High-turbulence fine particle flotation cell optimization and verification | Scientific Reports

Scientific Reports volume 14, Article number: 23124 (2024) Cite this article

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Microfine mineral particles have a small size, light weight, and low inertia, making it difficult for them to deviate from streamlines and collide with bubbles. Conventional flotation operations consume a large amount of reagents and exhibit poor flotation indicators. This study employs computational fluid dynamics (CFD) simulation and hydrodynamic testing to investigate the flow field within a high-turbulence microfine particle flotation machine equipped with a multilayer impeller–stator configuration, and validates the practical application performance of the microfine particle flotation machine through single-batch flotation experiments. Result shows that the impeller region of the traditional mechanical stirring flotation machine has a turbulent energy dissipation rate of 20 m²/s³, whereas that for the microfine particle flotation machine averages over 120 m²/s³. In the flotation verification, the cumulative recovery rate of the fine particle flotation machine is increased by 28% compared with that of the traditional KYF flotation machine. The flotation rate is also 1.3 times that of the KYF, demonstrating stronger selectivity for fine particle concentrates. It has certain guiding significance for the resource utilization of fine particle minerals.

With the continuous development of mineral resources and the massive consumption of high-grade and easily processed ores in recent years, the available mineral resources are increasingly becoming “poor in quality, fine in size, and complex in composition.”1How to utilize microfine particles and low-grade refractory ores economically and efficiently has become a severe challenge faced by the mineral processing industry2. According to the elephant curve proposed by Lynch, the efficiency of flotation rapidly decreases when the mineral particle size is less than 20 μm. For improving the concentrate grade of refractory ores, the grinding fineness should be reduced to fully liberate the target minerals. However, this approach significantly increases the difficulty of ore flotation, making it challenging to achieve with conventional flotation processes and equipment3. Statistics show that 33% of the world’s phosphate minerals, 20% of tungsten-bearing minerals, 16% of copper-bearing minerals, and millions of tons of other useful minerals are lost in tailings in the form of fine particles. This loss not only results in a waste of resources but also causes pollution to the environment surrounding the mining areas4,5. Due to the complexity of the types of minerals involved in flotation, there is currently no unified definition for the classification of particle sizes. Jung6refers to particles smaller than 10–15 μm as fine or ultrafine particles, while Yanez7designates minerals smaller than 20–30 μm as fine to ultrafine minerals. This paper focuses on non-ferrous metal ores and, in conjunction with the classic elephant curve proposed by Lynch8, which illustrates the relationship between the fineness of industrial sulfide ores and recovery rate, defines particles smaller than 10 μm as ultrafine, 10–20 μm as fine, and 20–74 μm as coarse, as depicted in Fig. 1.

Traditional flotation data and particle size division methods for industrial sulfide ore flotation.

Considering the characteristics of microfine ore particles, such as small size, low specific gravity, large specific surface area, and similar surface physicochemical properties, researchers have proposed three technical approaches from a process perspective to enhance the recovery of microfine particles: first, increasing the apparent diameter of microfine particles; second, reducing bubble size to improve the mineralization efficiency of useful minerals9,10; third, strengthening the interaction between flotation reagents and target minerals11. From the perspective of equipment, the technical approaches include altering the flow field structure in the separation space to increase the effect of turbulence on microfine particles and introducing micro- or nano-sized bubbles to enhance the selective capturing of hydrophobic microfine mineral particles12. Among these approaches, the StackCell microfine particle flotation machine by Eriez13,14 has been industrially validated. Its multistage impeller–stator strong stirring and the isolated structure design of the reaction chamber from the separation chamber have been successfully verified in semi-industrial experiments. Flotation equipment such as the Concorde Cell7,15, the Jameson Cell9, and cyclonic static microbubble flotation columns16 enhance the collision efficiency between microfine mineral particles and bubbles by reducing bubble size and promoting the detachment of mineralized particles9. However, in the development process of these devices, constructing a fluid dynamic environment that conforms to the separation of microfine mineral particles has become a primary task16,17. The study of fluid dynamic characteristics inside flotation machines commonly employs computational fluid dynamic (CFD) simulations18. Researchers often use simulation technology to perform single- or dual-phase fluid simulations on the flotation machine structure after physically setting it up to determine whether the design structure can achieve the intended goals before conducting PIV tests or clear water hydrodynamic tests19.

In this study, a high-turbulence microfine particle flotation machine (HTF) is designed on the basis of the principles of intense turbulent mineralization and weak turbulent separation. It achieves localized strong turbulence dissipation through a small impeller rotating at high speed, thereby enhancing the interaction between microfine mineral particles and bubbles. Although the technical approach of improving microfine mineral flotation indicators through strong agitation has been industrially validated in many places, the new type of strong-agitation microfine particle flotation machine has its stirring and separation zones in the same space. The characteristics of the internal flow field of the flotation machine are not clear, and the turbulent energy dissipation rates and fluid velocity vectors in different regions are undefined. The influence of different process conditions on the internal flow field of the flotation machine still needs to be explored. Due to these considerations, this research examines the hydrodynamic performance of the HTF flotation machine through CFD simulation and dynamic testing, focusing on the turbulent energy dissipation rates, fluid velocity vectors, and air dispersion characteristics in various zones. Additionally, the effectiveness of the machine in the mineral flotation process is assessed using flotation experiments.

The raw material for the flotation test in this study is obtained from the original ore of a large copper mining and processing plant. The chemical composition analysis results of the ore sample are shown in Table 1.

The copper grade in the ore sample is 0.32%, and the molybdenum grade is 0.031%. Apart from copper and molybdenum, the content of other elements that can be utilized comprehensively in the ore sample is very low.

The chemical phase analysis of the original copper in the ore is presented in Table 2.

The oxidation rate of copper is low, with the majority of copper still present in the form of sulfides, predominantly as native copper sulfide minerals. The primary metallic minerals in the ore sample are pyrite and chalcopyrite, followed by molybdenite, covellite, azurite, chalcocite, malachite, sphalerite, and galena. The gangue minerals are mostly quartz and mica, followed by feldspar, chlorite, and calcite, with minor amounts of apatite and rutile and traces of illite, saponite, zircon, monazite, xenotime, scheelite, and barite.

The mineral composition and relative content of the raw ore are listed in Table 3, and the dissemination characteristics of the main minerals in the raw ore are illustrated in Fig. 2.

(1) Chalcopyrite primarily occurs as medium-grained, irregular inclusions within the gangue (Fig. 2a). Small amounts of fine-grained chalcopyrite specks are irregularly scattered throughout the gangue (Fig. 2b). This dissemination characteristic indicates a tight intergrowth relationship between chalcopyrite and the gangue minerals, making it difficult to liberate chalcopyrite from these inclusions through grinding.

(2) A minor amount of very fine-to-fine-grained chalcopyrite is disseminated within the gangue; not only is the chalcopyrite’s grain size fine and uneven, but its shape is also quite irregular. Consequently, complete liberation of most chalcopyrite during the grinding process is challenging to achieve (Fig. 2c and d).

Dissemination Characteristics of the Original Ore (a) Medium-grained chalcopyrite is irregularly disseminated within the gangue minerals. (b) Chalcopyrite is irregularly disseminated within the gangue minerals. (c) Fine-grained chalcopyrite in the ore sample is disseminated within the gangue minerals. (d) The ore sample contains fine-grained chalcopyrite disseminated within the gangue minerals.

The degree of liberation of sulfide copper minerals is measured under a microscope at different grinding fineness conditions, and the results are shown in Table 4. Because this study utilized microfine particle flotation equipment, a fine grinding treatment of the raw ore is conducted to assess the extent to which the increased presence of microfine particles negatively impacts the flotation process and the performance of the equipment.

The mineral samples used in this study were taken from the crushed minerals of less than 2 mm in the crushing plant. A ball mill was used to grind the minerals at a grinding concentration of 50% for 25 min to obtain the pulp for flotation tests. The particle size analysis of the raw ore after ball milling was conducted using a laser particle size analyzer, with the results shown in Fig. 3.

Particle size distribution of raw ore.

The results indicate that 90% of the raw ore passed through a 200-mesh sieve, with an average particle size of 15 μm, which meets the fine particle mineral standard set in this paper.

The high-intensity turbulent microfine particle flotation machine used in this research features a multitiered impeller–stator design. It includes a bottom aeration system, an inner tank high-turbulence mineralization system, an outer tank low-turbulence separation system, a slurry circulation system, and an impeller–stator system. The impeller–stator arrangement is multitiered, with the impeller consisting of five levels, each with six blades, and the stator comprising four levels, each with six blades, fixed to the inner tank. The slurry circulation system connects the inner and outer tanks, enabling the function of suction from the bottom of the outer tank and supply to the bottom of the inner tank. Noncritical components within the model are simplified during the simulation study.

Table 5 presents the parameters for the key structural components of the high-intensity turbulent microfine particle flotation machine.

The experimental platform used for the flotation tests is shown in Fig. 4.

Flotation test platform.

The experimental platform, constructed from an acrylic material, is utilized for actual flotation test. The setup employs two peristaltic pumps to simulate the slurry flow caused by feeding and discharging, with a direct-current variable-frequency motor controlling the impeller’s rotational speed. An air compressor, in conjunction with a pressure regulator valve, a ball valve, and a gas flow meter, is used to control the volume of air supplied.

For the selection of experimental conditions, combined with the equipment design concept and standard KYF flotation machine experience parameters, the rotation speed is based on the principle of equal angular velocity and equal linear velocity, and 750 rpm-1200 rpm is selected for the experiment. The aeration rate is based on the principle of equal apparent aeration rate, that is, 0.8m3/(m2 * min) aeration rate is required for flotation of chalcopyrite, which is converted to about 60 L/min in HTF. Finally, the ore feeding rate is determined to be about 60 L/min based on the gas-liquid ratio of about 1:1 in the inner tank. Different experimental conditions are set according to the existing equipment working capacity for testing and simulation.

The experimental equipment is described in Table 6.

This research utilized CFD simulations to study the clear water hydrodynamic characteristics of the HTF flotation machine, employing the standard k-ε turbulence model to simulate the internal flow field. It was assumed that the fluid dynamics within the flotation machine had fully evolved into turbulent motion, with the effects of molecular viscosity being neglected.

The purpose of the simulation is to investigate the influence of the flotation machine’s structural design and operating parameters on the internal fluid dynamics, primarily evaluated through the hydrodynamic performance within the flotation machine. In the given experimental model, the structural dimensions are fixed. Based on these existing designs, factors such as impeller speed, ore feeding and discharging rates, and jet height significantly affect the flow characteristics within the tank. Therefore, this study focuses on how these conditions influence fluid velocity and turbulent energy dissipation rate. The ZOY plane is selected as the central longitudinal section, and the ZX plane at Y = 288 mm (the Sect. 288 mm from the tank bottom) is chosen as the central transverse section. Velocity vector plots are analyzed using the central longitudinal section to understand the liquid-phase flow conditions in the entire tank and the central transverse section to analyze the flow conditions at the jet outlet section. A schematic for the central longitudinal and transverse sections is shown in Fig. 5. In the simulation model, a circular plane with a radius of 61 mm and a height ranging from 0.284 to 0.289 from the bottom is extracted as the jet outlet plane, and the flow velocity of this plane is taken as the jet outlet flow rate. In the experiment, to compare with the simulation results, the velocity at the jet orifice position was measured using a S-type Pitot tube under the same conditions. The measurement position is shown in Fig. 6.

Schematic of the central longitudinal and transverse sections.

Schematic diagram of flow velocity measurement at the jet port.

Air dispersion is a metric used to assess the dispersion effect of the gas introduced within the flotation cell. It is obtained by measuring the actual superficial gas velocity at various points within the flotation cell and then performing calculations. The superficial gas velocity refers to the volume of air entering per unit area of the flotation cell per unit time, commonly denoted by \(\:{J}_{g}\)​. In this study, the drainage gas collection method was employed to test the gas holdup rate. Several points were selected within the flotation tank, as shown in Fig. 7. An organic glass tube with a calibrated height and a sealed end was used; it was filled with water and then inverted in the flotation tank. The time required for the gas to displace a certain height of water was recorded. During the measurement, the volume of displaced water was used to represent the volume of air. The measured gas holdup rate in the flotation cell can be expressed as follows:

The formula for calculating the air dispersion inside the flotation machine is:

Distribution map of inflation measurement points.

For comparing flotation machine performance, without specific requirements for flotation indices, a one-step rougher flotation process is adopted. The pH level for flotation is controlled at around 8.5 using lime, with a collector dosage of 44 g/t and a total flotation time of 10 min. Samples are taken every minute for the first 5 min and then combined for the last 5 min to analyze the flotation dynamics.

The experiments are divided into four groups based on their objectives:

The stirring intensity condition test for the HTF flotation machine, which explores the flotation indices under two different rotational speed conditions of 750 and 1200 rpm.

The jet height condition test, which investigates the flotation indices for the HTF flotation machine with three different jet heights from the tank bottom: 50, 90, and 130 mm.

The air supply condition test, which examines the flotation indices of the HTF under low- and high-air-volume conditions.

Comparative tests between different machine models to analyze the differences in flotation indices between the HTF flotation machine and the standard KYF flotation machine.

Under the condition of a feed rate of 90 L/min, the velocity vector plots of the internal longitudinal section of the tank at different rotational speeds are shown in Fig. 8.

Velocity vector plots of the central longitudinal section at different rotational speeds.

Owing to the confinement of the inner tank, most of the turbulence created by the impeller agitation is formed within this space. As the impeller agitation intensifies, radial and axial flows within the inner tank strengthen. The flow velocity reaches its maximum at the jet outlet position. In the outer tank, only the area around the external disperser disc experiences high flow velocities; those in other regions are below 1 m/s. Particularly, the bottom of the outer tank experiences downward flow because of the suction effect of the circulation, and the absence of agitation structures in the outer tank may lead to sedimentation. Near the outer stator area, as the rotational speed increases, the flow velocity at the jet outlet position rises significantly. The fluid, after being flung out by the upper impeller, strikes the outer stator and achieves uniform dispersion in the outer tank. Therefore, a certain jet velocity is essential for achieving uniform dispersion of materials in the outer tank.

Under a rotational speed of 1200 rpm, the velocity vector plots of the internal longitudinal section of the tank at different feed rates are shown in Fig. 9.

Velocity vector plots of the central longitudinal section at different feed rates.

From the subfigures, increasing the feed rate primarily affects the axial flow velocity within the inner tank and the radial flow velocity at the height of the jet outlet. When the flow rate is considerably low, the impeller agitation hardly disperses the pulp in the inner tank to the outer tank. Therefore, a certain amount of upward flow is necessary in the inner tank. However, increasing the flow rate can lead to an increased local flow rate at the ore discharge port of the outer tank, which increases the downward flow velocity and is not conducive to the smooth flotation of mineralized bubbles in the outer tank. This phenomenon can also exacerbate the accumulation of settled minerals.

The velocity at the jet orifice position was measured using a Pitot tube, while simultaneously extracting the area-averaged velocity of the jet orifice ring plane from the simulation results. The effects of rotation rate and feed rate on jet port velocity are shown in Figs. 10 and 11, respectively.

Effects of rotation rate on jet port velocity.

Effects of feed rate on jet port velocity.

The velocity obtained by measurement is smaller than that by simulation because the flow rate in the slit of the jet port cannot accurately be measured by an S-pitot tube. Increasing the rotational speed is the primary method to change the flow velocity at the jet outlet. At a rotational speed of 1200 rpm, the flow velocity can reach 1.7 m/s; meanwhile, increasing the feed rate within a limited range has a minimal effect on the flow velocity at the jet outlet.

The influence of rotational speed on the turbulence energy dissipation rate is shown in Fig. 12.

Distribution of turbulence energy dissipation rate on the central longitudinal section.

Increasing the stirring intensity has a significant impact on the turbulence energy dissipation rate within the inner tank. In the outer tank, owing to the absence of direct stirring structures, the turbulence energy dissipation rate is uniformly below 0.1 \(\:{m}^{2}{s}^{-3}\), which suggests that the turbulent kinetic energy in the inner tank is mostly dissipated in the impeller–stator region. However, despite doubling the rotational speed, the turbulence energy dissipation rate in the outer tank has not significantly increased, indicating that the design of the inner and outer tanks concentrates the input energy and releases it in the inner tank, improving the energy utilization efficiency in the inner tank.

The cross-sectional velocity vectors are shown in Fig. 13. In this figure, the feed rate is 90 L/min, the rotational speed is 1200 rpm, and the height of the jet outlet from the bottom varies at 50, 90, and 130 mm.

velocity vector plots at different jet outlet heights.

The jet height has a minimal impact on the flow characteristics within the inner tank, mainly influencing the fluid dynamics as the fluid is ejected from the jet outlet into the outer tank. For structures with a low jet outlet, the pulp, after being flung out from the inner tank, is subject to significant draw-off suction from the ore discharge, which greatly increases the likelihood of mineralized bubbles not rising normally and being drawn off instead. The upper region of the outer tank exhibits a weak circulation intensity, which also negatively affects the uniform dispersion of mineralized bubbles. Nevertheless, as the jet height increases, the adverse effects of the ore discharge suction on the ejected pulp diminish. After being ejected, the pulp strikes the side walls of the outer tank, creating two circulations, upper and lower. The mineralized bubbles, through the turbulent action of the outer stator and the side walls, experience a reduction in radial velocity, thereby achieving upward flotation.

After setting a 60 L/min inflation inlet at the bottom, the gas holdup distribution cloud map 1 is shown in Fig. 14.

Cloud map of gas holdup distribution in the central section.

Research has found that after filling the bottom with air, the gas content in most areas of the inner tank is above 0.4. Excessive gas content can easily lead to the accumulation and merging of a large number of bubbles in the inner tank. Air exists in the form of voids rather than effective bubbles. There is a clearly low gas volume area below the jet port in the outer tank, which can easily form a circulation dead zone. The gas content on the outermost surface of the tank is relatively low, and the overall air dispersion situation still needs to be improved.

A solid-liquid two-phase simulation was conducted using quartz particles with an average particle size of 15 µ m, a volume concentration of 10%, and a viscosity of 6.5 mPa · s. The solid volume fraction cloud map obtained is shown in Fig. 15.

Cloud map of solid volume fraction in central section.

Research has found that due to the strong stirring of the impeller, the slurry concentration in the inner tank is relatively evenly maintained at around 10%, while in the outer tank, the concentration decreases after passing through the jet, and is uniformly suspended at the jet mouth and lower part due to the light weight and low inertia of fine mineral particles. In the outer tank, due to the lack of direct stirring by the impeller, solid particles lack the kinetic energy to be lifted upward, resulting in a lower surface concentration of the tank. This not only avoids energy waste but also avoids the forced floating of gangue minerals on the tank surface due to mechanical stirring.

The effect of rotational speed on air dispersion is shown in Fig. 16.

Effect of rotational speed on air dispersion.

At a fixed jet height, the impact of impeller speed on air dispersion is relatively minor. In contrast, the jet height has a more significant influence on air dispersion. When the jet height is set to 130 mm, the air dispersion is generally low; however, adjusting the jet height to 90 mm significantly improves the air dispersion, meeting the requirements of the separation process.

The effect of air flow rates on air dispersion is shown in Fig. 17.

The effect of air flow rates on air dispersion.

When the jet height is set to 50 mm, at lower air flow rates, the air dispersion is relatively low. As the air flow rate increases, the air dispersion effectively improves. This suggests that at a lower jet height, increasing the air flow rate can enhance the dispersion of air, which could potentially lead to higher flotation efficiency. For a jet height of 90 mm, the air dispersion continues to increase with the augmentation of the air flow rate. This implies that at this jet height, raising the air flow rate contributes to further improving the air dispersion, which may help achieve better flotation outcomes. When the jet height is 130 mm, the air dispersion generally maintains around 1.2, indicating that at this jet height, the air dispersion is not sensitive to changes in the air flow rate and remains at a relatively stable level.

The effect of Feed rates on air dispersion is shown in Fig. 18.

The effect of Feed rates on air dispersion.

When the jet height is set to 50 mm, an increase in the ore feed rate tends to cause a decrease in air dispersion. This could be due to the increased ore feed affecting the interaction between the airflow and the pulp, leading to a reduction in air dispersion. At all three jet heights (50 mm, 90 mm, 130 mm), the air dispersion peaked at an ore feed rate of 85 L/min. This suggests that there is an optimal ore feed rate that maximizes air dispersion, which can be beneficial for enhancing flotation efficiency. Among these three jet heights, the overall air dispersion was lowest when the jet height was set to 130 mm. This could imply that at higher jet heights, it is more difficult to improve air dispersion or that it is constrained by other factors.

The influence of rotational speed on the flotation indices of fine particle flotation machines is shown in Fig. 19, and its effect on the average particle size of the concentrate is illustrated in Fig. 20.

Cumulative recovery rate at different rotational speeds.

Concentrate grade under different rotational speeds.

Under high-rotational-speed conditions, the mineralization effect within the inner tank is enhanced by 100%. Combined with simulation studies, it has been shown that the high turbulence energy dissipation in the inner tank enables sufficient contact between useful minerals and chemical bubbles. Fine particle concentrates achieve good mineralization and subsequent flotation recovery in a short time. Under low-rotational-speed conditions, the cumulative recovery rate and the flotation time are lower than those under high-rotational-speed conditions. When the cumulative recovery rate is incorporated into a flotation kinetic model for analysis, the flotation rate constant at a low rotational speed is 0.26 with a theoretical recovery rate of 71.8%; at a high rotational speed, the flotation rate constant is 0.43 with a theoretical recovery rate of 88.6%. These results indicate a 65% increase in the flotation rate and a 23% increase in the theoretical maximum recovery rate. During the flotation process, under the same air supply conditions, the liquid surface stability at a low rotational speed is significantly weaker than at a high rotational speed. Increasing the rotational speed is beneficial for shearing the air in the inner tank, creating more and smaller bubbles, thereby enhancing the stability of the foam layer.

The influence of jet height on the flotation indices is demonstrated in Figs. 21 and 22.

Cumulative recovery rate under different jet heights.

Concentrate grade under different jet heights.

When the jet height is set to 96 mm, the flotation rate significantly improves, with the flotation rate constant reaching 1.57, which is substantially higher than those for the other two heights tested. The final cumulative recovery rates for the tank with a height of 56 mm is 90%, and that for the 96 mm tank is 89%, both considerably exceeding the 57% for the 136 mm tank. When the jet height is increased, the lack of bottom circulation can lead to ore accumulation, causing some useful minerals to be lost in the tailings instead of effectively participating in the cycle. Conversely, when the jet height is considerably low, mineralized bubbles that are ejected into the outer tank through the jet action are sucked back into the inner tank via the middling circulation port, reducing the flotation rate. Nevertheless, this phenomenon also results in multiple cycles of mineralization, allowing for a concentrate grade that is much higher than those at the other two heights. For ensuring a high flotation efficiency and a high recovery rate, an appropriate jet outlet height should be determined.

The influence of aeration rate on the flotation indices of fine HTF is shown in Figs. 23 and 24.

Cumulative recovery rate under different air flow rates.

Concentrate grade under different air flow rates.

Under a low air flow rate, a high grade of concentrate can be guaranteed. When the air flow rate is increased, the grade of the concentrate decreases by more than double; nevertheless, the flotation rate improves, which is due to the foam layer becoming significantly thicker with the increased air flow rate. Under high air flow rates, the production rate of the concentrate in the first minute increases from 1.71 to 4.72%, yet the theoretical maximum recovery rates between the two remain essentially unchanged. The phenomenon of ore accumulation at the tank bottom is also basically consistent. That is, on the premise that the concentrate grade is up to standard, increasing the air flow rate to a certain extent can enhance the flotation efficiency of fine particle flotation machines while maintaining good foam layer stability.

After structural and process optimization, the final comparative results of flotation tests between the HTF and standard KYF flotation machines are shown in Figs. 25 and 26.

Cumulative recovery rate of different flotation devices.

Concentrate grade under different flotation devices.

The flotation rate constant of the fine particle flotation machine is increased by 26%, and after 10 min of separation, the cumulative recovery rate is improved by 22.1%. In terms of concentrate grade, the rapid flotation of the fine particle flotation machine leads to a decrease in concentrate grade and an increase in concentrate production rate, primarily due to the significant entrainment in the foam layer caused by the increase in air flow rate. If controlling the concentrate grade is desired, spraying water above the foam layer can be implemented to achieve smaller bubbles.

Particle size analysis is conducted on the concentrate from the first minute for both types of machines via laser particle size analysis, with the results shown in Fig. 27.

Concentrate particle size analysis. (a) Difference distribution, (b) Cumulative distribution.

Research has shown that the particle size distribution of fine-grained flotation machines is more concentrated, while traditional flotation machines are relatively dispersed, with a median particle size of around 12 µ m for both. However, the HTF flotation machine has a 46% concentration of -10 µ m concentrate, while the KYF flotation machine has a 42% concentration. At the same time, the recovery rate of the fine-grained flotation machine within one minute is 70.08%, while the traditional flotation machine is only 46.5%, a difference of 23.58% between the two. This indicates that the fine-grained flotation machine can enhance the recovery of fine-grained minerals through its strong turbulence, thereby improving flotation efficiency and concentrate recovery rate.

The results of the concentrate XRD analysis are shown in Fig. 28. According to the XRD results, the concentrate products mainly consist of chalcopyrite and pyrite, with the primary gangue minerals being quartz and Muscovite.

KYF (Left) and HTF (Right) concentrate XRD analysis.

To further elucidate the mineral composition of the concentrate products at different particle sizes, the BPMA (Benchmarking Process Mineralogy Automation) system was employed for measurement and analysis to obtain the mineral composition and content. The results are presented in Table Table 7. It can be observed that the primary component of the concentrate is chalcopyrite, with a content of 13.75%. Additionally, there are pyrite and magnetite with respective contents of 8.75% and 3.27%, while the main gangue minerals are quartz and mica. Due to the high content of finely disseminated ore, the selectivity in a single roughing process is relatively poor; however, this ensures a higher recovery rate.

The results of the single mineral particle size analysis of the concentrate are shown in Fig. 29. It can be seen that the fine particle floatation machine, compared to the traditional floatation machine, exhibits stronger selectivity for chalcopyrite, pyrite, and magnetite in the − 38 μm size fraction, making it more suitable for use in conditions where the overall particle size of the supplied ore is relatively fine.

Single mineral particle size analysis.

Addressing the issues of low efficiency and poor selective indices in the flotation of fine particles, studies have been conducted on the dynamic characteristics of high-turbulence fine particle flotation machines, as well as their advantages over traditional flotation machines in actual mineral flotation. Based on CFD simulations, a tank structure detaching the stirring area from the separation area with an inner tank can provide an environment with increased turbulent kinetic energy for the inner tank while offering a highly stable, weakly turbulent separation environment in the outer tank. The patterns of their impact on the internal flow field and the actual flotation environment are determined by studying key parameters such as stirring intensity, feed rate, air supply, and jet height.

The flotation dynamic analysis indicates that the advantage of the high-turbulence fine particle flotation machine in strong-turbulence mineralization is reflected in the flotation rate. Within the first minute, the fine particle flotation machine achieves a higher flotation recovery rate than that of the traditional flotation machine. The product size analysis shows that while ensuring the particle size composition of the flotation product is essentially the same as that of the traditional flotation machine, the fine particle flotation machine obtains a higher recovery rate, reducing the impact of fine minerals on the flotation process and providing more leeway for product index regulation. The analysis of concentrate grade shows that HTF can effectively improve the concentrate grade by increasing the rotation speed, adjusting the aeration rate, and adjusting the jet height. However, in order to study the performance of HTF itself, only one coarse selection operation was carried out, which still leaves a gap between the final grade of concentrate and qualified industrial products. At the same time, due to the flotation difficulties of fine-grained minerals, while pursuing flotation efficiency, a certain enrichment ratio is inevitably lost. This can be improved by optimizing the subsequent flotation process.

In summary, HTF has achieved high turbulence dissipation characteristics in the mineralized area through the structural design of small impeller high speed, multi-layer impeller stator, and enclosed mineralized area. It has shown a significant improvement in the flotation speed of fine-grained minerals in the actual mineral flotation process, and its application in the first stage flotation operation is expected to significantly reduce the use of traditional roughing equipment. However, it should be noted that the strong stirring impeller also causes higher energy consumption, and it was found in the experiment that additional necessary upflow needs to be provided in the inner tank to achieve effective gas dispersion. It is often difficult to achieve the required flow rate solely by supplying ore. Subsequent research needs to focus on these aspects.

All data generated or analysed during this study are included in this published article.

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This work was financially supported by the research on green and efficient mineral processing technology and equipment for complex gold resources (No. 2022YFE0126700). The research content of the project is part of the National Key Research and Development Program during the 13th Five-Year Plan, and it is an intergovernmental international cooperation project.

Key Laboratory of High-Efficient Mining and Safety of Metal Mines ministry of education (USTB), University of Science and technology Beijing, Beijing, 100083, China

QianDe Xu & Wentao Hu

Research Center for Efficient Utilization of Fine Minerals, University of Science and technology Beijing, Beijing, 100083, China

QianDe Xu, Wentao Hu & Ming Zhang

State Key Laboratory of Solid Waste Reuse for Building Materials, Beijing, 100041, China

Wentao Hu

BGRIMM Technology Group, Beijing, 100160, China

Ming Zhang

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In this study, Qiande Xu conducted the main simulation and experimental work, organized and analyzed the results, and wrote the main content of this paper. Ming Zhang mainly carried out the advancement of research projects, and formulated the research plan and content. Wentao Hu mainly constructed the train of thought of the paper, adjusted the content of the paper, and modified the language style.

Correspondence to Wentao Hu.

The authors declare no competing interests.

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Xu, Q., Hu, W. & Zhang, M. High-turbulence fine particle flotation cell optimization and verification. Sci Rep 14, 23124 (2024). https://doi.org/10.1038/s41598-024-73367-y

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Received: 29 April 2024

Accepted: 17 September 2024

Published: 04 October 2024

DOI: https://doi.org/10.1038/s41598-024-73367-y

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