Search Results (903)

To satisfy the industrial standards for phosphate products, phosphate ore must undergo beneficiation for the removal of gangue minerals such as carbonate minerals, silicate minerals, and clay minerals. Reverse flotation is commonly used to remove carbonate minerals from apatite. However, reverse flotation removes carbonate gangue minerals but fails to eliminate silicate and clay minerals. The use of pre-concentration (such as dense-medium cyclones and photoelectric sorting) in phosphate ore beneficiation enables the early rejection of gangue before the ore enters the fine-grinding and complex flotation circuits, thereby providing a range of technical and economic benefits. In addition, pre-concentration holds the potential to reject silicate and clay minerals in the beneficiation of phosphate ore. The phosphate ore investigated in this study was obtained from Hubei, China. It is characterized by well-defined gangue banding, which facilitates the liberation of some gangue minerals at relatively coarse comminution sizes (−15 + 0.5 mm). Based on these characteristics, photoelectric separation and dense-medium cyclone separation were employed as pre-concentration methods prior to reverse flotation, with the aim of achieving economically viable recoveries and marketable product grades. The results indicate that the combined dense-medium cyclone separation–reverse flotation process was the most effective for this phosphate ore, producing a final concentrate with a P₂O₅ grade of 31.08% and a recovery of 81.91%. Comparative evaluation reveals notable differences in gangue removal efficiency among the tested processes. While both reverse flotation and the combined photoelectric separation–reverse flotation process effectively removed dolomite, the dense-medium cyclone separation–reverse flotation process demonstrated superior overall performance by enabling the simultaneous removal of both silicate and dolomite impurities. Full article

For nearly a century, flotation kinetics has relied on deterministic first-order rate equations treating the cell as a homogeneous reactor, a paradigm that faces significant limitations for heterogeneous ores, especially coal, whose organic macerals, porosity, and oxidation susceptibility defy a single rate constant. While more advanced distributed-k, mixed-order, and population-balance models can account for certain types of particle heterogeneity (e.g., size or liberation), they still assume that the floatability distribution remains invariant during flotation, an assumption that fails when surface chemistry evolves concurrently with the separation process. Breaking from chronological cataloguing, this review proposes a three-dimensional taxonomy based on physical scale, inherent material heterogeneity, and epistemic certainty. We demonstrate that critical industrial prediction failures arise from structural mismatches between model physics and particle surface chemistry, notably time-dependent oxidation deactivation and selective maceral recovery. Six fundamental failure modes are identified, from neglected time-dependence of rate constants to the absence of a thermodynamic deactivation term, corroborated by experimental evidence from coal and base-metal flotation. Advanced microfluidic, automated mineralogical, surface-sensitive spectromicroscopic, CFD-DEM, and physics-informed machine learning tools are dismantling the black box of the flotation rate constant “k”. We introduce the Distributed Reactive Surface Kinetics (DRSK) framework, which embeds particle-scale heterogeneity into a population balance via an adaptive surface-sensitive selection function and treats kinetic uncertainty through stochastic differential equations. A comprehensive comparison table facilitates the transition from conventional models to the DRSK paradigm. We conclude with a roadmap for flotation kinetics 4.0, where digital twins, real-time froth analytics, and self-calibrating hybrid models transform this empirical discipline into a truly predictive engineering science. Quantitative validation against published coal and copper flotation data demonstrates that DRSK reduces prediction error by 60%–75% compared to conventional first-order and distributed-k models, while providing probabilistic uncertainty bounds essential for risk-based decision-making. The framework is elaborated for coal and conventional minerals, underscoring why coal demands its own dedicated kinetic theory and how these lessons can revolutionize the processing of increasingly complex, low-grade ores and secondary resources. Full article

Reliable state identification is essential for intelligent flotation control because recovery, concentrate grade, entrainment, and mineral losses are only partially observable online. This systematic review examines field instrumentation, online analyzers, froth imaging, temporal synchronization, machine-vision methods, multimodal soft sensing, and the engineering requirements that determine whether a predictive model can operate as an industrial sensor. Scopus and Web of Science publications from 2021 to June 2026 were screened using a PRISMA-based protocol. The systematic evidence base includes 98 peer-reviewed technical studies published between 2021 and June 2026, and two PRISMA methodological publications are used to ensure the methodology for presenting the review. Additional methodological and contextual sources cited outside the systematic body of evidence are not included in the number of studies reflected in PRISMA. The evidence shows that machine vision is the most mature non-contact sensing approach, supporting bubble-size measurement, froth-velocity estimation, operating-state recognition, grade prediction, and visual monitoring. Current research is shifting from handcrafted descriptors toward convolutional, transformer, self-supervised, graph-based, temporal, and multimodal models. However, predictive accuracy alone does not demonstrate industrial readiness when camera geometry, illumination, contamination, delay compensation, temporal leakage, domain shift, uncertainty, inference latency, and SCADA/PLC integration are not evaluated. A five-dimensional Sensor Readiness Index is proposed to assess metrological validity, temporal integrity, validation rigor, operational robustness, and automation integration. The review defines the principal requirements for reliable industrial deployment of flotation sensing systems. Full article

Pyrite is one of the most common sulfide minerals in polymetallic sulfide ores, and its flotation behavior directly affects the selective separation efficiency of valuable minerals. This study investigated the effects of collector type, pulp pH, pH regulator, and combined collector ratio on pyrite flotation using sodium butyl xanthate (SBX), diethyl dithiocarbamate (DDTC), ammonium dibutyl dithiophosphate (ADDP), and Aerophine 3418A (3418A), together with cyclic voltammetry (CV) and DFTB analyses. The results showed that DDTC and SBX exhibited stronger collecting ability than 3418A and ADDP at natural pH. Increasing pH significantly depressed pyrite flotation, with CaO exerting stronger inhibition than NaOH. Combined collectors displayed pronounced component dependence and ratio sensitivity. CV results indicated that collector adsorption on pyrite is an irreversible electrochemical process, and that calcium-bearing species in the CaO system passivate surface active sites, thereby inhibiting collector adsorption. DFTB calculations revealed that collecting performance is governed by the coordination stability of double-bonded S atoms with surface Fe sites and resistance to hydration. The research results can provide a theoretical basis for regulating pyrite flotation behavior and optimizing reagent regimes in the flotation separation process of complex sulfide ores. Full article

As emerging persistent contaminants, microplastics (MPs) are ubiquitous in aquatic environments. Wastewater treatment plants (WWTPs) act as critical sinks and sources of MPs, and their MPs removal efficiency can strongly influence aquatic ecological safety. To investigate how different process configurations affect MPs occurrence and removal performance, four municipal WWTPs equipped with diverse biological and advanced treatment processes were sampled and analyzed. MPs were extracted via density flotation combined with H₂O₂ digestion, and their morphological and polymeric features were identified using stereomicroscopy and Fourier-transform infrared (FTIR) spectroscopy. The results revealed that MPs removal efficiencies differed significantly across treatment processes: WWTP4 exhibited the highest comprehensive removal efficiency of 63.89% in the operational situations, followed by WWTP1 of 56.25% and WWTP3 of 51.61%, while WWTP2 exhibited the weakest elimination capacity of 28.12%. It could also be concluded that the differences were primarily governed by biological adsorption and advanced filtration units. Meanwhile, Fragmented and pellet MPs showed higher removal efficiencies than fibrous and film-shaped MPs, while Polymers including PVC, PS, PTFE and PP were more resistant to removal. Longer hydraulic retention time (HRT) and a stable and sufficiently long sludge retention time (SRT) promoted the association of MPs with activated sludge, whereas excessive aeration induced MPs fragmentation and resuspension. Optimizing operational parameters and upgrading advanced filtration facilities could facilitate the regulation and management of MPs. This study provides a theoretical basis for mitigating MPs emissions from municipal WWTPs. Full article

As a critical strategic resource in the 21st century, the efficient separation of lithium poses a major challenge in mineral processing. To address the issue of the low flotation separation efficiency caused by the similar surface properties of spodumene, lepidolite, and gangue minerals such as feldspar, this study systematically investigates the effects and mechanisms of NaOH/Na₂CO₃ mixed alkali pretreatment on the flotation behavior of the three minerals. The results show that pretreatment with a specific mass ratio of mixed alkali (NaOH:Na₂CO₃ = 5:2) can significantly enhance the flotation recovery of spodumene and lepidolite, while having minimal impact on the recovery of feldspar. After mixed alkali pretreatment, the flotation recovery of spodumene rises from less than 10% to 87.90%, and lepidolite recovery increases from below 10% to 90.1%, whereas feldspar recovery remains lower than 14% throughout the tests. Mechanistic analysis reveals that the mixed alkali system selectively promotes the breakage of Al-O bonds on the surfaces of lithium minerals, accelerating the differential dissolution of Al and Si, which leads to a decrease in the Al/Si ratio on the mineral surfaces and the formation of Al-enriched active sites. Meanwhile, Na₂CO₃ plays a selective regulatory role by adjusting the interfacial ionic environment and suppressing excessive attack by OH⁻. XPS analysis indicates a significant increase in the proportion of high-binding-energy Al species on the surfaces of lithium minerals after pretreatment, with no obvious changes observed on the feldspar surface. SEM-EDS and XRD confirm the cleaning, modification, and secondary precipitation behavior of the mineral surfaces induced by the pretreatment. Specific surface area analysis further demonstrates that moderate alkali etching reduces the surface energy and porosity of lithium minerals, facilitating subsequent collector adsorption. The bench-scale closed-circuit flotation of real complex lithium ore (1.21% Li₂O) finally yields lithium concentrate grading of 5.52% Li₂O with a Li₂O recovery of 76.82%. This study deepens the understanding of the interfacial reaction mechanisms of lithium minerals under alkaline conditions and provides theoretical support for the development of efficient and environmentally friendly flotation processes for lithium ores. Full article

Although the mineralogical form of occurrence of critical metals is widely recognised as a key factor controlling their recovery during beneficiation, this relationship has rarely been verified directly on freshly mined ore and its primary beneficiation products from Central Asian polymetallic deposits. This raises the research question of how the mineralogical mode of occurrence of Bi, In, Cd, Co, Se, Te and Re governs their distribution between gravity and flotation products. Accordingly, the aim of this study was to establish how the mineralogical form of occurrence of these critical metals determines their distribution among gravity-concentration and flotation products, using ores from the Zhuantobe and Strezhanskoe deposits (Kazakhstan) as a case study. To this end, the mineralogical features and distribution patterns of critical metals during gravity and flotation beneficiation of polymetallic ores from these deposits were investigated by optical microscopy, X-ray diffraction, and SEM-EDS, while metal distribution among beneficiation products was determined by chemical analysis. Sphalerite, galena, pyrrhotite, and silver tellurides were identified as the main carriers of the critical metals, with bismuth occurring as an isomorphic admixture in sphalerite (3.69 wt.%) and galena (1.85 wt.%). During flotation, distribution was governed by mineralogical affinity: cadmium and indium were preferentially concentrated in the zinc concentrate (56.31% and 15.44% recovery, respectively), bismuth in the copper–lead concentrate (23.03%), and selenium and rhenium in the copper-bearing products (23.60% and 37.05%). Correlation analysis of the gravity-concentration products confirmed a close association of cadmium with sphalerite (R² = 0.9998), bismuth with galena and sphalerite (R² = 0.9674), and cobalt with iron-bearing sulfides (R² = 0.9144). These results demonstrate that the distribution of critical metals is governed primarily by their mineralogical form of occurrence rather than by bulk ore content, providing a basis for technologies for the complex processing of polymetallic ores. Full article

Coarse particle flotation technologies have emerged to overcome the limitations of conventional flotation circuits, whose performance decreases for coarse fractions. Metso’s Coarse Particle Flotation (CPF) technology takes an approach based on feeding directly into the froth zone, where particle collection and froth transport processes occur. Currently, there are no models that link operating variables with the metallurgical performance of this technology. This work presents a model for the Metso’s CPF cell based on the two phenomena that occur simultaneously in the froth zone: particle collection and the transport of particle–bubble aggregates by the froth. The collection process is modelled using a rectangular distribution for flotation kinetics and a residence time distribution based on three perfectly mixed reactors in series: two small reactors and one large. The transport of the froth is represented as a function of froth stability, froth transport distance, and gas residence time. The model was calibrated using laboratory experimental data from copper ore, showing a maximum absolute error in Cu recovery of 2.9%. The main results showed recoveries of approximately 70% for the 300–425 μm class and approximately 50% for the +425 μm class. The size analysis showed a systematic decrease in recovery with particle size, with critical behavior at low froth depths and low superficial gas velocity. A sensitivity analysis confirmed consistent model responses to changes in the main operating variables. Full article

Iron beneficiation tailings from the Bayan Obo West Mine constitute a low-grade secondary rare-earth resource in which rare-earth minerals are finely disseminated and intricately intergrown with gangue. This study quantified the modes of occurrence of rare-earth minerals and assessed an integrated flowsheet comprising screening, magnetic separation, and flotation. The feed contained 1.32 wt.% rare-earth oxides (REOs), as determined by X-ray fluorescence spectrometry (XRF) and inductively coupled plasma optical emission spectrometry (ICP-OES). X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM-EDS), and automated mineralogy (AMICS) further showed that monazite and bastnäsite hosted 47.39% and 39.19% of the total REOs, respectively. Screening at 74 μm rejected 32.60% of the feed as a coarse fraction containing 0.65 wt.% REOs. Subsequent wet high-intensity magnetic separation reduced the mass entering flotation to 54.35% of the original feed while retaining 74.94% of the feed REOs and increasing the REO grade to 1.82 wt.%. Closed-circuit flotation with one rougher and three cleaner stages yielded a concentrate containing 51.99 wt.% REOs at an overall recovery of 52.38%. Rare-earth minerals accounted for 82.55 wt.% of the concentrate, including 41.65 wt.% monazite and 33.96 wt.% bastnäsite. This study thus demonstrated the feasibility of producing a high-grade rare-earth concentrate from the low-grade, fine-grained iron beneficiation tailings of the Bayan Obo West Mine characterized by complex mineral intergrowths, providing a practical basis for further rare-earth beneficiation and flowsheet optimization. Full article

Wastewater treatment plants (WWTPs) are essential infrastructure for urban water management. Their stable operation is critical to effluent quality and public safety. However, wastewater treatment involves complex biochemical processes and extensive electromechanical equipment. Hazards such as sludge flotation in secondary clarifiers, fire, electric shock, and toxic gas poisoning may occur. These hazards can threaten worker safety and reduce treatment efficiency. Traditional inspection mainly relies on manual patrols, fixed-camera monitoring, and experience-based judgment. These methods often have low efficiency, limited coverage, and delayed responses. To address these limitations, this paper investigates robot-based hazard detection for WWTPs. A multisource hazard detection dataset is constructed for secondary clarifiers and confined spaces, including images collected by an inspection robot. Object detection models are then applied to identify typical hazards. Comparative experiments are conducted using Faster R-CNN and several YOLO-series models. YOLOv12 achieves mAP@0.5 values of 0.917 and 0.819 for sludge flotation detection and confined space hazard detection, respectively. It also provides a good balance between detection performance and inference efficiency. The results demonstrate that robot vision combined with object detection can support intelligent inspection in WWTPs. Full article

Ilmenite is the core carrier of titanium resources in China. Conventional flotation systems generally have the problems of insufficient collector adsorption efficiency and limited separation index. Microwave pretreatment can strengthen the flotation process by activating the surface of minerals, but its regulation mechanism on the interface properties of ilmenite and the adsorption behavior of collectors remains to be systematically elucidated. Based on the previous research on the flotation separation effect of the ‘OHA + HDPA composite collector + microwave pretreatment (power of 800 W and irradiation time of 180s)’ system, this paper uses the OHA + HDPA (mass ratio 3:1) composite system as the collector and uses surface tension, contact angle, Zeta potential, infrared spectroscopy and X-ray photoelectron spectroscopy, and other multi-scale complementary characterization methods to systematically study the effect of microwave activation on the wettability of ilmenite surface and the adsorption of collector interface. The results show that the wettability of ilmenite surface by microwaves presents a two-way regulation characteristic. In a pure water system, microwave activation increases the surface polar active sites, the water contact angle decreases from 48.44° to 46.65°, and the hydrophilicity is slightly enhanced. Under the action of the collector, microwaves promoted the directional adsorption and orderly arrangement of reagents, the contact angle of minerals increased to 85.24°, the adhesion work reached 0.560 J/m², and the surface hydrophobicity and solid–gas adhesion ability were significantly improved. Interfacial electrokinetic analysis showed that microwave activation enhanced the positive surface charge of ilmenite, and the isoelectric point shifted from pH 5.1 to alkaline to pH 6.3. In the range of pH 2–10, the Zeta potential of the sample after microwave treatment shifted more negatively, which was due to the synergistic enhancement of electrostatic attraction and chemical chelation sites. Microscopic characterization confirmed that the collector was attached to the surface of ilmenite in the form of chemical adsorption. Microwaves did not change the essential properties of adsorption but increased the adsorption capacity of the collector by 10.9%, and the adsorption layer was more compact and orderly. A mechanism analysis reveals that microwave irradiation induces the oxidation of surface Fe²⁺ to Fe³⁺, and its atomic proportion increases from 23.91% to 38.64%, which significantly enhances the chelation between the collector and the iron site and the stability of the chemical bond. At the same time, combined with the change of XPS coordination environment, it is speculated that microwaves can induce lattice distortion, change the coordination environment of titanium atoms, increase the proportion of Ti-O-Fe bridge oxygen structure, increase the unsaturated titanium active site, and strengthen the coordination between the collector and the titanium site. The synergistic activation of iron–titanium multi-sites together enhances the adsorption strength and adsorption capacity of the collector. This study can provide theoretical support at the interface chemical level for the development of high-efficiency ilmenite flotation process. Full article

Reuse of industrial wastewater contributes to the conservation of freshwater resources and the implementation of the principles of the circular economy. In this study, the cyclic performance of a flat-sheet polyamide reverse osmosis membrane (PA-RO) for the advanced treatment of wastewater from a poultry slaughterhouse, pretreated by dissolved air flotation (DAF), was evaluated. The membrane was operated at three recirculation flow rates in successive filtration and chemical cleaning cycles to evaluate its hydraulic behavior, retention efficiency, fouling evolution, and permeate quality. Among the conditions investigated, the recirculation flow rate of 0.5 L/min provided the highest hydraulic stability and flux recovery under the investigated conditions, although hydraulic and microbiological performances were not optimized under the same operating conditions. The progressive deterioration of membrane performance during cyclic operation was associated with the accumulation of reversible and irreversible fouling, evidenced by the increase in hydraulic resistances and the incomplete flux recovery after chemical cleaning. Hierarchical clustering analysis (HCA) and mathematical modeling revealed strong relationships between operating conditions, membrane performance, and fouling evolution, generating predictive models with high coefficients of determination. The results demonstrate the potential of the cyclic operation of the PA-RO membrane to obtain a high-quality permeate intended for industrial reuse and provide a practical framework for optimizing operating conditions and fouling control strategies in membrane wastewater treatment processes. Full article

The Damiao titanomagnetite deposit on the northern margin of the North China Craton is a typical Fe-Ti-P polymetallic ore with significant deep resource potential. However, the mineralogical factors controlling its beneficiation remain poorly quantified. This study integrates multi-element analysis, chemical phase analysis, XRD, EPMA, and MLA to systematically characterize the ore’s chemistry, mineralogy, element deportment, grain size, dissemination, and liberation. Results show that Fe (25.81% TFe), Ti (6.50% TiO₂), and P (0.95% P₂O₅) are the main valuables. Fe is mainly in magnetite (59.53%), Ti in ilmenite (48.90%) and rutile (33.89%), and P almost entirely in fluorapatite. Magnetite, ilmenite, apatite, and pyrite are coarse-grained and achieve >80% free + rich intergrowths at 60% passing −0.074 mm, while rutile is fine and poorly liberated, representing the key titanium bottleneck. Silicate-bound iron (28.07% of Fe) causes irreversible loss; Ca-gangue (>20%) and chlorite slimes interfere with flotation. A staged flowsheet—primary grinding, magnetic separation, regrinding of rough concentrate, desulfurization, and sequential flotation—is proposed. This work provides a mineralogical basis for process optimization and offers references for similar deposits. Full article

In the wet-process stage of lithium-ion battery manufacturing, double-sided coating combined with air-flotation drying can reduce repeated drying operations, thereby helping improve production throughput. However, the requirements of air-flotation drying for equipment stability, together with the coupling among process parameters such as temperature, air velocity, and tension, substantially increase the difficulty of process-parameter calibration. As critical components degrade over time, deviations arise between nominal process parameters and actual operating conditions, introducing non-negligible uncertainty and further complicating parameter recalibration. This paper proposes a collaborative robust multi-objective optimization algorithm to obtain stable and reliable process-parameter combinations under limited computational resources. Specifically, multi-objective optimization models are first established. Then, the operating condition of new equipment is approximately formulated as an undisturbed auxiliary optimization problem, whereas the operating condition of aged equipment with parameter perturbations is formulated as a robust optimization problem; surrogate models are constructed for both problems. Finally, search information from the auxiliary problem is used to guide the evolution of the robust optimization problem, thereby improving its optimization efficiency. Experimental results demonstrate that the proposed algorithm can obtain robust Pareto solutions with favorable convergence and diversity while consuming fewer resources, providing engineers with reliable references for selecting suitable process parameters. Full article

Artificial intelligence (AI) is increasingly being investigated to support decision-making and process improvement in copper mineral processing and extractive metallurgy; however, the available evidence remains fragmented across operational units, methods, sustainability dimensions, and geographical contexts. This systematic mapping review, complemented by qualitative cross-study synthesis, analysed publications from 2014 to 2025 retrieved from IEEE Xplore, Scopus, and Google Scholar. Of the 410 records identified before screening, 71 studies were classified according to four predefined research questions addressing copper-processing operations, AI domains, sustainability contributions, and geographical distribution. The findings show an uneven distribution of research across the processing flowsheet. Comminution and froth flotation received the greatest attention, whereas lixiviation, solvent extraction, electrowinning, and electrorefining were less represented. Machine learning was the dominant AI domain, particularly supervised approaches based on historical operational data; however, no algorithm was universally superior, as reported performance depended on the dataset, target variable, operational context, and validation procedure. Most studies focused on prediction, monitoring, fault diagnosis, and operational optimisation, while reinforcement learning, hybrid mechanistic–data-driven models, adaptive control, and sustained industrial deployment remained comparatively limited. Sustainability assessments emphasised operational and economic outcomes more frequently than social, ethical, circular-economy, and broader environmental implications. Geographical results reflected the locations assigned to the reviewed studies and industrial cases rather than regional AI maturity. The review identifies data availability, heterogeneous validation practices, model transferability, and limited evidence of sustained industrial deployment as recurring challenges. It proposes a staged research agenda to develop more reliable, transferable, and human-supervised AI applications across copper-processing operations. Full article