Grade Mineral Research Articles

Optimized Weighted Ensemble Approach for Enhancing Gold Mineralization Prediction

The economic value of a mineral resource is highly dependent on the accuracy of grade estimations. Accurate predictions of mineral grades can help businesses decide whether to invest in a mining project and optimize mining operations to maximize the resource. Conventional methods of predicting gold resources are both costly and time-consuming. However, advances in machine learning and processing power are making it possible for mineral estimation to become more efficient and effective. This work introduces a novel approach for predicting the distribution of mineral grades within a deposit. The approach integrates machine learning and optimization techniques. Specifically, the authors propose an approach that integrates the random forest (RF) and k-nearest neighbor (kNN) algorithms with the marine predators optimization algorithm (MPA). The RFKNN_MPA approach uses log normalization to reduce the impact of extreme values and improve the accuracy of the machine learning models. Data segmentation and the MPA algorithm are used to create statistically equivalent subsets of the dataset for use in training and testing. Drill hole locations and rock types are used to create each model. The suggested technique’s performance indices are superior to the others, with a higher R-squared coefficient of 59.7%, a higher R-value of 77%, and lower MSE and RMSE values of 0.17 and 0.44, respectively. The RFKNN_MPA algorithm outperforms geostatistical and conventional machine-learning techniques for estimating mineral orebody grades. The introduced approach offers a novel solution to a problem with practical applications in the mining sector.

Fractal dimension used as a proxy to understand the spatial distribution for carlin-type gold deposits

The spatial distribution of ore-forming element grades typically exhibits strong nonlinear characteristics as a result of continuous geological processes. The trend of change in ore grade sequences is a crucial indicator of the degree of enrichment of an ore deposit. Therefore, quantitative evaluation of the spatial distribution of ore-forming elements holds great significance for understanding ore-forming processes as well as for ore exploration. In this work, based on the principles of fractal theory, a MATLAB-based program to calculate fractal dimensions was developed, and fractal analysis was conducted on the gold concentration values (g/t) of 25 drill holes in the Lannigou Gold Mining Area, Guizhou, China. Rescaled range analysis and the fractal correlation integral were utilized to obtain the spatial distribution of gold concentrations in the drill holes. Rescaled range analysis revealed that the Hurst exponent (HR/S) values vary in the range of 0.58–0.97, which reflected the persistent behavior of vertical variation in gold tonnage at the studied wells. Furthermore, the relationship between gold grade distribution and associated fluctuations in the fractal dimension derived from the correlation dimension (DC) was discussed. The DC value was found to vary between 1.01 and 1.59, indicating that high-grade gold deposits were distributed along steep fractal gradients and that fractal dimension values could be used as a reliable proxy to efficiently understand the migration pathways of auriferous fluid. Studies have shown that the Hurst exponent of the Au grade sequence exhibited a strong dependence on the grade of mineralization, with gold mineralized veins persisting throughout the studied drill holes. Thus, fractal dimension gradients can serve as an important proxy for identifying the locations of potential economic gold deposits in unexplored areas. Moreover, this approach can be employed to map the distribution patterns of other types of ore deposits.

Retrograde Assemblages of Gneisses at Arigidi and Erusu Areas of Southwestern Nigeria

The study is aimed to unravel the presence of low-grade minerals in the migmatite terrain of Southwestern Nigeria. Mineral and textural relationship of mineral assemblages were determined using a petrographic microscope, while chemical composition was analyzed using XRF and LA-ICP-MS. Petrographic studies show the mineral assemblage, biotite + plagioclase + chlorite + epidote + quartz + muscovite + ilmenite ± calcite. There is intense alteration of both biotite and plagioclase. Textural evidence shows chloritization of biotite and epidotization of both biotite and plagioclase. Epidotization of biotite is basically at the edges of biotite while that of plagioclase in more intense at the core of grains. Primary foliation is defined by mineralogical banding of quartzo-feldspathic and mafic minerals, while secondary foliation is defined by both biotite and chlorite. SiO2 contents are high in both gneisses (> 60 wt %), while there is a high depletion of REE. The results from field observations, mineral assemblages and textural relationship suggests that deformation due to shearing could have enhanced the retrograde chloritization of gneisses. Shearing could have created a path for the influx of fluid (H2O & CO2) thus triggering alteration of both biotite and plagioclase. Hydrothermal fluids containing K+ can be said to have initiated the retrograde process which gave rise to reactions that produces secondary low grade minerals; chlorite, epidote and muscovite.

Real-time ore sorting using color and texture analysis

Sensor-based ore sorting is a technology used to classify high-grade mineralized rocks from low-grade waste rocks to reduce operation costs. Many ore-sorting algorithms using color images have been proposed in the past, but only some validate their results using mineral grades or optimize the algorithms to classify rocks in real-time. This paper presents an ore-sorting algorithm based on image processing and machine learning that is able to classify rocks from a gold and silver mine based on their grade. The algorithm is composed of four main stages: (1) image segmentation and partition, (2) color and texture feature extraction, (3) sub-image classification using neural networks, and (4) a voting system to determine the overall class of the rock. The algorithm was trained using images of rocks that a geologist manually classified according to their mineral content and then was validated using a different set of rocks analyzed in a laboratory to determine their gold and silver grades. The proposed method achieved a Matthews correlation coefficient of 0.961 points, higher than other classification algorithms based on support vector machines and convolutional neural networks, and a processing time under 44 ms, promising for real-time ore sorting applications.

Smell the Rainbow: Olfactory Intensity Changes Color, not Luminescence in a Synesthete (P2-9.011)

<h3>Objective:</h3> To inform how odor concentration may change color perception in a synesthete. <h3>Background:</h3> In a synesthete, different concentrations of the same odor inducing different colors has not heretofore been described. <h3>Design/Methods:</h3> <h3>Case Study:</h3> This 27-year-old right-handed single male presented with a lifelong history of odor-color synesthesia. Each odor is associated with a specific color. While odors induce perception of color, colors do not induce perception of odors. <h3>Results:</h3> Amyl acetate in concentrations diluted in USP grade mineral oil to 10%, 1%, 0.1% 0.01% (Moberg, 2003; Doty, 1995) was presented randomly six times. This demonstrated retest reliability as well as change in color as identified on the Hexadecimal Real Color Wheel (Jusko, 2022), as opposed to change in brightness, with the most intense, 10% and 1%: yellow; 0.1%: orchid; and 0.01%: light pink. This revealed change in intensity correlated with change in color as opposed to change in luminescence. <h3>Conclusions:</h3> Some odorants, when presented with higher concentration, induce perception of entirely different aromas, as occurs with hydrogen sulfide (Hirsch, 1996). This would be consistent with each percept of odor inducing its own color. Peradventure, the increased intensity of each of the odors may decrease the perception of brightness or luminance (Zellner, 2008). This, minimal but still discreet, well-defined inducers, precipitating superimposition of specific colors, may be viewed as a variant of synesthesia, a super-synesthete. This suggests the presence of an underlying synesthetic network hyperconnectivity with the V4 occipital lobe, the primary color area of the visual cortex (Gennaro, 2021), and the hippocampal representation of memory of aroma (White, 2015), or olfactory lobe (orbital frontal cortex and insular cortex) (Mauric, 2013), and V4 occipital lobe hyperconnection (Hubbard, 2005). Further exploration of such connections may reveal greater understanding of olfactory and visual system. <b>Disclosure:</b> Miss Brar has nothing to disclose. Dr. Hirsch has nothing to disclose.

Prevalence of intra-articular mineralization on knee computed tomography: the multicenter osteoarthritis study

The aim of this work was to report the prevalence of computed tomography (CT)-detected intra-articular mineralization. We included participants from the Multicenter Osteoarthritis (MOST) Study. At the 12th year visit of the MOST study, bilateral knee CTs were first obtained. All participants also had posteroanterior and lateral radiographs of bilateral knees and completed standard questionnaires. Knee radiographs were assessed for Kellgren & Lawrence grade (KLG) and radiographic evidence of intra-articular mineralization. CT images were scored using the Boston University Calcium Knee Score (BUCKS) for cartilage, menisci, ligaments, capsule, and vasculature. Prevalence of intra-articular mineralization was computed for the total sample, and stratified by age, sex, race, Body Mass Index (BMI), presence of frequent knee pain, and KLG. We also determined distribution of mineralization in the cartilage and meniscus, and co-localization. 4140 bilateral knees from 2070 participants were included (56.7% female, mean age 61.1 years, mean BMI: 28.8kg/m2). On radiographs 240 knees (5.8%) had intraarticular mineralization, while CT-detected mineralization was present in 9.8% of knees. Prevalence of hyaline articular and meniscus mineralization increased with age and KL grade, and was similar by sex, BMI categories, and comparable in subjects with and without frequent knee pain. Mineralization tended to be ubiquitous in the joint, most commonly involving all three (medial/lateral tibiofemoral and patellofemoral) compartments (3.1%), while the patellofemoral compartment was the most involved compartment in isolation (1.4%). CT of the knee provides greater visualization of intra-articular mineralization than radiographs and allows better localization of the crystal deposition within the joint. Further studies should focus on the co-localization of intra-articular crystal deposition and corresponding magnetic resonance imaging (MRI)-features of knee osteoarthritis (OA).

Application of the k-Prototype Clustering Approach for the Definition of Geostatistical Estimation Domains

The definition of geostatistical domains is a stage in the estimation of mineral resources, in which a sample resulting from a mining exploration process is divided into zones that show homogeneity or minimal variation in the main element of interest or mineral grade, having geological and spatial meaning. Its importance lies in the fact that the quality of the estimation techniques, and therefore, the correct quantification of the mineral resource, will improve in geostatistically stationary areas. The present study seeks to define geostatistical domains of estimation for a mineral grade, using a non-traditional approach based on the k-prototype clustering algorithm. This algorithm is based on the k-means paradigm of unsupervised machine learning, but it is exempt from the one-time restriction on numeric data. The latter is especially convenient, as it allows the incorporation of categorical variables such as geological attributes in the grouping. The case study corresponds to a hydrothermal gold deposit of high sulfidation, located in the southern zone of Peru, where estimation domains are defined from a historical record of data recovered from 131 diamond drill holes and 37 trenches. The characteristics directly involved were the gold grade (Au), silver grade (Ag), type of hydrothermal alteration, and type of mineralization. The results obtained showed that clustering with k-prototypes is an efficient approach and can be used as an alternative or complement to the traditional methodology.

Abstract 15024: High Concentration Mineral Oil, Corn Oil and Their Constitutive Fatty Acids Do Not Influence Low-Density Lipoprotein (LDL) Oxidation Rates in vitro

Introduction: LDL transports dietary long chain fatty acids, constituents that may influence rates of lipid oxidation. Modified LDL promotes foam cell formation during atherosclerosis. The omega-3 fatty acid (n3-FA) eicosapentaenoic acid (EPA) administered as icosapent ethyl (IPE), reduced cardiovascular events in REDUCE-IT compared to mixed n3-FAs in similar high-risk patients (STRENGTH). Some have attributed these discordant outcomes, in part, to placebo choice (mineral versus corn oil) despite very limited oral absorption. We compared the effects of these oils and various FAs on rates of LDL oxidation at supra-pharmacologic doses. Methods: LDL was isolated from human plasma by isopycnic centrifugation, separated into test samples of 100 μg/mL before being incubated at 37°C for 30 min with pharmaceutical grade mineral or corn oil at high concentrations (100 μg/mL) that are comparable to treatment achieved n3-FAs (4 g/d) that have high oral absorption. We also tested FAs contained in these oils, including stearic acid (18:0), arachidic acid (20:0), and linoleic acid (18:2, n-6) as well as ascorbic acid (10 μM) and a water-soluble analog of vitamin E (Trolox, 10 μM) as controls. All samples then underwent copper-induced oxidation (20 μM) monitored by formation of malondialdehyde (MDA). Results: MDA formation increased from 0.28 ± 0.03 to 9.96 ± 0.58 μM ( p &lt;0.001) with vehicle treatment from 0-2 h. Addition of either mineral or corn oil at 100 μg/mL did not significantly influence rates of MDA formation at 2 h (0.02% and 1.93% change vs vehicle, respectively). Nor did we observe any antioxidant activity with constituent FAs stearic acid, arachidic acid, or linoleic acid, FAs with no or two double bonds. As antioxidant controls, ascorbic acid and Trolox both reduced LDL oxidation by 93% and 94% (0.71 ± 0.11 and 0.62 ± 0.04 to 9.96 ± 0.58 μM, p &lt;0.001) after 2 h. Conclusions: Neither mineral nor corn oils affected LDL oxidation even at supra-pharmacologic concentrations. Beyond poor oral absorption, mineral oil and its constituent fatty acids did not affect LDL oxidation, a property related to mechanisms of atherosclerosis.

Abstract 13685: Eicosapentaenoic Acid (EPA) Inhibits Low-Density Lipoprotein (LDL) Oxidation Compared to Docosahexaenoic Acid (DHA) and Mineral Oil in vitro

Introduction: Oxidized LDL triggers inflammation during the initiation and progression of atherosclerotic plaque. The omega-3 fatty acid (n3-FA) EPA administered as icosapent ethyl (IPE), reduced cardiovascular (CV) events in REDUCE-IT due, in part, to potential antioxidant and anti-thrombotic activity. By contrast, mixed n3-FA containing docosahexaenoic acid (DHA) have failed to reduce CV events in similar high-risk patients (STRENGTH). Some have raised concerns over the relationship between these discordant outcomes and placebo choice (mineral oil) as well as DHA content. We compared the effects of these compounds on oxidation of LDL where such ingested fatty acids are concentrated and transported. Methods: LDL was isolated from human plasma by isopycnic centrifugation, separated into test samples of 100 μg/mL, and incubated at 37°C for 30 min with pharmaceutical grade mineral oil, EPA, DHA or vehicle at equimolar levels (10 μM). All samples were then subjected to copper sulfate-induced oxidation (20 μM) monitored by formation of malondialdehyde (MDA). Ascorbic acid at equimolar levels served as a control. Results: LDL oxidation increased 30-fold (0.28±0.03 vs 8.72±0.54 μM; p &lt;0.001) after 4 h and the rate was unaffected by addition of mineral oil. By contrast, EPA significantly inhibited LDL oxidation; after 4 h, EPA inhibited MDA levels by 75% compared with vehicle (8.72±0.54 vs 2.20±0.36 μM; p &lt;0.001). While DHA exhibited antioxidant activity at 2 hours at a level less than EPA (1.15±0.54 vs 3.00±1.08 μM; p &lt;0.05), it exhibited no antioxidant activity after 4 h. Like DHA, ascorbic acid also reduced LDL oxidation only up to 2 h. Conclusions: These data support sustained LDL antioxidant effects for EPA compared with DHA, ascorbic acid, or mineral oil. The longer-term antioxidant actions of EPA may contribute to reduced events in outcome trials compared to mixed n3-FA formulations, independent of placebo selection.

Characterization of pulp calcifications and changes in their composition after treatments with citric acid and ethylenediaminetetraacetic acid solutions.

The ectopic calcifications of non-mineralized tissues can occur in several forms throughout life, such as pulpal calcification. The presence of pulp stones is a challenge in endodontic treatment because they partially or fully obliterate the pulp chamber hindering access to root canals and their subsequent shaping. This study aimed to determine their crystallographic properties and evaluate the capacity of citric acid (CA) and ethylenediaminetetraacetic acid (EDTA) to promote the demineralization of pulp calcifications. The samples were obtained from patients with indications of endodontic treatment, and the radiographic examination was suggestive of pulp stone in at least one permanent tooth. The samples were isolated and analyzed by scanning electron microscopy/energy-dispersive x-ray spectroscopy (SEM/EDX). The Fourier Transform by high resolution-transmission electron microscopy, Raman microscopy, and X-ray diffraction (XRD) were used to identify the mineral phase and crystallographic characteristics. To evaluate the effect of CA and EDTA on the crystallinity of calcifications, they were submerged into these two individual solutions and the changes were assessed in situ by Raman spectroscopy. The SEM images obtained from calcifications demonstrated irregular morphologies. EDX of sample surfaces shows a high presence of oxygen, carbon, calcium, and phosphorous, however, other elements such as sodium, magnesium, nitrogen, chlorine, potassium, sulfur, and zinc were identified in less quantity. According to Raman, XRD, and high-resolution transmission electron microscopy, the predominant mineral phase identified in the pulpal calcification was a poor crystallinity apatite. According to in situ analyses, the effect of CA and EDTA was observed on the signals of PO4 3- and CH2 groups corresponding to inorganic and organic components. The changes with CA were evident at 7min while the effect of EDTA was observed until 15 min of treatment. All results indicate that pulp stones have a heterogeneous composition principally composed of apatite with low crystallinity. The solubility of these pathological minerals is adequate using solutions such as EDTA or CA; however, the effectivity depends on the mineralization grade of calcifications, time, and concentration of exposition to this chemical.

Spatial Ensemble Anomaly Detection Method for Exhaustive Map-Based Datasets

Spatial anomaly detection is an essential part of subsurface data quality control and modeling for resources, e.g., groundwater aquifer, hydrocarbon resources, and mining mineral grades, along with environmental remediation. Efficiently identifying spatial local anomalous regions is important for detecting changes in subsurface population and data acquisition artifacts. Advanced data analytics and machine learning methods may be applied, but often omit essential spatial context with the additional cost of reduced interpretability. Considering the high cost of the risk in subsurface resource exploration, it is essential to maximize the integration of domain expertise. Our proposed method is an ensemble anomaly detection method that calculates the local anomaly probability based on the joint probability density space derived from the semivariogram model. The ensemble approach of our proposed method utilizes multiple local anomaly classifications calculated over a moving search window around each grid of a 2D map or 3D model. The anomalous regions are eventually decided based on the majority rule of the ensemble anomaly classifiers. We demonstrate the proposed method with 3 synthetic exhaustive, map-based, spatial datasets to cover different scenarios for spatial anomaly applications. The proposed ensemble anomaly detection method integrates domain expertise, spatial continuity, and scale of interest. We suggest using the proposed method as an automated tool to effectively identify the spatial local anomalies, based on the rigorous use of spatial continuity and volume variance from geostatistics, to focus professional time.

Effects of Randomized Treatment With Icosapent Ethyl and a Mineral Oil Comparator on Interleukin-1β, Interleukin-6, C-Reactive Protein, Oxidized Low-Density Lipoprotein Cholesterol, Homocysteine, Lipoprotein(a), and Lipoprotein-Associated Phospholipase A2: A REDUCE-IT Biomarker Substudy.

REDUCE-IT (Reduction of Cardiovascular Events With Icosapent Ethyl-Intervention Trial) reported a 25% relative risk reduction in major adverse cardiovascular events with use of icosapent ethyl compared with pharmaceutical grade mineral oil. The mechanisms underlying this benefit remain uncertain. We explored whether treatment allocation in REDUCE-IT might affect a series of biomarkers in pathways known to associate with atherosclerosis risk. Serum levels of interleukin-1β, interleukin-6, high-sensitivity C-reactive protein, oxidized low-density lipoprotein cholesterol, homocysteine, lipoprotein(a), and lipoprotein-associated phospholipase A2 (Lp-PLA2) were measured at baseline, at 12 months, at 24 months, and at the end-of-study visit among REDUCE-IT participants with triglyceride levels ≥135 mg/dL and <500 mg/dL who were randomly allocated to treatment with either 4 grams daily of icosapent ethyl or mineral oil used as a comparator. At baseline, median levels of each biomarker were similar in the 2 treatment groups. The levels of biomarkers associated with atherosclerosis increased over time among those allocated to mineral oil treatment; in this group at 12 months, the median percent increases from baseline were 1.5% for homocysteine, 2.2% for lipoprotein(a), 10.9% for oxidized low-density lipoprotein cholesterol, 16.2% for interleukin-6, 18.5% for lipoprotein-associated phospholipase A2, 21.9% for high-sensitivity C-reactive protein, and 28.9% for interleukin-1β (all P values <0.001), with similar changes at 24 months. In the icosapent ethyl group, there were minimal changes in these biomarkers at 12 and 24 months. As such, at study conclusion, between-group treatment differences largely reflected increases in the mineral oil group with median percent differences of 2.4% for lipoprotein(a), 3.0% for homocysteine, 4.2% for oxidized low-density lipoprotein cholesterol, 19.8% for interleukin-6, 26.2% for Lp-PLA2, 38.5% for high-sensitivity C-reactive protein, and 48.7% for interleukin-1β (all P values ≤0.007). These data are consistent with previous REDUCE-IT results in which the median percent change for low-density lipoprotein cholesterol at 12 months was -1.2% among those allocated to icosapent ethyl and 10.9% among those allocated to the mineral oil comparator. Among participants in REDUCE-IT, allocation to icosapent ethyl had minimal effects on a series of biomarkers associated with atherosclerotic disease, whereas levels increased among those allocated to mineral oil. The effect of these findings on interpretation of the overall risk reductions in clinical events observed within REDUCE-IT is uncertain. URL: https://www. gov; Unique identifier: NCT01492361.

Extraction of rare earth and cobalt from leach residue of Nd-Fe-B waste by reductive leaching with iron powder

After recovering rare earth from neodymium–iron–boron (Nd–Fe–B) magnet waste via oxidation roasting–hydrochloric acid leaching, extracting rare earths and cobalt from remaining leach residue, containing about 0.67% (w/w) RE and 0.36% Co, is environmentally and economically important. However, extracting valuable elements from low–grade minerals remains challenging. The purpose of this study is to accelerate the dissolution of rare earths and cobalt from leach residue of Nd–Fe–B waste (MWLR) under low acidity by adding iron as a reductant, which is conducive to destroying the main phase iron oxide. To optimize the leaching process of MWLR in a sulfuric acid system, the effects of reaction temperature, reaction time, sulfuric acid dosage, solid/liquid (S/L) ratio, reductant addition time and reductant dosage were investigated. Circa 87.9% Fe, 99.7% Co, 99.4% Nd, 73.2% Pr and 87.9% Ce were leached. Furthermore, kinetic results indicated that the leaching process, controlled by a combination of internal diffusion and surface chemical reaction, changed to a surface chemical reaction control in the presence of Fe added as the reductant. This research proposed and verified a way to extract low–grade rare earths and cobalt from MWLR, and investigated the mechanism of reductive leaching process.

Совершенствование методов рудоподготовки минерального сырья при освоении сложноструктурных месторождений

The article assesses available methods of managing mineral grades in mining and possible ways to improve the mining efficiency. Assessment criteria for the ore masses are given depending on mineral and chemical composition, structural and other features. The outcomes are presented of developing a methodology of zoning technological types of ores within an open pit with account of complex evaluation of qualitative characteristics of minerals using modern geoinformation technologies. Two main methods, i.e. express and detailed, are proposed for data interpretation in geoinformation systems, which require preliminary creation of a geological database and allow to make reliable assessment and zoning of ores within an open pit based on qualitative indicators. The methods are different in terms of labour intensity, level of detail and the possibility of adjusting the resulting models depending on established or changed requirements towards the mineral grade. An enhanced mining and geological information system allows zoning of technological types and grades of ores within an open-pit with a high degree of reliability, which contributes to the selection of the most effective ore treatment method as part of the ore grade management for specific mining and geological conditions at the planning stage of mining operations. Examples of zoning technological types of ores within an open pit as well as methodological approaches to selecting effective methods of ore grade management are presented for deteriorating mining and geological conditions of deposits and increasing requirements towards the quality of products.

Electron Backscatter Diffraction Study of Ultrahigh-Pressure Tso Morari Eclogites (Trans-Himalayan Collisional Zone): Implications for Strain Regime Transition from Constrictional to Plane Strain during Exhumation

Abstract The Tso Morari Crystalline Complex (TMCC) of trans-Himalaya (eastern Ladakh, India) contains enclaves of ultrahigh-pressure eclogites that underwent deep burial (≥80 km) and subsequent rapid exhumation during continental subduction, collision, and final accretion of the Indian plate with the Eurasian plate. We present an electron backscatter diffraction (EBSD) study of eight eclogite samples to investigate the deformation mechanism and strain regimes active during peak (HP) metamorphism and subsequent postpeak rapid exhumation of the TMCC. Our study shows that the least retrogressed eclogite exhibits strong linear fabric (L tectonite) characterized by omphacite, having [001] axes parallel to and (110) poles perpendicular to lineation. These features concur with constrictional strain during peak (HP) metamorphism. A transitional planolinear fabric (LS tectonite) is shown by other eclogites that show petrographic evidence of omphacite alteration to amphibole and the presence of lower metamorphic grade minerals like actinolite and chlorite. Characteristics of lattice preferred orientation (LPO) of omphacite and quartz, indicated, respectively, by the LS and B indices, also suggest variation in strain regime from pristine eclogites to their altered counterparts. Based on these results, it is suggested that a constrictional strain regime prevailed during peak (HP) metamorphism in the TMCC due to the buoyant rise of TMCC in response to slab break-off and reverse slab pull during and after the deepest continental subduction. This buoyant rise was also facilitated by compression related to the ongoing India-Eurasia collision. This regime evolved later to plane strain that was superimposed on the UHP rocks at a shallower depth. It is plausibly associated with foliation-parallel extension during exhumation at midcrustal depths. A high-temperature prism c-slip in quartz shown by few samples is interpreted to have formed due to a subsequent granulite facies metamorphic overprint on the eclogite during collisional thickening.

Multigaussian and plurigaussian simulation to quantify uncertainty in estimating ore grades and rock types in copper deposits [Simulación multigaussiana y plurigaussiana para cuantificar incertidumbre en la estimación de leyes de mineral y tipos de rocas en yacimientos cupríferos

The main objective of this researching was to quantify the uncertainty of a copper deposit using multigaussian simulation of grades of rock types. The developed algorithms for simulation of categorical variables, usgsim for continuous variables and algorithms programmed in Python 3.0. The dimensions of a block are 20x20x15m indexed 81x109x58 in xyz; making a total of 512 082 blocks. The results of the categorical simulations show that there is a probability (p.v. ≥ 0.8) of 19 987, 227 387 and 49 036 blocks for rock type 1, 2 and 3, respectively. Consequently, the quantified uncertainty for this threshold (0.8) is 20 %; representing 58 % of the blocks. On the other hand, the quantification of the uncertainty of continuous variables (associated with grades of Cu and Mo), not less than 90, 80 and 70 %, based on cut-off thresholds of variance per block, resulted in lithology One 353, 1900 and 7553 blocks with Cu grades, which represents 0.07, 0.37 and 1.49 % of the total blocks, respectively; a total of 24, 139 and 582 blocks with grades of Mo,&#x0D; representing 0.006, 0.027 and 0.114 % of the total blocks; for lithology Two there were 106, 648 and 2739 blocks with Cu grades, which represents 0.021, 0.127 and 0.535 % of the total blocks; a total of 32, 129 and 357 blocks with grades of Mo, which represents 0.006, 0.025 and 0.070 % of the total blocks; finally for lithology 3 there were 478, 2324 and 8804 blocks with Cu grades, which represents 0.093, 0.454 and 1.719 % of the total blocks; a total of 93, 355 and 982 blocks with grades of Mo, which represents 0.018, 0.069 and 0.192 % of the total blocks. &#x0D; Finally, it is concluded that it was possible to quantify the uncertainty in the estimation of mineral grades and rock types in a copper deposit.

Chemical Dissolution of Chalcopyrite Concentrate in Choline Chloride Ethylene Glycol Deep Eutectic Solvent

Currently, the high demand for copper is in direct contrast with the decrease in the mineral grade and, more significantly, the concerns regarding the environmental impact that arise as a result of processing such low-grade materials. Consequently, new mineral processing concepts are needed. This work explores the chemical dissolution of chalcopyrite concentrate at ambient pressure and moderate temperatures in a deep eutectic solvent. Copper and iron are dissolved without changing their oxidation state, without solvent pH change, and stabilized as a chloride complex with no evidence of passivation. Chemical equilibria of the metallic chloride complexes limit the dissolution, and the step that is rate-controlling of the kinetics is the interdiffusion of species in the solvent. The chemical mechanism may involve initial chloride adsorption at positive sites of the solid surface, pointing out the importance of surfaces states on chalcopyrite particles. A model based on a shrinking particle coupled with pseudo-second-order increase in the liquid concentration of copper describes the dissolution kinetics and demonstrates the importance of the liquid to solid ratio. Iron and copper can be recovered separately from the solvent, which highlights that this concept is an interesting alternative to both redox-hydrometallurgy and pyrometallurgy to obtain copper by the processing of chalcopyrite concentrate.

Improving first-principle model accuracy using a hybrid approach: A case study to high pressure grinding rolls in mineral industry

High-pressure grinding rolls are key assets in ore processing because of their low energy consumption and high capacity. Accurately predicting the purity of the obtained product is paramount as it directly impacts the predicted economic benefits. First-principle models of grinding- flotation circuits can be used to predict the product grade. These models can, however, exhibit deviations from actual process values (“model-plant mismatch”). Deviations between first-principle models and actual processes originate mainly from unmodeled or poorly approximated relationships between process variables. This paper presents a hybrid modeling approach to improve the prediction of mineral grade in first-principle models of grinding flotation circuits. A Multi-Layer Perceptron (MLP) is combined with a first-principle model to reconstruct the mismatch due to the unmeasured effects of grain size distribution on the mineral grade. Two different backup soft sensors are proposed to predict the product mineral grade when two separate faults occur in the online grade analyzer. The hybrid model is able to estimate the mismatch with a coefficient of determination (R2) of 0.97 and a mean absolute error (MAE) of 0.011.

Glass production using tailing of upgraded rare metal mineralization, Abu Rusheid area – Egypt for nuclear waste immobilization

Most research activities in the nuclear mining industries are directed to separation of heavy and radioactive minerals from rocks and sediments. This process is completed without utilizing tailing and mineral waste materials. Tailing materials containing radioactive wastes are considered as a major environmental problem; especially with increasing the exploration of metals and lower grade mineral deposits. In the present work, borosilicate glass could be prepared for immobilizing these nuclear wastes in the designing compositions by melting at 1200–1250 °C. NaI (TI) gamma-ray spectroscopy system was used to detect 238U, 232Th, 226Ra, and 40K concentrations in tailing materials and prepared glass to emphasize their safe dose. The produced glass was characterized by XRD, SEM, FTIR, and UV spectrophotometer. Vickers hardness and leaching properties were also studied. The results showed that compact - structured glass with high durability towards groundwater was obtained. All studied environmental parameters indicated that the glass radiation dose was lower compared to international averages, thus the glass can be safely used in nuclear waste immobilization.

Geometallurgical Characterisation with Portable FTIR: Application to Sediment-Hosted Cu-Co Ores

Cobalt (Co) mine production primarily originates from the sediment-hosted copper (Cu) deposits of the Democratic Republic of Congo (DRC). These deposits usually consist of three ore zones with a supergene oxide ore blanket overlying a transition zone which grades into a sulphide zone at depth. Each of these zones display a mineral assemblage with varying gangue mineralogy and, most importantly, a distinct state of oxidation of the mineralisation. This has direct implications for Cu and Co extraction during mineral processing as it dictates which processing method is to be used (i.e., leaching vs. flotation) and affects the performance of these. To optimise resource efficiency, reduce technical risks and environmental impacts, comprehensive understanding of variation of ore mineralogy and texture in the deposit is essential. By defining geometallurgical ore types according to their inferred metallurgical behaviour, this information can serve to classify the resources and improve resource management. To obtain insight into the spatial distribution of mineral grades, it is necessary to develop techniques that have the potential to measure rapidly and, preferably, within the mine at relatively low-cost. In this study, the application of portable Fourier transformed infrared (FTIR) spectroscopy is investigated to measure the mineralogy of drill core samples. A set of samples from a sediment-hosted Cu-Co deposit in DRC was selected to test this approach. Results were validated using automated mineralogy (QEMSCAN). Prediction of gangue and target mineral grades from the FTIR spectra was achieved through partial least squares regression (PLS-R) combined with competitive adaptive reweighted sampling (CARS). It is shown that the modal mineralogy obtained from FTIR can be used to classify the ore according to type of mineralisation and gangue mineralogy into geometallurgical ore types. This classification supports selection of a suitable processing route and is likely to affect the overall process performance.