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Influence of operating parameters on the flotation of the Khibiny Apatite-Nepheline Deposits | Journal of Materials Research and Technology
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DOI: 10.1016/j.jmrt.2019.08.027
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Available online 11 September 2019
Influence of operating parameters on the flotation of the Khibiny Apatite-Nepheline Deposits
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Abdullah Elbendary, Tatiana Aleksandrova, Nadezhda Nikolaeva
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nadegdaspb@mail.ru

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Saint-Petersburg Mining University, Russian Federation
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Received 05 July 2019. Accepted 17 August 2019
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Tables (9)
Table 1. Collector mixture.
Table 2. Mineral composition of apatite-nepheline ore.
Table 3. Chemical analysis of the flotation feed.
Table 4. Operational parameters affecting the apatite flotation and their levels.
Table 5. Box–behnken design and the results of experiments.
Table 6. ANOVA for response surface quadratic model for apatite ore flotation.
Table 7. ANOVA for Response Surface Quadratic Model Analysis of variance for apatite ore flotation ((% grade of P2O5).
Table 8. ANOVA for Response Surface Quadratic Model Analysis of variance for apatite ore flotation (% recovery of P2O5).
Table 9. Effect of grinding time in the % grade and recovery of P2O5.
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Abstract

Phosphate as fertilizer is so essential for agriculture plants growth. Most of the phosphate resources cannot be directly treated due to the low grade of P2O5 and high content of impurities. Therefore, upgrading of this type of ore is so essential to achieving a grade of concentrate suitable for the production of fertilizer and phosphoric acid. Flotation is one of the most efficient techniques applied to phosphate upgrading. This paper aimed to investigate the effect of operating parameters, including collector dosage, depressant dosage, particle size, and pulp pH, on the rougher stage flotation of apatite ore. The results indicated that at the optimum conditions of flotation, a concentrate of 30% P2O5 with a recovery of a proximately 75% was obtained from a feed of particle size less than 250 microns and 10.8% P2O5.

Keywords:
Phosphate flotation
Flotation reagents
Apatite-Nepheline-Deposits
Experimental design
Full Text
1Introduction

Phosphate rock is the primary source of phosphorous, which is essential to all life forms. Approximately 95% of the phosphate produced in the world is used in fertilizer manufacturing to supply plant nutrients [1,2]. The marketable phosphate is generally at or above 30% P2O5[1,3,4]. According to their origin, phosphate deposits may be divided into three groups: (1) deposits from marine sediments; (2) igneous deposits; (3) biogenetic deposits [5]. Igneous phosphates account for about 15–20% of the world’s phosphate production and vary considerably from the more abundant sedimentary type. Igneous deposits generally contain well-formed crystals of apatite as the predominate phosphate mineral. The Kola Peninsula, in Russia, is the biggest deposits of igneous phosphate mined today. The Khibiny complex is one of the Peninsula's largest igneous complexes [5,6,40]. There are many beneficiation methods that can be used for the upgrading of phosphate ore, depending on the type of ore, the associated gangue minerals, as well as considerations such as the degree of liberation of apatite minerals, the cost of the beneficiation method [1,3,4,41]. The techniques used include magnetic separation [7–9], gravity separation [3,10,38,39], electrostatic separation [49,50], calcinations [1,3,11,12], acid leaching [13–18,42], and flotation process which considered one of the most effective and commonly used technique for apatite enrichment [1,2,5,19,20,43].

The statistical techniques were commonly used to study the flotation of different minerals [21–23,46]. The statistical design of the experiments has several benefits over the classical method of considering one variable at a time. The experimental design (DOE) provides information about the interaction of many factors and how the overall system works, which features cannot be obtained by studying one factor at a time while keeping other factors constant. It is essential that the methodology of the experimental design is also a very cost-effective way of saving the materials used for analysis and private costs [24]. Different DOE methods have recently been used for mineral processing modeling [25–31]. Response surface methodology has been performed to model parameters affecting Turkish coal processing [27], flotation of celestite concentrate [30], sulfur grindability in a batch grinding [31], apatite flotation process and kinetics [20,32], and the separation performance of phosphate ore from iron gangue [33,34].

This research was carried out on low-grade apatite ore Khibiny deposits (Kola Peninsula, Russia). As well known the most common flow-sheet for beneficiation of this type of ore is consist of ore preparation, a rougher stage, followed by some cleaning and scavenger stages for obtaining a concentrate with high grade of P2O5 (39.5%) [47,48]. The influences of flotation operation parameters were studied on the apatite grade and recovery using a statistical technique during rougher stage for the optimization of the process and improve its quality to meet the industry requirement.

2Materials and methods2.1Materials

For this study, apatite samples were collected from Khibiny deposits, Kola Peninsula, Russia. A mixture of different surfactants was used as collector and dispersing agent (Table 1), sodium silicate was used as a depressant. CaCl2 and Na2CO3 were used as pH modifiers.

Table 1.

Collector mixture.

Collector mixture  Content % 
Distilled tall oil  10 
Coniferous crude tall oil (CTO20 
Deciduous tall oil  30 
Alkyl benzene sulphonic acid 
Phospholan PE169  35 
2.2Methods2.2.1Sample preparation

The samples were subjected to primary and secondary crushing to produce a product of size less than 2mm. The crushed sample then subjected to grinding in a conventional ball mill. The experimental mill employed was laboratory sized, 125×170mm, with a total mass of 3.3kg of steel balls to reach the liberation size. The grinding product less than 160 microns (88% of the initial feed) were used as a feed for the rougher flotation. Further studies were performed on ground products of different fraction size (less than 250μm and 160μm) which prepared by milling at different grinding times to investigate the effect of over grinding and the effect of particle size on the flotation performance.

2.2.2Chemical and mineralogical analysis

Complete chemical analysis of the sample was conducted by Energy Dispersive X-ray Fluorescence Spectrometer (EDX-7000). Identification of the mineral composition of the considered sample was conducted by X-ray diffraction (XRD). The Mineralogical study was performed by using the Liberation Analyzer (MLA). MLA is a scanning electron microscope (SEM) equipped with energy dispersive X-ray (EDX) spectrometers, and computer software that automates microscope operation and data acquisition for automated mineralogy. MLA measurements are based on image analysis of the backscattered electron (BSE) for determining grain boundaries. Different quantitative information sets are collected on polished surfaces of rocks, sediments or other particulate specimens, including modal mineralogy, grain size and shape, mineral associations and digital textural maps

2.2.3Flotation experiment and modeling procedure

The flotation tests were performed in a conventional flotation machine 237 FL-A with 0.35-liter capacity cell and the impeller rotational speed 40rev/sec. Batch flotation tests were carried out at room temperature. 100g of ore sample was conditioned with tap water in a flotation cell and stirred for 3min before adding any reagent; CaCl2 and Na2CO3 were used as pH modifiers. Conditioning of the pulp with reagents was carried out for 1min and 3min for the depressant and collector respectively. The whole flotation continued for 3min. The float and sink products were filtered, washed, dried, weighed and chemically analyzed.

The experimental design was performed using a software package, Design-Expert 6.0.5, Stat-Ease, Inc., Minneapolis, USA, for regression analysis of experimental data and to plot the response surface. The Box–Behnken factorial design was chosen to find out the relationship between the response function (percentage weight of the concentrate, % grade of P2O5 and % recovery) and three important variables (collector dosage (60–140) g/ton, depressant dosage (100–500) g/ton, and the degree of pH of the pulp from 9.5 to 11) and their influence in the primary (rougher) apatite ore flotation. These variables were changed during the tests with respect to the Box–Behnken experimental design, whereas the other operational parameters of flotation were kept constant (amount of feed, impeller speed, air quantity).

3Results and discussions3.1Mineralogical and chemical analyses

Table 2 and Figs. 1 and 2 represented the results of mineralogical studies using MLA, it has been shown that the primary minerals in the sample are apatite and nepheline, the content of which 30.67 and of 30.88% respectively; in the secondary presented pyroxenes, mica, feldspar, as well as natrolite and kaolinite. The most valuable minerals of the sample are Apatite — the main phosphorus mineral and nepheline — the main aluminum mineral Table 2. Apatite forms prismatic crystals shape, clusters crystals, rarely massive clusters of fractured anhedral (xenomorphic) grains, and usually associated with other minerals such as — pyroxenes, mica, sphene, nepheline. Apatite is resistant to weathering; it does not form secondary minerals. The grain size of apatite is 0.05–1.0mm and the prevail size between 0.1–0.4mm Figs. 1 and 2. The results of mineralogical studies were confirmed by performed the X-ray diffraction of the sample. It is clear that the sample is dominated by fluorapatite and the main gangue mineral is nepheline Fig. 3.

Table 2.

Mineral composition of apatite-nepheline ore.

Mineral  Content, %  Mineral  Content, % 
Apatite  30.67  Sphene  2.48 
Nepheline  30.88  Magnetite  1.02 
Pyroxenes (aegirine, augite, aegirine-augite)  9.22  Iron hydroxides  0.44 
Mica (biotite, muscovite)  7.47  Kalsilite  0.68 
Feldspar  5.98  Cancrinite  0.51 
Natrolite  3.71  Pectolite  0.34 
Kaolinite  2.61  Other  2.84 
Arfvedsonite  1.15  Amount  100.00 
Fig. 1.

a) Apatite crystals are associated with muscovite, sphene and aegirine-augite. b): 1 – apatite; 2 – muscovite; 3 – sphene; 4 – aegirine-augite; 5 – kaolinite; 6 – carbonates of rare earth elements; 7 – zeolites.

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Fig. 2.

a) Clusters of Apatite associated with sphene and ilmenite in the matrix of altered nepheline. b): 1 – ilmenite; 2, 5 – sphenes; 3, 8 – nepheline; 4, 6 – apatite; 7 – zeolite; 9 – ramsey.

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Fig. 3.

XRD of phosphate sample.

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Table 3 represented the results of a complete chemical analysis of the apatite sample using X-ray fluorescence analysis technique (XRF). The flotation sample contains a low content of P2O5 (˜10.8%) and high amounts of SiO2 and Al2O3.

Table 3.

Chemical analysis of the flotation feed.

Oxide  SiO2  Al2O3  CaO  P2O5  K2O  Fe2O3  TiO2  MgO  MnO 
37.54  19.79  18.26  10.80  5.70  4.30  2.50  0.92  0.19 
3.2Statistical analysis

The experimental data were analyzed statistically. The effect of the factors and also the interactions between factors were quantified and interpreted.

The studied parameters are representing in Table 4. According to this design, the optimal conditions were estimated using second order polynomial function by which a correlation between studies factors and response was generated. The general form of this equation is:

Y=βo+β1X1+β2X2+β3X3+β4X4+β12X1X2+β13X1X3+β14X1X4+β23X2X3+β24X2X4+β34X3X4+β11 X12+β22 X22+β33 X32+β44 X42
Where: Y is the predicted response, X1, X2, X3 and X4 are studied variables; βi are equation constant and coefficients. The extent of fitting the experimental results to the polynomial model equation was expressed by the determination coefficient, R2. Table 5 shows the results of Box–Behnken design in term of wt% of concentrate, P2O5 grade %, and recovery %. R2 for the Wt% of the concentrate, % P2O5 and % recovery are 0.979, 0.984 and 0.981, respectively, these values indicate the well fitting of the experimental results to the polynomial model equation and hence accuracy of this model Table 6. Analysis of variance (ANOVA) was used to estimate the statistical parameters. The variance analysis results of the mathematical equations for the percentage grade of P2O5 and for the recovery are presented in Tables 7 and 8. It should be mentioned, that at the confidence level of 95% the variables that their Prob>F is less than 0.05 are significant. The F value of each variable shows the importance degree and the effectiveness of the variable [44].

Table 4.

Operational parameters affecting the apatite flotation and their levels.

Symbol  Parameter  Unit  (–)  (0)  (+) 
Collector dosage  g/ton  60  100  140 
Depressant dosage  g/ton  100  300  500 
pH  –  9.5  10.25  11 
Table 5.

Box–behnken design and the results of experiments.

Run  Wt % of the concentrate  % Grade of P2O5  % Recovery 
140  200  10.25  31.64  25.20  73.82 
100  300  11.00  29.00  26.60  71.40 
100  500  9.50  8.90  18.49  15.23 
100  300  10.25  29.50  26.80  73.20 
100  300  10.25  29.50  26.80  73.20 
60  300  11.00  26.11  28.75  69.50 
100  500  11.00  29.02  26.57  71.39 
140  300  11.00  28.00  26.00  67.40 
60  500  10.25  12.66  22.13  25.94 
10  140  500  10.25  25.70  27.70  65.91 
11  140  300  9.50  23.35  23.95  51.78 
12  100  300  10.25  29.00  27.30  73.30 
13  60  100  10.25  27.65  25.78  66.00 
14  60  300  9.50  8.12  17.90  13.45 
15  140  100  10.25  32.00  22.05  65.33 
16  100  100  11.00  31.11  23.32  67.17 
17  100  100  9.50  28.15  19.95  51.99 
18  100  500  10.25  22.17  25.39  52.12 
19  100  500  11.00  29.02  26.57  71.39 
20  140  500  11.00  29.57  26.00  71.18 
21  100  300  10.25  29.50  26.80  73.20 
22  120  410  10.80  28.97  26.92  72.21 
23  100  100  10.25  31.00  24.18  69.40 
24  100  200  10.25  28.00  25.89  67.12 
25  100  300  10.25  29.60  26.70  73.17 
26  140  300  10.25  29.00  26.30  70.60 
Table 6.

ANOVA for response surface quadratic model for apatite ore flotation.

The statistical parameters  Concentrate wt%  % P2O5  % Recovery 
The standard deviation  1.16  0.43  2.97 
R-squared  0.9797  0.9846  0.9817 
Adequate precision  33.645  39.086  33.65 
Table 7.

ANOVA for Response Surface Quadratic Model Analysis of variance for apatite ore flotation ((% grade of P2O5).

Source  Σ (sum of squares)  Φ (DF)  Ψ (mean square)  χ (F value)  τ (Prob>F) 
Model  192.53  21.39  113.76  <0.0001 
2.29  2.29  12.19  0.0030 
2.22  2.22  11.79  0.0034 
81.57  81.57  433.78  <0.0001 
A2  0.47  0.47  2.51  0.1326 
B2  25.26  25.26  134.35  <0.0001 
C2  37.53  37.53  199.56  <0.0001 
AB  22.68  22.68  120.61  <0.0001 
AC  25.53  25.53  135.78  <0.0001 
BC  5.49  5.49  29.19  <0.0001 
Residual  3.01  16  0.19     
Lack of fit  2.78  11  0.25  5.54  0.0357 
Pure error  0.23  0.046     
Cor total  195.54  25       
Table 8.

ANOVA for Response Surface Quadratic Model Analysis of variance for apatite ore flotation (% recovery of P2O5).

Source  Σ (sum of square)  Φ (DF)  Ψ (mean square)  χ (F value)  τ (prob>
Model  7536.7  837.41  95.13  <0.0001 
883.34  883.34  100.35  <0.0001 
864.79  864.79  98.24  <0.0001 
2927.03  2927.03  332.51  <0.0001 
A2  322.92  322.92  36.68  <0.0001 
B2  336.03  336.03  38.17  <0.0001 
C2  915.15  915.15  103.96  <0.0001 
AB  446.09  446.09  50.68  <0.0001 
AC  487.89  487.89  55.42  <0.0001 
BC  553.61  553.61  62.89  <0.0001 
Residual  140.84  16  8.80     
Lack of fit  140.83  11  12.80  6453.20  <0.0001 
Pure error  9.920E-003  1.984E-003     
Cor total  7677.54  25       
3.3Effects of the operating parameters on the percentage grade of P2O5

Figs. 4–7 represented the effects of operating parameters on the % grade of P2O5. It has been shown that the most effective parameter influence on the grade of P2O5 is the pH degree. The percentage grade of P2O5 improved significantly as the pH degree increased. The pH solution determines the extent of ionization and hydrolysis of the collector; this helps or hinders the adsorption of the collector at the different ionized solid/liquid interfaces, contributing to higher or lesser flotation selectivity [47]. It was shown that the low grade of the concentrate was observed at pH 9.5 at all studied ranges of collector and depressant dosage Figs. 5–7. It can be discovered in Figs. 5 & 6 and Table 5 that a medium dosage of a depressant (300g/t) associated with a low collector level (60g/t) at pH 11, provided a better quality product, where P2O5 content was 28.75%. This is due to the more efficient action of the depressant and also due to the small amount of available collector adsorbs preferentially on the surface of the apatite. Figs. 4, 5 showed that, at the lowest value of depressant and the highest collector dosage, the minimum content of P2O5 (22%) was obtained, due to the fact that the amount of depressant is inadequate to promote a more selective collection of the apatite [45]. In addition, a large amount of collector renders it for adsorption at the surfaces of other mineral particles hence increasing the flotation of impurities. This observation is in agreement with the previous studies [33,35].

Fig. 4.

Effect of collector dosage and depresant dosage in the grade of P2O5.

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Fig. 5.

Effect of collector dosage and pulp pH in the grade of P2O5.

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Fig. 6.

Effect of depressant dosage and pulp pH in the grade of P2O5.

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Fig. 7.

Cubic graph represents the effect of operating parameteres in the % grade of P2O5.

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From the experimental parameters in Table 4 and experimental results in Table 5, the second order response function representing the grade of P2O5 in the concentrate can be expressed as a function of the three process parameters. The quadratic model found to adequately predict the response variables were given by the following Eq. (1), where A is the collector dosage g/ton, B is the depressant dosage g/ton, and C is the pulp pH.

% Grade of P2O5=−556.2446+0.77228A-0.064487 B+104.069C-1.7723e−004A2- -5.29095e−005 B2-4.60634C2 +2.71091e−004 AB −0.078651 AC+6.95953e−003BC

The correlation between the observed and predicted results using the above-mentioned models was shown in Fig. 8. Value of R2 was 0.984 for this model. The high value of R2 indicates that the quadratic equation is capable of representing the system under the given experimental domain. It can be seen that there was a good agreement between predicted and actual values.

Fig. 8.

Correlation between experimental and predicted values of the % grade of P2O5.

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3.4Effects of the operating parameters on the percentage recovery of P2O5

The effects of operating parameters on the % recovery of P2O5 were represented in Figs. 9–14. It has been shown that the percentage recovery drastically increased with increasing the collector dosage and the pH degree especially in the range from 60 to 100g/ton. For low values of the collector, when pH is increased, recoveries are increased too Fig. 10. This observation is in agreement with the previous studies, Pugh and Per Stenius (1984), investigated the effect of pH and collector concentration. They reported that the minimum surface tension and the formation of pre-micelle associated species occurred at higher pH in lower concentrations of sodium oleate solution, which attributed to the better flotation recovery of apatite [36]. The minimum percentage of recovery and grade of P2O obtained at a lower value of collector and a higher depressant value, that is may be due to the amount of collector is not enough to coat all the mineral surfaces and render them hydrophobic and most of the valuable minerals unfloated and lost in tailing. As well known that, the main role of sodium silicate in apatite flotation is to depress the silica particles by the precipitation of sodium silicate polymeric species on silica particles, also, sodium silicate interacts with calcium ions and precipitates them as calcium silicate in the solution, and on silica and apatite particle which explain why extra sodium silicate dosage may significantly reduce apatite recovery [2].

Fig. 9.

Effect of collector dosage and depresant dosage in the recovery of P2O5.

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Fig. 10.

Effect of collector dosage and pulp pH in the recovery of P2O5.

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Fig. 11.

Effect of depressant dosage and pulp pH in the recovery of P2O5.

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Fig. 12.

Cubic graph represented the effect of operating parameteres in the % recovery of P2O5.

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Fig. 13.

Contour plot of the combined effect of collector dosage and depresant dosage on the recovery of P2O5 at pH 11.

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Fig. 14.

Effect of collector dosage and depresant dosage on the Wt % & grade and recovery of the concentrate at center value of pH 10.25.

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At a higher collector dosage 140g/ton, the maximum recovery obtained at pH 10.25, increasing or decreasing pH above or down this degree will negatively affect recovery % Fig. 10. Fig. 11 showed the effect of depressant dosage with pH. It is clear that, at a lower degree of pH 9.5, the percentage recovery of P2O5 decreased with increasing depressant dosage. In contrast, at a higher degree of pH 11, the percentage recovery recorded maximum values even if the collector or depressant have low or high values Figs. 11–13. It can be concluded from the results that higher pulp pH had positive effects on apatite flotation. According to the work by Feng and Aldrich (2004), increased the flotation recovery with increased the pH of pulp probably through softening the process water and speeding up the electrolysis of the fatty acid [32].

The maximum recovery 73.20% with a grade of 26.80% was obtained at centered values of collector, depressant and pH degree when both recovery and grade are considered at the same time Fig. 14.

The quadratic model found to adequately predict the response variables for the recovery of P2O5 was given by the following Eq. (2), where A is the collector dosage g/ton, B is the depressant dosage g/ton, and C is the pulp pH.

% Recovery of P2O5=−2731.648+4.3255A-0.76447B+502.865C-4.6351e−003A2-1.9296e−004B2-22.747C2 +1.2022e−003AB -0.3438AC+0.06988BC

The correlation between the observed and predicted results was shown in Fig. 15. Value of R2 was 0.981.

Fig. 15.

Correlation between experimental and predicted values of the % recovery of P2O5.

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3.5Effect of grinding time on % recovery of P2O5

Further experiments were also conducted on a feed with wider particle size distributions (−250μm), which ground at different times, the results of different tests represented in Table 9 and Fig. 16. The results showed that during the flotation of apatite ore, increasing in the fineness of grind as a result of grinding at a long grind time was accompanied by decreasing in both recovery and grade of P2O5, which is the reason for its attribution to the presence of slimes in excessive amount.

Table 9.

Effect of grinding time in the % grade and recovery of P2O5.

Min, grinding time  Fractions  % wt of concentrate  % grade P2O5  % recoveryP2O5  % Overall recovery 
10−250 micron  89.0  34.0  30.00  83.50  74.30 
−160 micron  66.5  36.6  30.05  88.25  58.68 
15−250 micron  97.0  23.6  26.38  71.60  69.45 
−160 micron  84.0  32.0  29.50  78.60  66.02 
18−250 micron  100.0  25.0  26.20  60.65  60.65 
−160 micron  88.0  29.0  26.83  72.00  63.36 
Fig. 16.

Effect of grinding time in the overall recovery of P2O5.

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The presences of slimes are, in general, harmful to the flotation of apatite ores, affecting the selectivity and the quality of the concentrates, besides causing an increase in reagents consumption by which a value mineral is covered by slimes and prevented from direct contact with collectors and/or air bubbles [37]. It can be concluded that the maximum overall recovery (74.3%) with a grade of 30% P2O5 was obtained from a feed of particle size less than 250 microns with 12.2% P2O5 which prepared by grinding for 10min. This is due to the fact that process of selective grinding is observed in process of destruction.

4Conclusions

Box–Behnken design was used to investigate the influence of the operational factors affecting the floatability of apatite ore in the rougher stage including collector dosage, depressant dosage, and pulp pH. The study extended to investigate the effect of grinding time and particle size in the efficiency of the flotation.

The conclusions obtained from the study are as follows:

  • 1

    The percentage grade and recovery of P2O5 drastically increased with increased pH degree from 9.5 to 11.

  • 2

    A medium dosage of a depressant (300g/t) associated with a low collector level (60g/t) at pH 11, providing a better quality product with maximum P2O5 content.

  • 3

    The minimum recovery and grade of P2O5 were obtained at a lower value of collector and a higher depressant value, this indicated that the percentage recovery is sensitively affected by the collector and depressant dosage, therefore the amount of collector must be enough to coat at all the mineral surfaces and on the other hand, the amount of the depressant must be optimized to avoid the depress of the valuable mineral.

  • 4

    The maximum recovery and grade of P2O5 were obtained at centered values of a collector (100g/ton), depressant (300g/ton) and pH degree (10.25), when both recovery and grade were considered at the same time.

  • 5

    Increasing the percentage of fines and slimes in the feed as results of grinding at a long time (over 10min), has negatively affected the flotation performance and causing an increase in reagent consumption.

Based on the mineralogical, chemical, material composition, as well as techno-logical research on the possibility of processing phosphate ores, it was concluded that the optimal scheme for the extraction of apatite is a flotation circuit.

The maximum overall recovery (74.3%) with a grade of 30% P2O5 was obtained from a feed of particle size less than 250 microns at the rougher flotation stage, which prepared by grinding for 10min, the apatite ore of such specifications could be used in fertilizers and phosphoric acid. It is suggested to carry out further stages of flotation to achieve higher grade of P2O5 concentrate (39.5%).

Conflicts of interest

The authors declare no conflicts of interest.

Acknowledgement

The work was funded by Russian Science Foundation (Project No. 19-17-00096).

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