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Ind. Eng. Chem. Res. 2005, 44, 8952-8958
Determination of the Optimum Conditions for the Leaching of Nonsulfide Zinc Ores (High-SiO2) in Ammonium Carbonate Media Javad Moghaddam,† Rasoul Sarraf-Mamoory,*,† Yadollah Yamini,‡ and Mahmoud Abdollahy§ Materials Engineering Department, Chemistry Department, and Mining Engineering Department, Tarbiat Modarres University, P.O. Box 14115-175, Tehran, Iran
The Taguchi method was used as the experimental design to determine the optimum conditions for the dissolution of nonsulfide zinc ores in ammonium carbonate solution for high recovery of zinc, and to minimize the extraction of iron and lead. The experimental conditions were studied in the range of 35-75 °C for reaction temperature (T), 300-800 rpm for stirring speed (R), 2-4 mol for ammonium carbonate concentration (C), 30-90 min for reaction time (t), and 9-11 for pH (denoted as pH). The obtained optimum conditions from this study were T ) 45 °C, R ) 300 rpm, C ) 3 mol, t ) 45 min, and pH 10. Under these conditions, the optimum dissolution of zinc was ∼92%. To minimize iron and lead dissolution while keeping the dissolution of zinc, three series of experiments, in alternative conditions, were performed. Total optimum conditions that obtained from this study were T ) 45 °C, R ) 300 rpm, C ) 2 M, t ) 45 min, and pH 11. 1. Introduction
Table 1. Various Types of Zinc Minerals
Among the nonferrous metals, zinc is one of the most commonly used metals, after aluminum and copper; for the time period of 1998-1999, its worldwide production and consumption was almost 7.7 Mt.1 Zinc is primarily found in various forms around the world (ZnCO3, ZnS, etc.). The world’s zinc and zinc compounds reserves are most present in the United States, Canada, Australia, Mexico, Germany, and Poland, in order of descending resources. The minerals that commonly contain zinc are listed in Table 1. Blende, marmatite, and, to some extent, calamine presently are the only minerals of any commercial significance.2 The mineral deposits of the Angoran region in Iran have complex carbonate-silicate minerals that primarily contain zinc, lead, cadmium, nickel, and cobalt and they have high SiO2 content (∼11%-13% SiO2). The ore contains smithsonite (ZnCO3), hemimorphite (Zn4Si2O7(OH)2‚H2O), and quartz (SiO2). The dissolution of mineral ores in aqueous solutions may occur via physical, chemical, or electrochemical processes. The crystalline nature of the mineral, its state of subdivision, its defect structure, and other factors have an important role in the dissolution.3 None of the oxidized zinc minerals lend themselves very readily to any known concentrating method. Their specific gravities are too low for good gravity separations. Although many other carbonate and silicate minerals have yielded to concentration by flotation, the results along this line have not been successful with oxidized zinc ores.4 Often, all three minerals are simultaneously present in a single ore sample, although one mineral generally predominates. The zinc from all three must be extracted if a high overall recovery is going to * To whom correspondence should be addressed. Tel: +98-21-8011001. Fax: +98-21-8005040. E-mail address:
[email protected]. † Materials Engineering Department. ‡ Chemistry Department. § Mining Engineering Department.
mineral
formula
zinc blende or sphalerite marmatite calamine or smithsonite hemimorphite hydrozincite zincite eillemite
ZnS (ZnFe)S ZnCO3 4ZnO‚2SiO2‚2H2O 5ZnO‚2CO2‚3H2O ZnO 2ZnO‚SiO2
be obtained.4 Along this line, it should also be noted that, although smithsonite may be the principal mineral in one part of a large ore body, hydrozincite or calamine may predominate in some other part. This further complication limits the chances of working out a successful concentrating method.4 In view of this conditions, a hydrometallurgical process would seem to offer a reasonable solution to the problem if a suitable solvent were available.4 Sulfuric acid (H2SO4) is a leaching reactant used to recover zinc from oxidized zinc ores. Leaching of oxidized zinc ores with H2SO4, sulfurous acid (H2SO3), ammonium hydroxide (NH4OH), and sodium hydroxide (NaOH) solutions have been studied, and it has been found that NaOH is less effective than H2SO4.5 In another study, it has been found that H2SO4 or NaOH leaching reveals better results than H2SO3 and NH4OH.6 An oxidized material that contains a great amount of zinc and iron was leached with H2SO4, and ZnSO4‚7H2O (which was 99.5% pure) was obtained.7 Several other solvents exist, but a solvent that consists of ammonia and ammonium carbonate seems to possess the most desirable combination of properties. Ammonia has been widely used as an effective lixiviant in several hydrometallurgical processes for many years.8 The leaching of metals in ammoniacal solutions is primarily applied for the extraction of nonferrous metals such as copper from oxide ores or ores that contain native copper. The application of this leaching technology is gradually expanding from more traditional treatments of copper, nickel, and cobalt to the extractive metallurgy of zinc, cadmium, silver, and gold.8
10.1021/ie050479+ CCC: $30.25 © 2005 American Chemical Society Published on Web 11/01/2005
Ind. Eng. Chem. Res., Vol. 44, No. 24, 2005 8953
Figure 1. X-ray diffractrogram of the original ore.
Although ammonia leaching has been applied for zinc extraction for a long time,9 the leaching behavior of the Angoran zinc mineral with special compounds in ammoniacal solutions has not been investigated until now. The Eh-pH diagram of the Zn-NH3-H2O system shows that there are two stable regions for zinc hydroxide. Zinc tetra-ammine (Zn(NH3)42+) is stable only in the pH range of 8-11. The stability region of the solid phase decreases or even disappears as the activity of the soluble species or ammonia concentration increases.8 De Juan et al. studied the leaching behavior of Waelz oxides, using ammonium carbonate-ammonia (AAC) and ammonium sulfate-ammonia (AAS) solutions at ambient temperature and atmospheric pressure. Results showed that 94% of the zinc contained in such oxides was recovered when a 2.5-M ammonium carbonate solution with a pH of 10.1-10.5 (fixed with ammonia) was used.8 The Taguchi method has been shown as an effective means for the improvement of the productivity in the stage of research and development so that high quality items can be produced quickly at low cost. It has found much application in a wide range of industrial fields all over the world, because of its universal applicability to all engineering fields.10 In this study, the leaching behavior of zinc carbonate minerals from the Angoran region in Iran in AAC solutions was investigated. The experimental parameters such as reaction temperature (T), stirring speed (R), time (t), ammonium carbonate concentration (C), and pH (denoted as pH) on the zinc recovery, using an L25 (55) orthogonal array, were investigated. The Taguchi experimental design method was used to determine optimum leaching conditions for maximizing zinc recovery and minimizing iron and lead. 2. Experimental Section 2.1. Materials and Methods. A zinc carbonate ore sample was obtained from the Angoran mines (Angoran, Zanjan, Iran). The ore was divided, using a standard rotary sample divider (Fritsch, model Laboratte 27) and was sieved using a 200 mesh ASTM standard sieve. For complete ore characterization, the sample was analyzed using an X-ray diffractometer (Phillips, model EXPERT). The results showed that the sample contained mainly smithsonite, hemimorphite, mimmetite, and SiO2. An X-ray diffractogram of the sample is given in Figure 1. Major and trace elements were analyzed using inductively coupled plasma (ICP) spectroscopy (Varian, model vista-pro ICP-OEP) and X-ray fluorescence (XRF) (Phillips, model PW2404). The results were given in Tables 2 and 3.
Table 2. Chemical Composition of Main Elements in Original Ore, Obtained Using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) component
amount (wt %)
Zn Pb Fe Cu Cd Ni Co Ca Al K Na
35.1 1.2 2.3 0.0092 0.16 0.04 0.03 1.85 0.15 0.01 0.04
Table 3. Chemical Composition of Main Elements in Original Ore, Obtained Using X-ray Fluorescence (XRF)
a
component
amount (wt %)a
Zn Pb Fe2O3 Cd Ni Co CaO Al2O3 K2O As MnO TiO2 Cl SO3 P2O5 SiO2 MgO
43.51 6.98 2.79 0.13 0.12 0.05 2.66 4.33 0.54 1.01 0.20 0.11 0.09 0.56 0.05 12.44 0.68
Semiquantitative.
Table 4. Chemical Composition of Some Elements in the Calcined Ore, Obtained Using ICP-OES component
amount (wt %)
Zn Pb Fe Cu Cd Ni Co Ca Al K Na
42.18 2.01 2.21 0.008 0.14 0.03 0.03 1.67 0.53 0.01 0.42
Zinc analysis in the leach liquor was performed by complexometric titration, using ethylenediamine tetraacetic acid (EDTA) as the titrante and Eriochrome Black T as the indicator. Prior to the dissolution experiments, the ore was calcined in a tube furnace at 800 °C for 1 h. The chemical compositions of the calcined ore and its XRD
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Figure 2. X-ray diffractrogram of the calcined ore. Table 5. Parameters and Their Values Corresponding to Table 6 Value parameter reaction temperature, T (°C) stirring speed, R (rpm) ammonium carbonate concentration, C (M) reaction time, t (min) pH
level 1
level 2
level 3
level 4
level 5
35 300 2
45 400 2.5
55 500 3
65 650 3.5
75 800 4
30 9
45 9.5
60 10
75 10.5
90 11
diffractogram are given in Table 4 and Figure 2, respectively. The dissolution experiments were performed in a glass reactor with a volume of 1 L submerged in a thermostatic bath. The vessel has four necks: one for the stirrer (Heidolf RZR 2020), one for the pH meter (Hanna pH 209), one for inlet of the sample, and one for the thermometer. The mechanical stirrer had a controller unit, and the bath temperature was controlled using a digital controller (within (0.5 °C). The pH was adjusted via the addition of ammonia. All of the chemical materials that were used in this study were purchased from Merck Company (Darmstadt, Germany). Three hundred milliliters of (NH4)2CO3 solution at a given concentration (2-4 mol) was placed into the reactor. When the desired temperature (35-75 °C) of the reactor content was reached, a predetermined amount (50 g) of calcined ore was added into the solution while the content of the vessel was being stirred at a certain speed (300-800 rpm) and the pH was being controlled by adding ammonia at a certain pH (9-11). At the end of the reaction period, the content of the vessel was filtered and the filtrate was either titrated for Zn2+ or analyzed by ICP to determine the iron and lead contents. Experimental parameters and their levels determined in the light of preliminary tests have been given in Table 5. 2.2. Taguchi Method. The technique of defining and investigating all possible conditions in a experiment involving multiple factors is known as the design of experiments.11 Basically, classical parameter design, which was developed by Fisher, is complicated and not easy to use.12 Especially, a large number of experiments must be conducted when the number of the process parameters increases. To solve this task, the Taguchi method uses a special design of orthogonal arrays to study the entire parameter space with a small number of experiments only.12
The orthogonal array (OA) L25 (55), which denotes five quantities each with five levels, was chosen and each experiment was repeated twice under the same conditions at different times to observe the effects of noise sources in the dissolution process. Table 6 represents the selected orthogonal array for this study. Taguchi recommends the use of the loss function to measure the performance characteristic deviating from the desired value.12 The value of the loss functions is further transformed to a signal-to-noise (S/N) ratio. Usually, there are three categories of the performance characteristic in the analysis of the S/N ratio: that is, the lower, the better; the higher, the better; and the nominal, the better. The S/N ratio for each level of process parameters is computed based on the S/N analysis.12 3. Results and Discussion Table 6 shows the experimental conditions and results for the dissolution of zinc mineral based on L25 (55) matrix design. To use the S/N ratio for optimal dissolution performances, SNL and SNS calculation was performed to maximize zinc recovery and to minimize the iron and lead in leach liquor solution, respectively. The two performance characteristics were evaluated using the following equations:
the lower, the better:
the higher, the better:
(∑ ) 1
SNS ) -10 log
n
ni)1
yi2
( )
SNL ) -10 log
1
n
∑ ni)1
1
yi2
(1)
(2)
where SNS and SNL are performance characteristics, n is the number of repetitions performed for an experimental combination, and yi is the performance value of the ith experiment.13 The results of variance analysis are given in Tables 7-9. Statistical analysis of variance (ANOVA) was performed to see whether the process parameters are statistically significant or not. The F-value for each process parameter indicates which parameter has a significant effect on the dissolution value. With ANOVA analysis and performance characteristics, the optimal combination of process parameters can be predicted. In the Taguchi method, the experiment corresponding to the optimum working conditions might not been conducted during the entire period of the experimental stage. In such cases, the performance value correspond-
Ind. Eng. Chem. Res., Vol. 44, No. 24, 2005 8955 Table 6. L25 (55) Randomize Experimental Plan Table and Results Parameters and Their Levels
Results
experiment
T
R
C
t
pH
Zn (%)
Zn (%) R
Fe (ppm)
Fe (ppm) R
Pb (ppm)
Pb (ppm) R
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
1 2 3 2 5 1 3 5 5 2 2 2 5 1 1 4 4 3 3 4 5 1 4 3 4
1 5 2 1 1 3 5 5 4 3 4 2 3 4 5 3 2 1 4 1 2 2 4 3 5
1 1 4 2 4 3 2 3 2 4 5 3 1 4 5 2 1 3 1 5 5 2 3 5 4
1 2 1 3 2 3 4 1 5 5 1 4 4 4 5 1 5 5 3 4 3 2 2 2 3
1 3 3 4 5 3 1 4 3 1 2 5 2 4 5 5 4 2 5 3 1 2 1 4 2
86.56 92.79 89.68 90.46 91.86 91.07 89.99 84.38 89.21 91.85 90.46 92.79 88.74 90.46 88.12 90.61 93.73 94.97 86.09 92.17 94.50 90.14 91.07 87.96 87.80
89.05 93.88 88.74 89.67 86.88 88.12 88.27 92.64 81.90 88.58 88.27 89.52 89.52 90.30 87.03 92.48 89.20 93.73 84.54 93.57 89.05 91.70 92.32 87.65 81.90
7.44 3.70 5.48 1.86 1.97 4.39 10.58 3.49 0.93 37.37 2.10 0.59 1.90 5.80 0.03 0.25 0.30 2.88 0.10 1.88 9.95 19.36 11.34 1.60 14.56
11.18 4.31 2.11 3.10 2.05 0.05 11.02 0.69 2.76 10.63 15.49 2.27 3.19 5.08 2.69 0.59 0.27 9.93 0.13 2.13 14.56 11.92 7.74 7.89 8.01
156.67 43.56 101.43 165.54 130.74 162.95 100.10 78.21 142.37 119.01 39.60 132.26 126.98 59.32 34.10 106.99 77.60 142.17 52.53 80.35 99.05 57.54 74.40 63.20 55.50
67.75 35.70 45.05 34.25 52.65 53.00 49.60 73.55 84.65 38.35 36.60 73.35 44.45 119.55 33.95 48.90 84.40 68.45 65.90 104.60 66.50 54.55 46.80 72.75 82.60
Table 7. Results of the Analysis of Variance for the Dissolution Values of Zinca
a
parameter
sum of squares, S
degree of freedom, f
variance, S/f
variance ratio, F
reaction temperature ( °C) stirring speed (rpm) ammonium carbonate concentration (mol) reaction time (min) acidity, pH error total
3.36 5.40 2.03 3.64 0.83 12.25 28.28
4 4 4 4 4 4 24
0.84 1.35 0.70 0.91 0.21 3.06
0.27 0.44 0.23 0.30 0.06 1
FTable ) 6.39 with 95% confidence.
ing to the optimum working conditions can be predicated by utilizing the balanced characteristic of OA. Under these conditions, the following additive model may be used:
Yi ) µ + Xi + ei
Yi (
x
FR;1, DFMse(MSe)
(P1 - 1)
Ω(db) ) -10 log
(5)
(3)
where µ is the overall mean of performance value, Xi the fixed effect of the quantity level combination used in the ith experiment, and ei the random error in the ith experiment.13 Equation 3 is a point estimation, which is calculated using experimental data; therefore, to determine whether the results of the confirmation experiments are meaningful or not, the confidence interval must be evaluated. The confidence interval at the chosen error level may be calculated using
confidence interval )
centage values should be applied first, using the following equation:
(
)
1+m 1 + (4) N ni
where F is the value of the FTable, R the error level, DFMse the degree of freedom of mean square error, m the number of degrees of freedom used in the prediction of Yi, N the number of total experiments, and ni the number of repetitions in the confirmation experiment. If experimental results are given as percentages before evaluating eqs 3 and 4, Ω transformation of the per-
where Ω(db) is the decibel value of the percentage value subject to Ω transformation and P is the percentage of the product obtained experimentally.13 Values of interest are then determined later, by performing reverse transformation using the same equation. In the case of zinc recovery (which is expressed as a percentage), Ω transformation and SNL quantities are calculated. The results of ANOVA analysis for zinc are given in Table 7. The F-value for this condition, with 95% confidence, is 6.39.11 Therefore, as observed in Table 7, no parameter has a statistically meaningful effect for the dissolution of zinc. For the dissolution of iron, Table 8 shows that pH and the ammonium carbonate concentration (C) each have significant effects on the dissolution process, whereas the reaction temperature (T), stirring speed (R), and reaction time (t) have no effect within the working range. The pH value has the most important effect on the minimum dissolution of iron. The solubility product for Fe(OH)3 is expressed by the relation Ks ) aFe3+ × aOH-3 ) 3.8 × 10-38. By increasing the equilibrium pH, the number of OH- ions increases and, therefore, hydrolysis becomes increasingly more favorable.14 Therefore, the number of Fe3+ ions in solution decreases.
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Table 8. Results of the Analysis of Variance for the Dissolution of Iron parameter
sum of squares, S
degree of freedom, f
variance, S/f
variance ratio, F
pure sum of squares
contribution, P (%)
reaction temperature (°C) stirring speed (rpm) ammonium carbonate concentration (mol) reaction time (min) acidity, pH error total
293.25 64.57 605.37 141.58 1820.34 54.46 2979.58
4 4 4 4 4 4 24
73.31 16.14 151.34 35.39 455.09 13.615
5.39 1.19 11.12 2.60 33.43 1
238.80 10.11 550.91 87.19 1765.88 0
8.01 0.34 18.49 2.92 59.27
a
FTable ) 6.39 with 95% confidence.
Table 9. Results of the Analysis of Variance for the Dissolution of Lead
a
parameter
sum of squares, S
degree of freedom, f
variance, S/f
variance ratio, F
reaction temperature (°C) stirring speed (rpm) ammonium carbonate concentration (mol) reaction time (min) acidity, pH error total
16.38 93.41 50.99 36.84 16.91 16.97 231.51
4 4 4 4 4 4 24
4.10 23.35 12.75 9.21 4.23 4.24
0.97 5.51 3.00 2.17 1.00 1.00
FTable ) 6.39 with 95% confidence.
Table 10. Optimum Working Conditions and Alternative Working Conditions for Three Different Experimental Conditions, Showing Observed and Predicted Dissolved Quantities Case 1 parameter T R C t pH
value 45 300 3 45 10
Case 2 level 2 1 3 2 3
value 45 300 2.5 45 11
Case 3 level 2 1 2 2 5
value 45 300 2 45 10.5
Case 4 level 2 1 1 2 4
value 45 300 2 45 11
observed Zn (%) predicted Zn (%) confidence limit
(1) 91.72, (2) 93.1 88.14 84.07-92.21
88.57 84.84 80.775-88.91
89.5 85.56 81.46-89.62
88.2 84.97 80.91-89.04
observed Fe (ppm) predicted Fe (ppm)
7.92 11.75
2.03 0.36
3.56 1.19
1.2 0.95
observed Pb (ppm) predicted Pb (ppm)
84.65 136.9
56.2 54.56
67.3 55.9
35.2 46.06
Table 9 shows that, for the dissolution of lead, it has also been observed that no parameter has a meaningful effect on the dissolution of lead. Under economical considerations, it is desired that the dissolved amount of iron and lead to be minimum, and the temperature T, stirring speed R, ammonium carbonate concentration C, reaction time t, and pH should be kept low. For this reason, it would be useful to investigate how zinc recovery would be affected with changes at the same values of minimum dissolution of iron and lead. The influences of parameters on the performance characteristics have been given in Figures 3-5. The highest SN level that is calculated by eq 1 or 2 is the optimal level of a process parameter. The best value of each graph is the value of the maximum point that marked a particular parameter in each graph and was given in case 1 of Table 10 for each parameter. Figure 3 shows that the parameter values of the optimum conditions for zinc recovery are T2 (45 °C), R1 (300 rpm), C3 (3 M), t2 (45 min), and pH3 (pH 10). Under these conditions, the predicted amount of zinc recovery and confidence limits were 88.14% and 84.07%-92.21%, respectively. It can be seen that the predicted amount was within the confidence limits and an additional model (eq 3) was adequate for prediction; also, results of the confirmation experiments were meaningful.
level 2 1 1 2 5
Figure 4 shows that the optimum conditions for minimum iron are T4 (65 °C), R4 (650), C1 (2 M), t3 (60 min), and pH5 (pH 11), and, finally, Figure 5 shows that the optimum conditions for minimum lead are T2 (45 °C), R5 (800 rpm), C5 (4 M), t2 (45 min), and pH2 (pH 9.5). Thus, because the minimum iron content is more important than the lead content in solution (the lead content can be removed by strontium carbonate or with zinc powder cementation), it is desired that those parameter levels be selected to be near to the minimum iron in solution. As previously mentioned from Table 8, pH was chosen in maximum quantities and ammonium carbonate concentration was chosen in minimum. Three series of experiments were performed, and the statistically analyzed results were given for cases 2-4 in Table 10. If the experimental plan given in Table 6 were to be studied carefully, together with Table 5, it can be observed that the experiments corresponding to the work conditions in Table 10 have not been performed during the planned experimental work in Table 6. The dissolution percentage for zinc and the dissolution contents for iron and lead (given in units of ppm) in Table 10 are predicted results that are obtained using eqs 3 and 4 and observed results for the same conditions. To test the predicted results, confirmation experi-
Ind. Eng. Chem. Res., Vol. 44, No. 24, 2005 8957
Figure 3. Effect of each parameter on the optimization criteria of zinc.
Figure 4. Effect of each parameter on the optimization criteria of iron.
Figure 5. Effect of each parameter on the optimization criteria of lead.
ments were performed twice under the same working conditions. The results showed that minimum iron and lead dissolution occurred in the conditions T2 (45 °C), R1 (300 rpm), C1 (2 M), t2 (45 min), and pH5 (pH 11). Under these conditions, zinc recovery has been kept at 88.2%. Its predicted amount and confidence limits were 84.97% and 80.91%-89.04%, respectively. It was stated that an additional model was adequate for prediction and also results of confirmation experiments were meaningful. The observed amounts of iron and lead in solution were 1.2 and 35.2 ppm, respectively, which are the most minimum amounts for this study. 4. Conclusions The main conclusions can be derived from this study are as follows: (1) It can be stated from the results of primary experiments that, when the ore is calcined at a temperature of ∼800 °C, the rate of chemical reactions was increased. (2) Quantity values of optimum conditions for zinc recovery are 45 °C for reaction temperature (T), 300 rpm
for stirring speed (R), 3 mol for ammonium carbonate concentration (C), 45 min for reaction time (t), and 10 for pH (denoted as pH). Under these conditions, the dissolution of zinc in ammonia solutions was ∼92%. (3) No parameter has a meaningful effect for the dissolution of zinc and lead statistically; however, pH and the ammonium carbonate concentration each have a significant effect on the dissolution process of iron. (4) The predicted and observed dissolution values are similar to each other, so it may be concluded that the additive model is adequate to describe the dependence of the dissolution process on the various parameters. (5) The most important parameter that affects the solubility of iron is pH. (6) The total optimum conditions that were obtained from this study occurred at T2 (45 °C), R1 (300 rpm), C1 (2 M), t2 (45 min), and pH5 (pH 11). Literature Cited (1) Babu, M. N.; Sahu, K. K.; Pandey, B. D.; Zinc Recovery from Sphalerite Concentrate by Direct Oxidative Leaching with Ammonium, Sodium and Potassium Persulphates. Hydrometallurgy 2002, 64, 119.
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(2) Morgan, S. W. K. Zinc and Its Alloys and Compounds, First Edition; Ellis Horwood Limited: New York, 1985. (3) C¸ opur, M. Solubility of ZnS Concentrates Containing Pyrite and Chalcopyrite in HNO3 Solutions. Chem. Biochem. Eng. Q. 2001, 15 (4), 181. (4) Wendt, W. J. Ammonia; Ammonium Carbonate Leaching of Low Grade Zinc Ores. Eng. Min. J. 1963, 154, 84. (5) Dimanche, F.; Ek, C.; Frenay, J. Processing of Belgian Oxidized Zinc Ores. Spec. Publ. Ged. Soc. 1983, 7, 235. (6) Frenay, J. Leaching of oxidized zinc ores in various media. Hydrometallurgy 1985, 15 (2), 243. (7) Goldstein, J.; Bordas, E.; Staicu, F.; Faur, G. Zinc Sulfates from Oxide Materials with High Zinc and Iron Contents. Intreprinderea Metalurgica de Motela Neferoase. 1980, 101 (268), 29. (8) Lozano Blanco, L. J.; Meseguer, V. F.; De Juan Garcia, D. Statistical Analysis of Laboratory Results of Zn Wastes Leaching. Hydrometallurgy 1999, 54, 41. (9) Hewedi, M. A.; Engle, L. F. The NH3-CO2-H2O System at Atmospheric Pressure in Non-Ferrous Extractive Metallurgy. In Proceedings of the International Symposium on Hydrometallurgy, Chicago, IL, 1973; p 806.
(10) C¸ opur, M.; Ozmetin, C.; Ozmetin, E.; Kocakerim, M. M. Optimization Study of the Leaching of Roasted Zinc Sulphide Concentrate with Sulphuric Acid Solutions. Chem. Eng. Process. 2003, 43, 1007. (11) Roy, R. K. A Primer on the Taguchi Method, First Edition; Van Nostrand Reinhold: New York, 1995. (12) Nian, C. Y.; Yang, W. H.; Tarng, Y. S. Optimization of Turning Operations with Multiple Performance Characteristics. J. Mater. Process. Technol. 1999, 95, 90. (13) C¸ opur, M.; Pekdemir, T.; C ¸ elik, C.; C¸ olak, S. Determination of the Optimum Conditions for the Dissolution of Stibnite in HCl Solutions. Ind. Eng. Chem. Res. 1997, 36, 682. (14) Jackson, E. Hydrometallurgical Extraction and Reclamation; Ellis Horwood Limited; Chichester, U.K., 1986.
Received for review April 22, 2005 Revised manuscript received August 11, 2005 Accepted October 4, 2005 IE050479+
