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Vol. 8. Issue 5.
Pages 4312-4317 (September - October 2019)
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Vol. 8. Issue 5.
Pages 4312-4317 (September - October 2019)
DOI: 10.1016/j.jmrt.2019.07.041
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Recovery of pyrite from copper tailings by flotation
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Mario Santander
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mario.santander@uda.cl

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, Luis Valderrama
Department of Engineering in Metallurgy, University of Atacama, Copiapó, Chile
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Figures (2)
Tables (9)
Table 1. Elemental chemical composition of the fresh tailing samples.
Table 2. Levels of each factor used in the factorial experimental design.
Table 3. Main operating parameters used in kinetics of scavenger, cleaner, and recleaner flotation.
Table 4. Statistical evaluation of four variables effects and their interactions on recovery of pyrite.
Table 5. Results of the factorial experimental design.
Table 6. Kinetic parameters, confidence interval (C.I.), standard error of the recovery (S.E.), and correlation coefficient (R2).
Table 7. Split factor calculated with the open cycle tests.
Table 8. Global recovery and pyrite grade in the final concentrate (recleaner concentrate) for the two simulated circuits.
Table 9. Global recovery and pyrite grade in the final concentrate at industrial scale.
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Abstract

Tailings that are generated in the copper concentrate production contain great amount of sulfide mineral, in particular pyrite. Pyrite in contact with water and oxygen might oxidize spontaneously and originates a serious environmental problem. In this article the recovery of pyrite before storing it in the tailing deposit to produce pyrite concentrates of economic interest, and to avoid the generation of acid mine drainage-AMD when transforming an acid tailing into a neutral tailing is proposed. The effect of conditioning time, pH, collector and frother dosage, and a number of flotation stages on grade and recovery of pyrite were studied at laboratory scale, using a fresh tailing sample collected in a concentrator plant from the Atacama Region, Chile. Furthermore, a continuous flotation circuit at laboratory scale was designed, which was evaluated on an industrial scale. The flotation circuit was designed using mathematical simulation by means of the “Split Factor” technique. The results obtained both at laboratory and industrial scale showed that it is possible to produce concentrates with a pyrite grade over 90% and recoveries over 70% in a flotation circuit that includes rougher–scavenger–cleaner and recleaner stages. To achieve this grade and recovery of pyrite, it is only necessary to condition the fresh tailings with 30g/t of collector, 20g/t of frother, 10min of conditioning time, adjust the pH to 8 and set the flotation time for the rougher–scavenger–cleaner and recleaner stages in 10, 10, 10, and 5min, respectively.

Keywords:
Copper tailing
Pyrite recovery
Flotation
Split factor
Full Text
1Introduction

The concentration of sulfide copper minerals by means of flotation generates large volumes of tailings. It is estimated that one hundred twenty-five tons of tailings are generated per one ton of produced copper, and its generation is on a continuous rise because of the decrease of the copper grades [1]. On the one hand, the tailing is considered an environmental problem as a result of its great volume and mineralogical species contained; on the other, a source of low-cost mineral resources because it is not required to perform the comminution stage to process them.

The main environmental problems generated because of the storage of tailings in “Deposits or Tailings Dams” include the risk to the population before a seismic event of great magnitude, possible percolation of pollutants to the groundwater, visual impact, soil and habitat destruction, and wildlife alteration. The collapse of a tailings deposit, related to natural events, has resulted in accidents with catastrophic consequences in the social, environmental, and human sphere [2]. Copper tailings contain reactive sulfide minerals, such as pyrite, chalcopyrite, chalcocite, and other residual metal minerals [3]. Sulfide minerals, mainly pyrite, in the presence of air, water, and bacteria can suffer a rapid oxidation to produce acidic water [4]. Acidic waters dissolve other metals, producing solutions that can carry toxic chemicals to the environment, for example mercury and arsenic [5].

The following measures to prevent the oxidation of pyrite and consequently the generation of acidic waters have been proposed: restricting the entry of water and/or the penetration of oxygen through the air using materials like compacted clay, concrete, asphalt, and HDPE.

Considering that pyrite content in the tailings varies between 4% and 8%, an alternative to prevent the generation of acidic waters is to recover pyrite as a by-product, this would solve part of a future environmental problem and it would improve the profitability of the flotation plants that concentrate copper ores. Pyrite is used to produce elemental sulfur or sulfuric acid, as a disinfectant and wood protector in the ferrous sulfate production, to color in the glass industry, in brakes and abrasive coatings, and as fuel in the pyrometallurgy of copper. There are also studies that show that the pyrite can be used as a catalyst for the decontamination of water contaminated with nitrates [6].

Studies aimed to recover oxide iron ores from tailings have been conducted by several researchers using different techniques such as: flocculation, flotation, and magnetic concentration [7–10]. The recovery of iron from tailings has also been studied using magnetic separation after a pre-thermal treatment to transform the iron ores into magnetite [11].

The objective of this study was to design a flotation circuit to produce pyrite concentrate of commercial interest from fresh tailings generated in a concentrator plant from the Atacama region, Chile. To achieve the objective: (1) the effect of pH, collector and frother dosage, and conditioning time on the recovery in the rougher flotation stage at laboratory scale were evaluated, (2) the optimal flotation time of the rougher–scavenger–cleaner and recleaner stages was determined, (3) a continuous circuit at laboratory scale using mathematical simulation, and applying the “Split Factor” technique was designed to produce pyrite concentrates of economic interest and (4) a design of a circuit at laboratory scale was evaluated on an industrial scale.

2Experimental2.1Materials and reagents

A fresh tailing sample obtained from Manuel Antonio Matta Plant of the National Mining Company, Chile was used in the flotation studies. X-ray Diffraction spectrums (not presented herein) revealed that the fresh tailing sample contains pyrite, chalcopyrite, magnetite, quartz, calcite, clinochlore, anorthite, and orthoclase.

In the flotation tests the pulp was conditioned with Aero 404 as a collector (mixture of sodium dibutyl dithiophosphate and sodium mercaptobenzothiazole), and MIBC (carbinol isobutyl methyl), and DF-250 (propilene glycol methyl ether) were used as frothers. The pH was regulated with sulfuric acid or lime.

Table 1 presents an elemental chemical composition of the fresh tailing sample. The magnetic material contained in the tailing sample was determined by Davis tube tests (DTT), the sulfur content was determined using the combustion technique in LECO equipment (S-230SH) while the content of total iron, magnetic iron and copper were determined in a GBC 908 atomic absorption spectrophotometer (AAS).

Table 1.

Elemental chemical composition of the fresh tailing samples.

Component  Total iron  Magnetic iron  Total copper  Total sulfur 
Weight, %  16.12  12.90  0.26  2.71 

The pyrite grade in the fresh tailing sample and in the flotation product was determined indirectly from the content sulfur, copper and iron. Calculations carried out considering the elemental chemical composition presented in Table 1 and the mineralogical species that contained sulfur, identified by the XRD analysis, allowed to determine that the fresh tailings sample contained 4.56% FeS2 and 0.75% CuFeS2. On the other hand, a particles size analysis carried out through wet sieving showed that 53% of particles of the fresh tailing sample had a size under 74μm.

2.2Rougher flotation

In the first part of this study, a series of conventional rougher flotation tests were conducted using a factorial experimental design in two levels, with the purpose of evaluating the effect of collector and frother dosages, pH, and conditioning time on recovery. The experimental results were analyzed using Statgraphics plus 5.0 Software. Table 2 presents the level of each factor used in experimental design.

Table 2.

Levels of each factor used in the factorial experimental design.

Factors  Levels
  Minimum  Central  Maximum 
Aero 404, g/t  10.0  20.0  30.0 
MIBC, g/t  5.0  7.5  10.0 
DF-250, g/t  5.0  7.5  10.0 
Conditioning time, min  10.0  12.5  15.0 
pH  6.0  7.0  8.0 

After this, the flotation kinetics for the rougher, scavenger, cleaner, and recleaner stages was performed to determine the optimal flotation time. Subsequently, open cycle flotation tests were conducted for the mathematical simulation of different configurations of flotation circuits at laboratory scale by means of the “Split Factor” technique. Finally, one of the simulated flotation circuits at laboratory scale was tested on an industrial scale.

The rougher flotation tests were performed in a Denver D-12 flotation machine with a 2.5L cell. In each rougher flotation test, 2.260L of fresh tailing pulp with 37.4±1.3% solid by weight, 4.7±0.3% pyrite grade, and pH 9.6±04 were added in the cell and agitated at an impeller rotation speed of 1400rpm. Then, the pH of the pulp was adjusted by adding 0.1M of sulfuric acid solution. Subsequently, Aero 404, MIBC and DF-250 were added to the pulp and conditioned for the predetermined period of time. After the conditioning process, the pulp was floated for 10min with an air flow of 4.5L/min. Mineralized froths were recovered by scraping the froth layer every other 15s. Water was added to the test periodically to maintain the pulp level.

2.3Flotation kinetics

The kinetics of the rougher flotation was performed under the same experimental conditions as those for the conventional rougher flotation tests, except that 30g/t of Aero 404, 10g/t of DF-250 and 10g/t of MIBC were added. The pH was set at 8. The pulp was floated for 15min and mineralized froths were recovered by scraping the froth layer every other 15s at the following time intervals: 0–1, 1–2, 2–3, 3–5, 5–7, 7–10, and 10–15min.

The experimental procedure to the kinetics of scavenger, cleaner, and recleaner flotation was the same used in the kinetics of the rougher flotation except that no flotation reagents were added and mineralized froths were scrapped from the froth layer every other 15s at the following time intervals: 0–1, 1–5, 5–7 and 7–10min to scavenger; 0–1, 1–3, 3–5 and 5–10min to cleaner and 0–1, 1–2, 2–5 and 5–7 to recleaner. Table 3 summarizes the main operating parameters applied in these kinetics.

Table 3.

Main operating parameters used in kinetics of scavenger, cleaner, and recleaner flotation.

Parameters  Scavenger  Cleaner  Recleaner 
Cell volume, L  2.5  1.5  1.5 
Impeller rotation, rpm  1400  1200  1200 
Air flow, L/min  4.5  3.5  3.5 
pH 
Flotation time, min  10  10 
Content solids by weight, %  35  20  10 

In all flotation tests, the produced concentrates and tailings were filtered, dried at 80°C, weighed to determine the mass recovery and analyzed to determine the chemical composition.

2.4Open cycle flotation tests

Once the optimal flotation times were determined, open cycle tests were conducted to calculate the split factors of the four flotation stages. These tests were performed using optimal time determined with flotation kinetics.

2.5Industrial scale flotation tests

Industrial scale tests were conducted in a rougher–scavenger–cleaner–recleaner flotation circuit composed of six bi-cells of 1.1m3. The tests were conducted with a pulp flow of 0.21m3/min, 30% solid by weight, pH 8.5, 17min of flotation time for the rougher and scavenger stages, and 8.4min for the cleaner and recleaner stages. The feed to the flotation circuit had a pyrite grade between 3.2 and 3.8% (estimated from sulfur contained in the processed fresh tailing) and a 51.1% of the particles size was under 74μm. Tests were performed during 4 days in shifts of 6h per day, one sample was collected in each shift from the feed flow, the recleaner concentrate flow (or final concentrate), and the scavenger tailing flow (or final tailing). The samples were formed by increments collected every 2h.

3Results and discussion3.1Rougher flotation

Results of a statistical evaluation of the Aero 404, MIBC+DF-250, conditioning time and pH effect, and their interactions on recovery of pyrite in rougher flotation at a 95% confidence level are presented in Table 4. The regression coefficient (R2) of the estimation of the factors effects and their interaction was 0.88. The effects of variables are statistically significant when the P values of their coefficient obtained from ANOVA (analysis of variance) are less than the selected significance level of 0.05 (α).

Table 4.

Statistical evaluation of four variables effects and their interactions on recovery of pyrite.

Effect  P-value  Effect on response 
A: Aero 404  0.0003  Positive 
B: MIBC+DF-250  0.5093  Negative 
C: Conditioning time  0.4513  Positive 
D: pH  0.8794  Positive 
A·B  0.7553  Positive 
A·C  0.9741  Negative 
A·D  0.2526  Positive 
B·C  0.9431  Negative 
B·D  0.2649  Positive 
C·D  0.4227  Negative 

As can be seen from Table 4, the only variable that has a significant effect on the recovery of pyrite is the Aero 404 dosage, which can also be corroborated with the results of the factorial experimental design presented in Table 5. The recovery of pyrite is over 80% with 30g/t of Aero 404, except in the test No. 12, while with a dosage of 10g/t the recovery of pyrite is less than 48.5%.

Table 5.

Results of the factorial experimental design.

Test No.  Collector, g/t  Frother, g/t  Conditioning time, min  pH  Recovery, %  Pyrite grade, % 
30  20  10  91.0  51.1 
12  30  20  10  50.6  43.2 
16  30  20  15  88.6  51.9 
10  30  20  15  81.1  47.7 
17  30  10  10  82.4  45.1 
15  30  10  10  80.0  52.4 
30  10  15  82.3  49.8 
30  10  15  80.4  41.9 
20  15  12.5  80.5  41.6 
18  20  15  12.5  81.1  42.1 
10  20  10  12.0  9.3 
10  20  10  12.2  10.0 
10  20  15  13.1  10.7 
11  10  20  15  9.9  11.8 
10  10  10  10.7  7.7 
14  10  10  10  15.8  14.6 
13  10  10  15  10.1  9.6 
10  10  15  48.5  32.2 

The interaction between the collector dosage and the pH (A·D) has a positive effect on the recovery of pyrite, even though it is not statistically significant because the P value is greater than 0.05. In Table 5 it is observed that the recovery of pyrite is increased when the pH was increased from 6 to 8, 30g/t of collector and equal dosages of frother were added, and the same conditioning times were set. However, when 10g/t of collector were added, the recovery of pyrite increases with the pH in some tests and in others it decreases.

López et al. [12], studied the floatability of pyrite as a function of pH, using ethyl xanthate as a collector. They found that in the range of pH from 5 to 9, the recovery of pyrite was less than 40% when using 1×10−6M collector concentrations and it was greater than 80% when using 1×10−4M collector concentrations. According to these researchers the lower floatability of pyrite with low dosages of collector is because of the high surface density of iron oxy-hydroxide. Wang and Forssberg [13], indicate that Fe+3 ions are produced due to the superficial oxidation of pyrite, which are hydrolyzed to form iron oxy-hydroxide that adheres to the sulfide-rich surface of the pyrite, decreasing its hydrophobicity.

3.2Flotation kinetics

The model proposed by Garcia–Zuñiga was adjusted to the results of the flotation kinetics:

where R is the recovery (%) of a valuable metal in an instant t (min); with R representing the maximum estimated recovery (%) and k is the first order kinetic.

Kinetic parameters, confidence interval of the fit at a significance level of 90% (C.I.), standard error of the recovery (S.E.), and correlation coefficient (R2) obtained for each flotation stage shown in Table 6 were determined by using the Microsoft Excel all-over spreadsheet program SOLVER function [14].

Table 6.

Kinetic parameters, confidence interval (C.I.), standard error of the recovery (S.E.), and correlation coefficient (R2).

Stage  R, %  k, min−1  C.I.  S.E.  R2 
Rougher  89.7  1.03  ±3.3  1.69  0.979 
Scavenger  68.6  0.20  ±7.9  3.35  0.978 
Cleaner  99.4  0.28  ±6.4  2.72  0.992 
Recleaner  99.2  0.80  ±2.2  0.91  0.998 

The values of the correlation coefficient show that the experimental recoveries fit quite well the García-Zúñiga model, that is, over a 97.8 of the recovery variation it can be explained by the variation of the flotation time.

Fig. 1 shows accumulated recoveries as a function of time for the kinetics of rougher, cleaner, recleaner, and scavenger flotation; the symbol denotes experimental accumulated recovery and the line indicates accumulated recovery calculated with the Garcia–Zuñiga model.

Fig. 1.

Accumulated recoveries as a time function of the rougher, scavenger, cleaner, and recleaner flotation stages.

(0.08MB).

The magnitude of the kinetic constant (k) for the rougher stage is greater than for the cleaner and recleaner stages; however, the maximum estimated recovery (R) is lower. After 6min of flotation, 90% of the pyrite is recovered; longer times do not increase recovery. This time could be considered as the optimal flotation time for this stage; nevertheless, the instantaneous grade of pyrite in the concentrate is 22.9%, a value that is considered high. After 10min of flotation, the instantaneous and accumulated grade of pyrite in the concentrate is 11.2% and 51.1% respectively; therefore, a flotation time of 10min was set for the rougher stage. The rougher tailings with a pyrite grade of 0.43% will be reprocessed in a scavenger flotation stage.

The maximum estimated recovery for the scavenger flotation stage was 68.6%; the time required to achieve this recovery, as estimated with the García-Zuñiga model, is greater than 20min. This time was selected as the optimal time for the scavenger stage, taking into account that at 10min of flotation, the pyrite grade was 6.54% in the concentrate, and 0.25% in the scavenger tailings; the instantaneous grade of pyrite in the concentrate was 0.56%, and the scavenger concentrate produced could be recirculated to the rougher flotation stage.

Even though the kinetic constant for the cleaner stage (k=0.28min−1) is lower than for the rougher stage (k=1.08min−1), after 6min flotation the recovery continues increasing until reaching an estimated maximum recovery of 99.03% at 20min of flotation. Considering that at 10min of flotation the recovery is greater than 90% and that a longer flotation time decreases the pyrite grade in the concentrate; this time will be defined as the optimum time for the cleaner stage. The cleaner concentrate will be fed to a recleaner stage and the cleaner tailing with a 10% pyrite grade will be recirculated to the rougher stage.

The pyrite flotation in the recleaner stage is faster than in the cleaner stage. The recovery of pyrite at 5min of flotation is 97.8%, and at 7min of flotation the maximum estimated recovery of 99.1% is reached. In order to produce a concentrate with a pyrite grade closest to 90%, and a recovery above 90%, 3.5min were selected for the recleaner flotation stage as the optimum flotation time.

3.3Determination of the split factor

The split factor concept represents the percentage by weight of each component fed to a flotation stage, appearing in the concentrate, i.e., it corresponds to the pyrite and weight recovery for the rougher, scavenger, cleaner, and recleaner flotation stages. The magnitude of the split factor depends, mainly, on the flotation time, in addition to the physical and chemical properties of the pulp and the characteristics of the mineral. Table 7 presents the split factor calculated with the open cycle tests carried out with the flotation optimum time determined with the flotation kinetics. The values of the pyrite recovery (split factor) for the rougher, cleaner and recleaner flotation stages are of the same order of magnitude (>90%) as those estimated with the Garcia-Zuñiga model. Nevertheless, the split factor for the scavenger stage is lower than the estimated with the Garcia–Zuñiga model, approximately 15.8 percentage points.

Table 7.

Split factor calculated with the open cycle tests.

Stage  Pyrite recovery, %  Weight recovery, % 
Rougher  91.4  4.5 
Cleaner  93.4  55.0 
Recleaner  92.5  85.2 
Scavenger  43.5  1.4 
3.4Simulation of flotation alternative circuits

Fig. 2 shows the two simulated flotation circuits through the application of split factor procedures to recover pyrite from fresh tailings of copper ores flotation.

Fig. 2.

Simulated circuits through the application of split factor procedures. F, feed; C, concentrate; T, tailing.

(0.1MB).

Table 8 presents the global recovery and pyrite grade in the final concentrate (recleaner concentrate) for the two simulated circuits. In the table it is observed that with both circuits similar pyrite global recoveries were obtained, of the order of 94%. However, the circuit No. 1 produced a pyrite grade in the final concentrate lower than the circuit No. 2, 80.6% and 91.6% respectively. The highest grade of pyrite in the final concentrate produced in circuit No. 2 is attributed to the recirculation of the recleaner tailings to the rougher stage (see Fig. 2), which allowed the production of a rougher and cleaner concentrate with a higher pyrite grade than the circuit No. 1.

Table 8.

Global recovery and pyrite grade in the final concentrate (recleaner concentrate) for the two simulated circuits.

Circuit  Global recovery, %  Final concentrate pyrite grade, % 
No. 1  94.6  80.6 
No. 2  94.2  91.6 
3.5Implementation at industrial scale

Table 9 presents the global recovery and pyrite grade in the final concentrate (recleaner concentrate) for the four tests performed at industrial level, and it is observed that in the tests No. 3 and No. 4, pyrite grade in the final concentrate is higher than those obtained in both simulated circuits at laboratory scale. However, the global recoveries are lower, even though for the rougher, scavenger and recleaner stages the laboratory-to-industrial scaling factor was greater than 1.7. The lower pyrite grade in the test No. 1 is because of typical problems of the start-up, such as variations in the feed flow, pH, and air flow.

Table 9.

Global recovery and pyrite grade in the final concentrate at industrial scale.

Test  Global recovery, %  Final concentrate pyrite grade, % 
No. 1  81.28  78.60 
No. 2  73.47  89.5 
No. 3  71.89  94.7 
No. 4  69.47  95.9 
4Conclusions

Based on the results obtained in both studies, at laboratory and industrial scale, it can be concluded that:

  • A flotation circuit to produce pyrite concentrates of economic interest (pyrite grade over 90% and recoveries over 70%) from fresh tailings of a concentrator plant from the Atacama Region-Chile was designed.

  • The application of the experimental design showed that from the four variables studied, the only variable that has a statistically significant effect on the recovery of pyrite is the collector dosage.

  • To produce concentrates with grades and recoveries of pyrite over 90% and 70% respectively, the flotation circuit must be composed of rougher–scavenger–cleaner and recleaner stages and the fresh tailings must be conditioned for 10min with 30g/t of collector, 20g/t of frother, adjust the pH to 8, and set the flotation time for each stage in 10, 10, 10, and 5min, respectively.

  • To reprocess fresh tailings would not only improve the concentrator plants profitability of copper minerals, but it would also avoid the generation of a future environmental problem, such as the generation of acid mine drainage.

Conflicts of interest

The authors declare no conflicts of interest.

Acknowledgements

The authors acknowledge the funding provided by the Directorate of Research of University of Atacama, 2016 Regular DIUDA Project, the collaboration of Javier Jara and Bruno Zazzali in the performed experimental development, and Miss Evelyn Cárdenas for her support in the translation of this paper.

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Copyright © 2019. The Authors
Journal of Materials Research and Technology

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