superstructure of pyrrhotite, which represents one of the most abundant minerals in the products. Based on EMPA, SEM-EDS, and XRD data, both monoclinic pyrrhotite and hexagonal pyrrhotite occurred in all samples. The abundance of different superstructures of pyrrhotite in one sample was determined by means of particle extraction and area calculation from microscopic images, and the distribution characteristics of monoclinic pyrrhotite and hexagonal pyrrhotite in the whole process were clarified. This process mineralogy study indicates that the strong magnetic hexagonal pyrrhotite mainly affects the copper recovery during flotation, and the hexagonal pyrrhotite mainly affects the recovery of cassiterite during gravity separation. Strong magnetic monoclinic pyrrhotite and weak magnetic hexagonal pyrrhotite should be fully considered in the optimization of mineral processing, and the magnetic separation of pyrrhotite should be adopted to optimize the overall environment of copper flotation and tin gravity separation.

Hollow drop bubbles: A preliminary study of simplified prototype for improving copper(II) extraction with ACORGA® M5640 using coated bubble swarm

There are two well-defined processes for the types of copper ores. One for the processing of copper sulfides and another for the processing of the copper oxides. There are similarities between the two, particularly in the preparation stage of the run of mine (ROM) such as the crushing. However, significant differences exist in how to concentrate the elements of interest. Flotation is the most used concentration process to separate copper sulfide minerals from other minerals using air bubbles. For oxides, after the dissolution of copper, the solvent extraction (SX) process is the preferred path using two immiscible liquids to separate the copper.A line of investigation for solvent extraction is the use of a bubble coated with solvent to extract the metal of interest from the aqueous solution, some devices have been built and tested for this purpose using different principles to generate a coated bubble swarm. However, those equipments have been tested on laboratory and have not been scaled up to an industry level.The Hollow Drop (HD) concept was born from the idea of building a device to generate coated bubbles in a continuous swarm that could be scalable to an industry level. In this paper two columns were built and operated: a proof-of-concept column and a scale-up attempt for the extraction of Cu(II) fom an aqueous solution of 2.5 g L−1 using ACORGA® M5640 (25% v/v) in the Kerosene.The results show that we could generate a bubble swarm and conduct the solvent extraction process at a 97% recovery using our proposed coated bubble generator. However, in our scaled prototype test only a 70% recovery was achieved, which shows that our column is working but the scaling-up needs more investigation regarding the dimensions and flows of the process.

Application of Machine Learning to Research on Trace Elemental Characteristics of Metal Sulfides in Se-Te Bearing Deposits

This study focuses on exploring the indication and importance of selenium (Se) and tellurium (Te) in distinguishing different genetic types of ore deposits. Traditional views suggest that dispersed elements are unable to form independent deposits, but are hosted within deposits of other elements as associated elements. Based on this, the study collected trace elemental data of pyrite, sphalerite, and chalcopyrite in various types of Se-Te bearing deposits. The optimal end-elements for distinguishing different genetic type deposits were recognized by principal component analysis (PCA) and the silhouette coefficient method, and discriminant diagrams were drawn. However, support vector machine (SVM) calculation of the decision boundary shows low accuracy, revealing the limitations in binary discriminant visualization for ore deposit type discrimination. Consequently, two machine learning algorithms, random forest (RF) and SVM, were used to construct ore genetic type classification models on the basis of trace elemental data for the three types of metal sulfides. The results indicate that the RF classification model for pyrite exhibits the best performance, achieving an accuracy of 94.5% and avoiding overfitting errors. In detail, according to the feature importance analysis, Se exhibits higher Shapley Additive Explanations (SHAP) values in volcanogenic massive sulfide (VMS) and epithermal deposits, especially the latter, where Se is the most crucial distinguishing element. By comparison, Te shows a significant contribution to distinguishing Carlin-type deposits. Conversely, in porphyry- and skarn-type deposits, the contributions of Se and Te were relatively lower. In conclusion, the application of machine learning methods provides a novel approach for ore genetic type classification and discrimination research, enabling more accurate identification of ore genetic types and contributing to the exploration and development of mineral resources.

Catagenetic type of manganese ores: REE and isotope (δ13C, δ18O) geochemical features (on the example of the Usa deposit, Russia)

Catagenetic type of manganese ores: REE and isotope (δ13C, δ18O) geochemical features (on the example of the Usa deposit, Russia)

Optimizing multi-spectral ore sorting incorporating wavelength selection utilizing neighborhood component analysis for effective arsenic mineral detection

Arsenic contamination not only complicates mineral processing but also poses environmental and health risks. To address these challenges, this research investigates the feasibility of utilizing Hyperspectral imaging combined with machine learning techniques for the identification of arsenic-containing minerals in copper ore samples, with a focus on practical application in sorting and processing operations. Through experimentation with various copper sulfide ores, Neighborhood Component Analysis (NCA) was employed to select essential wavelength bands from Hyperspectral data, subsequently used as inputs for machine learning algorithms to identify arsenic concentrations. Results demonstrate that by selecting a subset of informative bands using NCA, accurate mineral identification can be achieved with a significantly reduced the size of dataset, enabling efficient processing and analysis. Comparison with other wavelength selection methods highlights the superiority of NCA in optimizing classification accuracy. Specifically, the identification accuracy showed 91.9% or more when utilizing 8 or more bands selected by NCA and was comparable to hyperspectral data analysis with 204 bands. The findings suggest potential for cost-effective implementation of multispectral cameras in mineral processing operations. Future research directions include refining machine learning algorithms, exploring broader applications across diverse ore types, and integrating hyperspectral imaging with emerging sensor technologies for enhanced mineral processing capabilities.

Research on Hyperspectral Surface Reflectance Dataset of Typical Ore Concentration Area in Hami Remote Sensing Test Field

Abstract. Surface reflectance data is the basic data source for the hyperspectral parametric remote sensing products and remote sensing quantitative application, which is widely used in various application fields such as natural resources and ecological environment monitoring. At present, multispectral data takes the leading role among the common land surface reflectance datasets and the reflectance data mainly involves the types of ground objects such as farmland, forest land, water body, soil, etc., while the datasets relatively less targets the types of rock and mineral surface objects, yet especially the reflectance datasets with the combination of time series and multi-scale satellite-earth are even more scarce. In order to better promote the application of hyperspectral surface reflectance and explore the advantages of joint application of satellite-earth multi-scale reflectance data, on the basis of field-measured rock and mineral target spectral, a comprehensive surface reflectance dataset was generated by using domestically produced hyperspectral satellite data as the data source in this study, mainly focusing on the typical ore concentration area in the Hami Remote Sensing test field in Xinjiang. The dataset includes multi-period hyperspectral satellite surface reflectance images, field measured rock and mineral spectral data, and multi-period sub-pixel spectral data collected based on ground spectral measured points, which can provide significant support for the research and development and accuracy verification as well as performance evaluation of algorithms such as surface reflectance inversion, mineral identification and ground object classification.

Copper and zinc isotopic variations in Ni-Cu-PGE ores of the Noril’sk Province (Russia)

Research subject. Mineral assemblages of sulfides from massive and disseminated sulfide nickel-copper-platinum-group element (Ni-Cu-PGE) and low-sulfide PGE ores of the Noril’sk Province, which hosts the richest complex deposits of platinum-group metals, nickel, and copper. Aim. In order to identify sources of ore material and explore new forecasting approaches for Ni-Cu-PGE deposits, we study the Cu- and Zn isotopic compositions of sulfides from economic Kharaelakh and Noril’sk-1 intrusions containing unique and large sulphide Ni-Cu-PGE deposits (Oktyabr’sk and Noril’sk-1, respectively), subeconmic Zub-Marksheider and Vologochan intrusions containing small- to medium-size Ni-Cu-PGE deposits, and non-economic Nizhny Talnakh and Nizhny Noril’sk intrusions containing low grade disseminated Ni-Cu mineralization. Results. The analyzed samples are characterized by sulfide mineral assemblages, which contain mainly chalcopyrite, pyrrhotite, pentlandite, troilite, cubanite, and galena. Sulfide Ni-Cu-PGE ores of the Oktyabr’sk and Noril’sk-1 deposits, associated with economic intrusions (i.e., Kharaelakh and Noril’sk-1), demonstrate distinct δ65Cu values from –2.42 to –1.40‰ and from –0.33 to 0.60‰, respectively, which differ from the δ65Cu values for sulfides from other Ni-Cu-PGE deposits and ore occurrences of the Noril’sk Province (data comprise 36 analyses). We note that the Cu-isotopic composition for sulfide minerals of massive and disseminated ores from the Kharaelakh intrusion has similar “isotope-light” characteristics. The most pronounced shift towards “isotope-heavy” copper was found in the horizon of low-sulfide PGE ores of the Noril’sk-1 intrusion (δ65Cu = 0.51–0.60‰). The isotopic composition of Zn (δ66Zn) for the studied sulfide samples from economic, subeconomic, and non-economic intrusions, with the exception of one sample (0.73 ± 0.14‰), is characterized by similar “isotope-light” values (from –0.65 to –0.03‰). Conclusions. The revealed variations in the Cu- and Zn-isotopic composition in the studied sulfide assemblages from all types of ores reflect their primary characteristics; however, for the unique Oktyabr’sk Ni-Cu-PGE deposit, characterized by the most “isotopically light” composition of copper (δ65Cu = –1.9 ± 0.34‰), the possibility of assimilation of an external source of Cu during the formation of sulfide Ni-Cu-PGE ores cannot be excluded. The combined use of Cu and Zn isotopic parameters proved to be a weakly informative predictive indicator for the detection of high-grade sulfide ores, primarily due to the similarity of the Zn isotopic composition of the ore material in all investigated intrusions of the Noril’sk Province.

Feasibility of Estimating Type and Abundance of Iron Ore Using Field Hyperspectral Radiometry and Spectral Transformation in Precambrian Banded Iron Formations of North Odisha, India

Feasibility of Estimating Type and Abundance of Iron Ore Using Field Hyperspectral Radiometry and Spectral Transformation in Precambrian Banded Iron Formations of North Odisha, India

An automated mineralogy derived criterion for clustering ore samples for mineral liberation studies

Correctly determining the optimal grinding size is crucial for mineral processors, yet it poses several challenges. Still popular among practitioners, the empirical determination of the grinding target involves time-consuming and resource-intensive laboratory routines employed for generating quality, recovery and energy curves from which the target size is set. This approach becomes even more challenging for mines with diverse ore textures, requiring extensive testing on numerous samples to accurately capture the behaviour of the entire ore body. Consequently, a more efficient experimental method is highly desirable. A solution for reducing the laboratory effort is clustering samples according to the mineral liberation characteristics. This paper introduces a novel multivariate criterion for statistical clustering of ore samples for mineral liberation studies, derived from SEM-based automated mineralogy data. The criterion considers three variables: two coefficients (named A and k) derived from the exponential correlation equation between degree of liberation and the top size of the size fraction, and the overall degree of liberation, both easily obtained from the liberation spectrum for a top size of 1 mm. The effectiveness of the proposed criterion has been experimentally demonstrated. It was concluded that the clustering process correctly grouped samples with similar mineral liberation characteristics. The clustering approach can be used to significantly reduce the laboratory effort on liberation studies involving a great number of samples of different types of ore. Although developed using iron ore samples, the criterion's theoretical basis suggests its potential for adaptation to other types of ore.

The distribution and formation of mine body in Tibet

The Gangdise metallogenic belt has been a popular mineral mine since it was discovered due to its various types of mineral elements, such as copper, iron, zinc, molybdenum, silver, gold, and bismuth, attracting millions of researchers. Moreover, the possible copper output that has been indicated here has already reached 3,000,000 tons. The deposit here is a typical skarn type ore rich in garnet. The article mainly introduces how the minerals in Gangdise metallogenic belt is distributed and investigates how the Gangdise metallogenic belt is formed. Some hypotheses in this article refer to previous investigations in the Gangdise metallogenic belt. This paper concludes that the reasons for the formation of the major ore deposit in Gangdise metallogenic can be regarded as the movement of the Eurasian Plate and India Plate, which can also be defined as the main collision phase, though other geologic changes altered the distribution of the ore body later.

Origin and evolution of a porphyry-skarn-stratabound system: constraints from geology, magmatic-hydrothermal zircon U–Pb and molybdenite Re–Os geochronology, and in situ S isotopes of the Dongguashan Cu(–Au) deposit, eastern China

Intrusion-related stratabound deposits within Late Carboniferous carbonate units are an abundant and highly economically significant ore type in eastern China. In such deposits, stratabound mineralization commonly coexists with porphyry and/or skarn mineralization, and the vast majority of reserves (>90 %) are derived from extensive stratabound orebodies, which are easy to exploit and of great interest to geologists. However, it is unclear whether these deposits were formed via the Late Carboniferous seafloor sedimentary exhalation formation or the Early Cretaceous magmatic-hydrothermal processes. Moreover, the fluid and sulfur isotope variations within porphyry-skarn-stratabound systems have not been adequately constrained. We investigated the Dongguashan deposit, one of the largest and most representative stratabound Cu(–Au) deposits in eastern China. Three mineralization types were recognized based on field and petrologic studies: porphyry, skarn, and stratabound. In the stratabound mineralization zone, magmatic and hydrothermal zircons from laminated ores yielded concordant U–Pb ages of 137.3 ± 1.1 and 135.7 ± 1.4 Ma, respectively, while molybdenite samples from vein-like ores yielded Re–Os model ages of 137.8–133.1 Ma (isochron age, 135.9 ± 1.4 Ma). These ages were consistent with the zircon U–Pb age of quartz monzodiorite (137.8 ± 1.7 Ma). A total of 146 in situ S isotope analyses yielded δ34S values (1.9–7.4 ‰) indicating that the sulfur was derived from a magmatic source. Therefore, the Dongguashan deposit resulted from Early Cretaceous magmatism rather than submarine exhalative sedimentary processes. The fluctuations in S isotopes of sulfides across the three mineralization types are attributable to different factors (pH, temperature, and oxygen fugacity) during the evolution of hydrothermal ore-forming fluids. This study demonstrates the importance of geochronology of mineralization and in situ sulfur isotope analysis under robust geological and petrographic frameworks, which can yield information about the ore-forming processes and ore genesis.