High-Pressure Grinding Rolls (HPGR) offer significant energy-saving benefits due to their unique interparticle crushing mechanism. This study developed a novel particle-bed crushing work index testing method based on modified piston press tests, specifically designed to predict specific energy consumption in closed-circuit HPGR operations. By integrating Bond's third theory of crushing, three different ore samples were systematically tested through closed-circuit HPGR crushing tests and particle-bed crushing work index determinations, culminating in the development of a numerical particle-bed crushing work index prediction model W-i = (0.1392x+0.0346 )/(-0.1267x+1.4586)( (10)/root(PPT)(P)(80 )- (10)/root F-80 (PPT)). Results demonstrate that all tested samples achieved steady-state conditions within 7 cycles (with G-value fluctuations < 3 %). To further validate the model's applicability, four additional ore samples with distinct characteristics were examined. Results show that the relative errors between model-predicted and measured specific energy consumption were consistently maintained within 15 %, which provides substantial validation of the model's reliability. Compared with conventional pilot-scale testing, this innovative approach significantly saves both cost and testing time, providing an efficient laboratory-based predictive tool for HPGR industrial design.

Sensor-based sorting is one of the effective methods to solve the high dilution rate of ores. However, gold ores generally have problems such as low grade and fine particle size of gold, which make it difficult for detectors to directly detect gold and limit the application. This study takes a gold deposit in Shanxi as an example, demonstrating a method for gold ore sorting based on process mineralogy and gold-hosting minerals. Through the analysis of process mineralogy, the types and occurrence characteristics of gold-hosting minerals in the gold ore and their correlation with the Au grade were investigated, and the potential for the detection of gold based on gold-hosting minerals was discussed. Subsequently, XRT response characteristic tests were conducted to analyze the differences in XRT images of different ore particles and evaluate the sortability. Finally, the feasibility of XRT sorting for gold ores was verified by a sorting experiment. The results show that XRT sorting can achieve good performance indicators, such as a discard rate of 40.53

Continuous coarse particle gangue rejection from an ultra-lean magnetite ore holds much potential to significantly reduce the energy consumption and processing costs. To enhance the HPGR comminution efficiency and gangue rejection performance, a comparative study was conducted between two different circuits. The base circuit employed an HPGR integrated with dry magnetic separation in closed-loop operation. The alternative circuit incorporated an HPGR coupled with a 3 mm aperture dry screening prior to magnetic separation. Industrial-scale sampling campaigns conducted in an ultra-lean magnetite comminution plant (base circuit) revealed that the primary cause of the high HPGR recycling load (151.95

Accurate energy consumption prediction in Laboratory Stirred Millss is critical for process optimization but remains challenging due to the limitations of existing mechanistic and empirical models in capturing nonlinear, multi-parameter interactions. This study proposes a Backpropagation (BP) neural network model to predict the specific energy consumption of a WTM-5 Laboratory Stirred Mills grinding Panzhihua vanadium-titanium magnetite. Based on experimental data covering variations in residence time, rotational speed, filling rate, and pulp concentration, the model effectively characterizes the nonlinear relationships between operational parameters and energy use. The BP neural network demonstrated significantly higher predictive accuracy compared to traditional methods. Furthermore, Spearman correlation analysis identified pulp concentration as the most critical factor influencing specific energy consumption. These findings establish the BP model as a robust tool for real-time prediction and parameter optimization in fine grinding processes, laying a foundation for advanced deep learning applications in mineral processing.

Fine grinding is essential for the effective liberation and separation of iron ores with complex mineral intergrowths. In Panzhihua region of China, titano-magnetite is intimately intergrown with chlorite, amphibole, and titanium-bearing minerals, posing a considerable challenge to selective magnetic separation. To address this issue, a comprehensive mineralogical investigation was performed using X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy coupled with-energy dispersive spectroscopy (SEM-EDS), and the Advanced Mineral Identification and Characterization System (AMICS) to clarify the chemical composition, dissemination features, and liberation behavior of raw titano-magnetite concentrate. Subsequently, systematic fine grinding experiments were conducted using a laboratory-scale horizontal stirred mill to evaluate the effects of key operating parameters (i.e., stirring speed, grinding concentration, feed slurry flow rate, and media filling ratio) on particle size distribution, mineral liberation, and magnetic separation performance. The results indicate that grinding parameters exert a nonlinear influence on separation efficiency. Moderate grinding improves the liberation of titano-magnetite, whereas excessive ultrafine grinding substantially increases slime generation (the yield of the -13 mu m ultrafine fraction increased from 5.13% to 8.38%). Such over-grinding induces heterocoagulation and slime coating of gangue minerals on titano-magnetite surfaces, further causing magnetic shielding and mechanical entrainment within magnetic aggregates and thereby deteriorating separation selectivity. The optimal grinding conditions were determined as follows: a stirring speed of 2000 r/min, a grinding concentration of 40%, a feed slurry flowrate of 20 & times; 10-3 m3/h, and a media filling ratio of 75%. Under these conditions, the monomeric liberation degree of titano-magnetite increased from 87.89% to 92.38%, yielding an optimized iron concentrate with a total iron (TFe) grade of 56.34% and an iron recovery of 93.78%.This study clarifies the critical balance between fine grinding intensity and magnetic separation performance, providing a reliable theoretical and practical reference for the efficient upgrading of complex titano-magnetite resources.

Kerosene is widely used as a collector in graphite flotation, but its consumption has risen sharply in recent years due to poor water dispersibility and depleting high-quality graphite resources. This study explored the flotation behavior and mechanisms of fine/micro-fine flake graphite with hydrocarbon collectors (kerosene, aviation kerosene, 1:2 mixed hydrocarbon oil-liquid paraffin) via micro-flotation and multi-characterization (turbidity, surface tension, contact angle, FTIR, XPS, AFM). The results showed mixed hydrocarbon oil significantly improved fine-grained graphite recovery and exhibited excellent collecting performance across particle sizes. Mechanistically, aviation kerosene and the mixed hydrocarbon oil dispersed better in water, boosting collision probability with graphite and enhancing surface hydrophobicity, with contact angle changes strongly correlating with recovery. Spectroscopic analyses confirmed collectors physically adsorbed on graphite (not quartz, ensuring high selectivity), and mixed hydrocarbon oil most effectively reduced hydrophilic groups and increased hydrophobic groups on graphite surface, with its higher proportion of linear alkanes enabling stronger van der Waals adsorption, thereby achieving a substantial enhancement in the flotation recovery of fine-grained graphite.

The mining industry is one of the important engines of the world’s economy and one of the key units in energy consumption and greenhouse gas (GHG) emissions. Considering the technologies for renewable energy production are leading to increased demand for minerals and metal, it is expected that the final energy consumption per unit mass of mineral extracted is also forecast to increase due to the decline in the quality of mineral deposits, which could make the energy consumption and GHG emissions of mining industry increase in the future. Currently, the integration of mining and mineral processing (IMM) into new advanced mining-downstream processing systems is considered an effective method to alleviate the increasing environmental issues and facilitate the sustainable development of the mining industry. To date, substantial amounts of efforts have been made with varying degrees of success to construct desirable IMM systems. Nevertheless, a comprehensive and systematic discussion on IMM showing the fast-growing development of this field is still lacking. This review focuses on clarifying the potential relationship between mining and mineral processing, introducing current and emerging IMM technologies, and summarizing key achievements. It is hoped that this review inspires innovative ideas and brings technical solutions for envisioning technically and economically viable IMM systems, thereby injecting momentum into the sustainable development of the mining industry.

In the staged grinding–staged magnetic separation process of magnetite ores, the selection of suitable grinding fineness is often mainly based on empirical design or single-index evaluation, which makes it difficult to balance mineral liberation degree, energy consumption, and magnetic separation performance. To this end, taking a -3 mm magnetite ore after High Pressure Grinding Rolls (HPGR) as the research object, this paper introduces an experimental approach for determining suitable finenesses of staged grinding based on ore process mineralogy, Bond Work index, and magnetic separation performance. Process mineralogy analysis, grinding-magnetic separation tests, and Bond work index tests were carried out, with particular emphasis on optimizing the grinding fineness of the first-stage grinding process. Results showed that a grinding fineness of -0.074 mm passing 75% was suitable for the first stage grinding of this magnetite ore. Under this condition, the corresponding Bond work index was 8.00 kWh/t, while the concentrate yield of the first-stage magnetic separation was 53.32%, with MFe grade and recovery were 51.00% and 94.22%, respectively. This proposed approach effectively integrates mineralogical characteristics, grinding energy consumption, and separation performance, and can provide a valuable reference for the optimization of staged grinding–staged magnetic separation processes for fine-grained embedded magnetite ores.

Serpentine slime coating significantly deteriorates the flotation performance of sulfide minerals due to electrostatic attraction under weakly alkaline conditions. To address this issue and develop a low-toxicity reagent regime, this study introduced ammonium polyphosphate (APP), specifically with varying molecular weights, as a novel depressant to achieve the efficient separation of pyrite from serpentine. Single-mineral and artificial mixed ore flotation tests demonstrated that APP with a medium degree of polymerization (APP-2) exhibited the best performance. At pH 8.5 and an APP-2 dosage of 80mg/L, the recovery of pyrite reached 93.17% with significant rejection of serpentine. APP-2 chemically adsorbs onto the serpentine surface through the formation of stable P-O-Mg bonds, reversing its surface charge from positive to negative, while having negligible interaction with pyrite. This effectively eliminates the heterocoagulation between the two minerals. Despite these promising laboratory results, the complexity of mineral textures in run-of-mine ores remains a challenge for industrial translation. Future perspectives focus on evaluating the pilot-scale performance of APP and further exploring phosphate-based green reagents to facilitate cleaner production in sulfide flotation.

In the beneficiation process of quartz vein-type tungsten ores, the sorting operation plays an important role in the rejection of waste rocks and gangue in advance, which can greatly improve economic benefits. However, multiple-sensor-based sorting can aid in taking advantage of the heterogeneity between valuable minerals and gangue, and achieve more accurate physical separation process. This study aims to explore the response characteristics of quartz vein-type tungsten ore under visible light and X-ray, and evaluate the sortability of ores under the two sensor types, to establish an integrated sorting process based on optical and XRT sorting, realizing a staged gangue disposal of tungsten ores in the sorting process. To this end, a digital camera was used to capture the images of the optical characteristics of ores and rocks, and an XRT platform was employed to capture the XRT images of ores. Then, the optical image and XRT image were analyzed in RGB color space and grayscale respectively. Based on the optical response characteristics and XRT response characteristics of the test samples, the integrated sorting strategy was developed. Finally, the integrated sorting experiments of optical sorting and XRT sorting were carried out to verify the feasibility. The results show that the relative discard rate can reach 57.00% and the WO3 loss is only 1.01% after two stages of optical sorting and one stage of XRT sorting. For quartz vein-type tungsten ores, the combination of optical and XRT sorting can achieve complementary advantages of both physical separation methods and can also be used for the optimization of the process flowsheet, which is feasible.

In mineral processing and metallurgy, total iron grade serves as a critical indicator guiding the entire production chain from crushing to smelting, directly influencing the quality and yield of steel products. To address the limitations of conventional matrix effect correction methods in X-ray fluorescence (XRF) analysis—such as low accuracy, high time consumption, and labor-intensive procedures—this study proposes a novel hybrid model (DSCN-LS) integrating least squares (LS) with dynamically regularized stochastic configuration networks (DSCNs) for total iron ore grade quantification. Through feature analysis, we decompose the grade modeling problem into a linear structural component and nonlinear residual terms. The linear component is resolved by means of LS, while the nonlinear terms are processed by the DSCN with a dynamic regularization strategy. This strategy implements node-specific weighted regularization: weak constraints preserve salient features in high-weight-norm nodes, while strong regularization suppresses redundant information in low-weight-norm nodes, collectively enhancing model generalizability and robustness. Notably, the model was trained and validated using datasets collected directly from industrial sites, ensuring that the results reflect real-world production scenarios. Industrial validation demonstrates that the proposed method achieves an average absolute error of 0.3092, a root mean square error of 0.5561, and a coefficient of determination (R2) of 99.91% in total iron grade estimation. All metrics surpass existing benchmarks, confirming significant improvements in accuracy and operational practicality for XRF detection under complex industrial conditions

The integration of high-pressure grinding roller (HPGR) with pre-concentration techniques and stirred mills is recognized for its energy efficiency. Studies have suggested that the feed with a P80 around 1 mm is acceptable for stirred mills or coarse particle flotation. Nonetheless, published experimental data characterizing the comminution behavior of single-stage HPGR circuits configured with a 1 mm screen aperture remain scarce. Moreover, extant research remains confined to laboratory scale. Consequently, critical performance metrics, including production capacity, screening efficiency, and process continuity, have not been substantively documented in the literature. In this paper, the HPGR performance in an industrial-scale HPGR/tower mill comminution circuit was assessed and optimized by laboratory and industrial tests. The research meticulously analyzed the impact of feed rate on the industrial-scale flip-flow screen and HPGR performance and found that the HPGR featuring two studded rolls with a diameter of 800 mm and a width of 400 mm, operating in a reverse classification circuit with a scalped feed by a 14.64 m2 flip-flow screen while running continuously 24 h per day, is capable of producing a −1 mm comminution product suitable for tower mill feed. Under the optimal operating conditions identified, it achieved a specific energy consumption of 4.57 kWh/t with a feed rate of 27.08 t/h.

Phosphate ores, which are regarded as critical mineral resources, play an important role in various industrial fields. Apatite is the main source of phosphate mineral resources and must be concentrated before it is processed into industrial products. Flotation is the most commonly employed method for apatite concentration. However, as the proportion of fine apatite increases, the challenge of separating it from gangue minerals intensifies, due to the resemblance in surface characteristics between apatite and gangue. Interfacial regulation during flotation is fundamental to the process, including the regulation of the mineral/water interface wettability by flotation reagents (collectors and modifiers), the control of interactions between mineral particles, and the regulation of interactions between mineral particles and bubbles. This article introduces the surface characteristics of apatite and its main gangue minerals. It discusses innovative work on flotation reagents (primarily collectors and depressants) and their action mechanisms on mineral surfaces. It reviews the current development of theories on the regulation of interactions between interparticles and between particles and bubbles. Finally, the study outlook the future research on interfacial regulation in apatite flotation. This study is intended to offer references for the continued advancement of apatite flotation.

To enhance the performance of the combined high-pressure grinding roller (HPGR) and tower mill (TM) process for −1 mm particle size, this study addresses the key technical challenges of insufficient material quantity (<100 kg) and complex experimental procedures in HPGR closed-circuit crushing tests by proposing a novel circulating load prediction method based on the principle of mass balance and first-order crushing kinetics. Using a side-flanged HPGR WGM 6020 installation, systematic −1 mm HPGR closed-circuit crushing tests were conducted on seven different ore samples under three specific pressing forces, with detailed characterization of the dynamic variations in product size distribution, specific energy consumption, and circulating load during each cycle. The results demonstrate that within the specific pressing force range of 3.5 N/mm2 to 4.5 N/mm2 when the crushing process reaches equilibrium, the circulating load stabilizes between 100% and 200%, while the specific energy consumption is maintained within 1–2.5 kWh/t. Notably, at the specific pressing force of 4.5 N/mm2, both the circulating load and specific energy consumption rapidly achieve stable states, with ore characteristics showing no significant influence on the number of cycles. To validate the model accuracy, additional samples were tested for comparative analysis, revealing that the deviations between the model-predicted −1 mm product content and circulating load and the experimental results were less than ±5%, confirming the reliability of the proposed method.

The determination of the optimal model and parameter settings for a high-pressure roller (HPGR) frequently necessitates a substantial investment of human resources, materials, and time, which complicates the selection process and increases costs. This paper examines the indexes of the HPGR in the context of practical experiments, simulations and modeling. Furthermore, the crushing process of ore in the HPGR is simulated in terms of connecting bond breakage. It was found that the throughput is related to the roller speed but inversely proportional to the specific pressure, that the crushing efficiency is affected by the roller speed and specific pressure, and that the energy consumption is greatly affected by the specific pressure. It was demonstrated that parameters derived from ore samples from small piston ballast tests can serve as a valuable basis for modeling HPGR parameters on a semi-industrial or even industrial scale. This can serve as a guide for HPGR selection.

Serpentine is easily muddy and has a high zero electric point of zero charge (PZC), which leads to heterogeneous coagulation with pentlandite, which seriously affects the flotation of pentlandite. To solve this problem, from the new perspective of reducing the heterogeneous coagulation of pentlanditeserpentine and dispersing them, this study explored the influence of sodium tungstate as a dispersant on the dispersion of between pentlandite and serpentine using flotation tests, zeta potential tests, scanning electron microscope-energy dispersive spectrometer (SEM-EDS) examination, molecular dynamics simulation (MS), and calculations of the extended Derjaguin-Landau-Verwey-Overbeek (EDLVO) theory. The results show that 20 l m fine serpentine seriously deteriorates the flotation of pentlandite, while adding sodium tungstate can significantly promote the flotation separation of pentlandite and serpentine. MS simulation results showed that sodium tungstate could be chemisorbed with iron ions on the surface of pentlandite and mainly physisorbed with serpentine. EDLVO theoretical calculations show that after adsorption of sodium tungstate, the interaction between the two changed from attraction to repulsion at pH less than 10, and the mutual attraction was weakened at pH more significant than 10, thus weakening the heterogeneous coagulation between pentlandite and serpentine and causing serpentine to des- orb from the surface of pentlandite, thus restoring the floatability of pentlandite, which SEM-EDS also confirmed. This provides a new insight into the dispersion mechanism of sodium tungstate as the innovative dispersant that is different from other dispersants for reducing heterogeneous coagulation of pentlandite and serpentine. (c) 2024 Published by Elsevier B.V. on behalf of The Society of Powder Technology Japan. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

In this work, acid surface pretreatment improved the selective dispersion between micro-fine titanaugite (-19 mu m) and ilmenite particles in pulp. Microflotation experiments showed that as the mass percentage of micro-fine titanaugite in mixed ore increased, the separation index in ilmenite flotation decreased due to micro-fine titanaugite adsorbed on ilmenite surfaces, while acid surface pretreatment weakened this adverse effect. Turbidity, optical microscope, SEM-EDS, and EDLVO theory analyses suggested that after acid surface pretreatment, these aggregations between ilmenite particles and between titanaugite particles reinforced, and they were related to the decreased surface hydrophilicity of ilmenite and the formative calcium precipitate on titanaugite surfaces, respectively. Meanwhile, the difference in surface hydrophilicity of out-of-phase particles increased. These variations between particles led to a reduction in aggregation between out-of-phase particles. AFM adhesive force analysis proved that after acid surface pretreatment, the adhesion between micro-fine titanaugite and ilmenite particles decreased, and it was lower than the increased adhesion between in-phase particles. A greater improvement in selective dispersion between out-of-phase particles treated with acid surface pretreatment occurred in pulp, further enhancing the flotation index of ilmenite.

Surface roughness has an important effect on the interfacial properties and wettability of mineral particles, but traditional characterization methods rely on parameters such as maximum height difference, which cannot capture the small-scale structure and spatial roughness distribution. To address these limitations, this study aims to provide a comprehensive analysis of surface roughness, specifically quantifying the effects of grinding media shape (balls and rods) on surface roughness. The study employed atomic force microscopy (AFM) to characterize the surface morphology of two iron-bearing grinding products, hematite and siderite. A method based on power spectral density (PSD) was introduced, combined with the root mean square (RMS) method, to quantify the surface roughness. AFM analysis reveals that the grinding action of rod media produces more scratches on ground particle surfaces, while ball media tends to generate island-like bulges. RMS results demonstrate significantly reduced surface roughness with decreasing particle size, with diminishing differences among fine particles. Rod-milled products consistently exhibit higher roughness than ball mill outputs at equivalent particle sizes. Low-frequency peaks in PSD curves confirm the periodic scratches on rod-milled particle surfaces. These findings provide valuable insights for optimizing the roughness characterization of mineral surfaces and offer references for the selection of mineral grinding media.

The Balzhe rare earth deposit, located in Inner Mongolia, China, is a complex deposit that also contains niobium and zirconium. However, it remains undeveloped. One notable challenge is the low grades of the main valuable minerals, including xinganite, zircon, niobite, ilmenorutile, pyrochlorite, eschynite, monazite, and bastnaesite. These minerals are either weakly magnetic or associated with ilmenite, a paramagnetic mineral. To overcome this, a high-intensity magnetic method can be employed to separate these valuable minerals from the gangue minerals, thereby generating enriched products to lower the cost of the following flotation. In this study, the first step involved utilizing a high-intensity magnetic separation to enrich particles in different size fractions. It was observed that the size fraction of -0.5 + 0.02 mm was particularly suitable for effective separation. Subsequently, staged magnetic pre-concentration was conducted to obtain products with varying specific magnetization coefficients. To optimize the applied magnetic field intensity, a combination of a high-intensity magnetic separator and a superconducting magnetic separator was employed at different magnetic induction intensities. This proposed technique not only reduces reagent costs but also enhances the operational efficiency of subsequent flotation processes. By implementing this approach, it is anticipated that the Balzhe rare earth deposit can be effectively processed, overcoming the challenge of low-grade valuable minerals. This would contribute to improved economic viability and operational efficiency in the extraction of rare earth elements, niobium, and zirconium from the deposit.