Article pubs.acs.org/IECR
Optimization of Silver Removal from Anode Slime by Microwave Irradiation in Ammonium Thiosulfate Solutions Dilara Tokkan,† Soner Kuşlu,‡,* Turan Ç alban,‡ and Sabri Ç olak‡ †
The 8th Regional Directorate Quality Control Laboratory Department Office, DSI, Orgeneral Demircioğlu Street, 25100, Erzurum, Turkey ‡ Department of Chemical Engineering, Engineering Faculty, Atatürk University, 25240, Erzurum, Turkey ABSTRACT: We investigate the optimization of removal of silver from anode slime in ammonium thiosulfate solutions by microwave using statistical design methods. Ammonium thiosulfate concentration, leaching temperature, solid-to-liquid ratio and leaching time were selected as variables. A model was obtained among relevant parameters by means of variance analysis by using the Matlab Computer Software Programme. The optimum conversion conditions for process were found to be ammonium thiosulfate (ATS) concentration of 0.4 M, leaching temperature of 313 K, solid-to-liquid ratio of 1/10, leaching time of 90 min, and stirring speed of 500 rpm. Under optimal conditions, the removal of silver is obtained as 88.76%. It is observed that the model obtained has nearly fitted the full second-order model, and the correlation coefficient calculated at the 95% confidence level has a value of 0.97.
1. INTRODUCTION Industrial development has led to the generation of more and more industrial waste during production processes. Industrial sludge can normally be treated by extraction using acids or solvents. The extraction process is environmentally and economically attractive because it can dexotify industrial sludge and remove valuable metals for reuse. Various studies have investigated the effect of acids and solvents during the removal of metals from solid wastes, such as in extraction using nitric and sulfuric acids.1−4 However, some problems may arise during hydrometallurgical operations as extraction. This includes the low recovery of extracted metal, difficulties in solid−liquid separation, and effect of impurities on the case of purification. Anode slimes are collected from the bottom of the electrolytic cell during copper refinement. The value of the anode slimes is determined mainly by the noble metals content, but in certain processes the contributions of Ni, Se, and other impurities are significant. There are two different kinds of slime depending on the sources obtained. The first one is produced during the processing of copper concentrate and contains a relatively high concentration of gold, silver, selenium, and tellurium. The second slime is produced during the processing of recycled scrap and has a higher concentration of lead, copper, tin, and silver than the first one. The anode slimes are characterized by high concentrations of silver, lead, copper, and tin. The slimes without the copper are then enriched in lead, tin, silver, and gold.5 Several methods are used to recover the valuable metals from anode slimes. These methods can be differentiated into pyrometallurgical processes which include roasting in the presence of oxidizing agent, sulfate-roasting, and the soda/ash process and hydrometallurgical process in which anode slimes are worked using different leachants such as chlorine, nitric acid, and sulfuric acid.6−8 Anode slimes generally contain 1−25% Pb, and Pb is basically present as PbSO4. During the hydrometallurgical processing, the waste lead precipitates mostly as lead sulfate from solutions due © 2013 American Chemical Society
to its low solubility (4.3 mg/100 mL). Finally, the insoluble lead sulfate is mostly converted into soluble compounds by leachants of successive alkaline and acid leaching of industrial anode slimes. Copper refinery anode slimes can be advantageously deleaded by reacting the PbSO4 present in the anode slimes with Na2CO3 solutions and then leaching the resultant lead carbonate with acetic acid.9 Bulakhova and Ben’yash10 note that the reaction is essentially complete within 30 min at 20 °C and within 15 min at 50 °C. The rate depends slightly on the stoichiometric ratio of PbSO4/Na2CO3, and over 99% lead sulfate conversion is achievable at the higher temperature in the presence of excess Na2CO3. Talip et al.2 carried out a work that found the optimum conversion conditions for lead removal process by the Taguchi method are a solid−liquid ratio 0.05 of g/mL, reaction period of 600 s, reaction temperature of 50 °C, and Na2CO3 concentration of 2 M. Under optimal conditions, the experimental results show that the conversion of lead sulfate at the 95% confidence level can be 97%, approximately. In another study, the copper anode slime was dissolved in concentrated H2SO4, and the optimum parameters were confirmed as a reaction temperature of 210 °C, solid-to-liquid ratio of 0.5, and the reaction period of 2 h.11 Microwave (MW) is a nonionizing electromagnetic energy. It is characterized by mutually perpendicular electric and magnetic fields, lies in the region of the electromagnetic spectrum between millimeter and radio waves, and is defined as those waves with wavelengths of between 1 and 100 cm, corresponding to frequencies of between 300 MHz and 300 GHz, respectively. MW causes movement of molecules and ions, will be reflected, transmitted, and absorbed, and heats throughout an absorbing materials. The energy transfer is by dielectric loss in MW heating Received: Revised: Accepted: Published: 9719
January 29, 2013 June 20, 2013 July 3, 2013 July 3, 2013 dx.doi.org/10.1021/ie400345g | Ind. Eng. Chem. Res. 2013, 52, 9719−9725
Industrial & Engineering Chemistry Research
Article
with the increasing demand for more environmental friendly processes. Microwaves are a distinctive source of energy compared to conventional heating including because of the advantages of low processing time, direct, selective, and volumetric heating, and a more controllable heating process. In contrast, microwave energy is transferred to materials by interaction of the electromagnetic fields at the moleculars level, and the dielectric properties ultimately determine the effect of the electromagnetic field on the material.12 Some researchers focused especially on this subject are summarized as follows. Joret et al. studied the effect of microwaves on the dissolution rate of CeO2 and Co3O4 in nitric acid and explained that microwaves give rise to an apparent acceleration of the chemical reactions as a result of the superheating phenomenon.18 Shibata at al. studied the decomposition reaction of sodium hydrogen carbonate in water, and they found that activation energy of the reaction is reduced by microwave irradiation.19 Peng and Liu applied microwave energy in the leaching of sphalerite with acidic ferric cloride. Test results demonstrated that the leaching rate of zinc increased with microwave energy.20 Chao-Yin et al. investigated removal of copper from industrial sludge by traditional and microwave acid extraction. Their experimental results showed that the most economical traditional extraction conditions consisted of the use of 1 N sulfuric or nitric acid for 60 min at an S/L ratio of 1/20; however, at an S/L ratio of 1/6, the extraction time needed to achieve the same copper removal efficiency was increased to 36 h.1 Al-Harahsheh et al. investigated the reality of nonthermal effects in microwave-assisted leaching systems. In this work, chalcopyrite and sphalerite were chosen as model materials due to their economic importance and the diversity of their heating behavior in a microwave field. Leaching of both chalcopyrite and sphalerite in ferric sulfate under microwave conditions has shown enhanced recoveries of metal values compared to that produced conventionally.16 This work focuses on the optimization of removal of silver in ammonium thiosulfate (ATS) solutions from anode slime by microwave using statistical design methods. The effects of various parameters such as ammonium thiosulfate concentration, leaching temperature, solid-to-liquid ratio, and leaching time on the removal of silver from decopperized anode slime have been investigated. A model has been fitted among relevant parameters by means of variance analysis by using the Matlab computer software.
and is not by conduction or convection as in conventional heating.12 Microwave irradiation affects molecules by several mechanisms. There are principally two, dipolar rotation and ionic conduction, but these are not the exclusive mechanisms. Dipole rotation refers to the alignment with the electric field component of the radiation of molecules which have induced dipoles. When MW passes through a sample, the molecules of the sample having dipole moments will try to align themselves with it. At 2450 MHz, the field oscillates 4.9 × 109 times per second and sympathetic agitation of the molecules generates heat. The amount of energy transferred, the loss tangent, is a function of both dipole moment and dielectric constant. This is not a linear function. Dielectric loss factor and dielectric constant of a sample are two important dielectric properties of a sample in MW heating. The high value of dissipation factor which is the ratio of dielectric loss factor to dielectric constant indicates the susceptibility of the sample to MW. The energy transfer is more efficient when the molecules are able to relax quickly. The most efficient transfer occurs when the relaxation time matches the frequency of the MW energy.13 Ionic conduction is another important microwave heating mechanism. Ionic conduction is the migration of dissolved ions with the oscillating electric field. Heat generation is due to frictional losses. In ionic conduction, the energy is transferred from the electric field causing ionic interactions that speed up the heating of solutions. Ionic conduction increases with temperature allowing ionic solutions to become stronger absorbers of MW as they are heated. Microwaves cause molecular motion by migration of ionic species and rotation of dipolar species. Microwave penetrates the material, and vibrates the polar molecules at high frequencies and produces energy in the form of heat.13,14 Microwave dielectric heating has attracted the attention of chemists. It causes the reduced time scales of chemical reactions. Indeed, there is no satisfactory explanation that has been put forward in order to explain the observed acceleration of the reaction rate and drastic reduction in the processing time. The reduced time is attributed to microwave irradiation. The decrease in the activation energy observed in some research stimulates naturally the proposal of “non-thermal” or “a-thermal” specific microwave effects15 which accelerate a reaction to a rate faster than would be expected on the basis of the bulk reaction temperature; an increase in the probability of contact between molecules or atoms by rapid rotation of dipoles induced by microwave field might cause a reduction of the activation energy. Meanwhile, some researchers claim that microwaves provide only a convenient way to transfer energy to a given system and give rise to an apparent acceleration of the chemical reactions as a result of a “superheating” phenomenon in the context of “hot spots” theory.16,17 The natural consequence of this theory is that the bulk temperature is no longer representative of the reaction conditions. Over the past few decades, microwave heating has been employed in various technological processes such as pretreatment of ores, leaching, roasting, drying, and treatment of slags and wastes. MW is an increasingly used tool to enhance chemical process rates such as electrochemistry ultrasound and photochemistry, and has been used in various areas of chemistry: MWassisted drying, solvent extraction, leaching, sample preparation, hydrolysis, digestion and inorganic reactions, etc. Microwaveassisted leaching has been investigated in an attempt to improve the yield of extracted metal and to reduce process time, especially
2. EXPERIMENTAL DESIGN The experimental design is used to investigate the effects of variable parameters on a process. The factorial experiment design method is a statistical method using to determine the best experimental conditions.21,22 In this method, the influences of all experimental variables, factors, and interactions on the responses are investigated. A frequently used factorial experiment design is known as the 2k factorial design, which is basically an experiment involving k factors, each of which has two levels (“low” and “high”). In addition, a zero-level is also included, a center, in which all variables are set at their midvalue. The center experiments should always be included in factorial designs, for the following reasons: the risk of missing nonlinear relationships in the middle of the intervals is minimized, and repetition allows for determination of confidence intervals.23−26 The method used to compare the magnitude of estimated effects of factors with the magnitude of experimental error is called analysis of variance. If the magnitude of a factor effect is 9720
dx.doi.org/10.1021/ie400345g | Ind. Eng. Chem. Res. 2013, 52, 9719−9725
Industrial & Engineering Chemistry Research
Article
The decopperized anode slime was washed several times, filtered, and then dried with laboratory medium. The chemical composition of the sample blended homogeneously was determined by volumetric, standard gravimetric, and AAS methods. Chemical analysis of the decopperized anode slime used in the experiments is presented in Table 1. An X−ray diffractogram illustrating the contents of the decopperized anode slime was given in Figure 1.
large when compared with experimental error, it is decided that the changes in the selected response cannot occur by chance and those changes in the response can be the effects of the factors. The factors causing a variation in the response are called significant. Also, the effects of pure quadratic terms are controlled by means of the following statistic: LOFcurv =
moF(y1̅ − yo̅ )2 mo + F
(1)
Table 1. The Chemical Analysis of the Decopperized Anode Slime
Analysis of variance is the curvature effect. Because of this, auxiliary experiments are carried out. Among various second order designs, the orthogonal central composite design is the most popular which required 2n auxiliary runs conducted at two new factor levels of the factorial design required −β, +β. β is calculated by the following relation: ⎛ QF ⎞1/4 ⎜ ⎟ ⎝ 4 ⎠
(2)
Q = [N1/2 − F1/2]2
(3)
N = F + 2n + mo
(4)
β=
The second-order model is defined as follows so as to facilitate calculations. 4
Y = bo +
4
4
4
∑ biXi + ∑ bii(Xi 2‐ X12) + ∑ ∑ bijXiXj i=1
i=1
i=1 j>1
where 1 N
N
∑ Xi2 = i=1
F + 2β 2 N
(6)
by defining, 4
bol = bo −
∑ bij X12
(7)
i=1
eq 6 may be written in the usual form as 4
Y = bo1 +
4
4
4
∑ biXi + ∑ biiXi2 + ∑ ∑ bijXiXj i=1
i=1
i=1 j>1
decopperized slime (%)
Pb Ag Cu Au SO4−2 SiO2 Ni Fe Zn Sn Sb As humidity others
29 2.15 0.33 0.13 28.70 1.72 0.03 0.16 0.28 15.9 17.1 0.93 0.78 2.86
At the second stage, the optimum conditions on removal of lead from decopperized anode slime in ATS solutions by microwave were determined using statistical design methods. The experiments were carried out using the above-mentioned methodology as described elsewhere. In the light of preexperiments, ATS solution, leaching temperature, solid-to-liquid ratio, and contact time were chosen as independent process variables. The process variables and their levels for 1/2·25 factorial design are shown in Table 2. The 25 orthogonal factorial design and central composite design for the microwave process were applied to estimate both the main effects and second order effects leaching experiments that were performed in random order to avoid systematic error. As usual, three central replicates were also employed to calculate pure experimental error. Microwave experiments were conducted as follows: The glass reactor was filled with 200 mL of ammonium thiosulfate solution, which was then heated to the desired temperature. Subsequently, predetermined amounts of anode slime were added to the solution, and the stirring operation was started at a stable speed. At the end of the reaction period, the contents of reactor were immediately filtered, and the amounts of silver in the solution were analyzed by AAS. 3.1. Microwave Experimental System. The experimental microwave apparatus (Elta Ltd., Bursa, Turkey) designed in our laboratory can be seen in Figure 2. It consists of a microwave generator at 2450 MHz, with adjustable power within the range 0−1 kW; an R26 standard rectangular waveguide; and an applicator. Three manually adjustable stub tuners inserted in the waveguide section and the tuning plunger of the applicator were used to maximize microwave absorption by minimizing the reflected power. A cylindrical Pyrex glass reactor was installed in the applicator at the position of the highest electric field, with an internal volume of 500 mL, an internal diameter of 110 mm, and a height of 130 mm. It was equipped with a reflux condenser to prevent evaporation during heating. An optical fiber connected
(5)
X12 =
chemical composition
(8)
3. MATERIAL AND METHODS The work planned to research and optimize the parameters influencing the removal of silver from the anode slime contains the following stages: (1) The removing of copper from the raw anode slime,21 and (2) The removal of silver from decopperized anode slime in ammonium thiosulfate solutions by microwave (the present study). At the first stage, before the removal of silver, the copper in the anode slime supplied from Sarkuysan Copper Co. in Turkey was removed under appropriate conditions. On this occasion, the dissolution of the copper in the raw anode slime in H2SO4 solutions with/without oxygen was investigated, and the optimum conditions corresponding to a solubility of 99.67% were determined as follows:21 blade number of 1, reaction temperature of 70 °C, O2 flow rate of 1.24 × 10−6 m3·s−1, stirring speed of 450 min−1, acid concentration of 5.43 wt %, solid-toliquid ratio of 0.125 g/mL, and reaction period of 3600 s. 9721
dx.doi.org/10.1021/ie400345g | Ind. Eng. Chem. Res. 2013, 52, 9719−9725
Industrial & Engineering Chemistry Research
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Figure 1. X-ray diffractogram of the decopperized slime used in the study.
Table 2. Process Variable and Their Levels for 1/2·25 Factorial Design low level (−)
high level (+)
average level (0)
variable name
symbol for chosen variable
first order
second order
first order
second order
first and second order
ATS concn (M) temp (K) solid−to− liquid ratio (g·mL−1) contact time (min) stirring speed (rpm)
X1 X2 X3 X4 X5
0.2 303 1/10 60 500
0.13 296 7/100 50 433
0.4 313 1/5 90 700
0.47 330 23/100 100 767
0.3 308 3/20 75 600
Figure 2. Microwave experimental system.
4. RESULT AND DISCUSSION
to a transducer (PT-100) allowed the measurement of temperature inside the reactor with an accuracy of (1 °C). The magnitudes of the forward and reflected powers were measured by power meters through the directional coupler. The incident power minus the sum of the reflected and transmitted power gives the absorbed power. The forward, reflected powers, and the temperature inside the reactor were recorded and monitored using a programmable controller (μscada control program).27−29
ATS concentration, leaching temperature, solid-to-liquid ratio, and leaching time were selected as process variables to investigate their effects on the process. The experiments for observing the effect of concentration of ammonium thiosulfate solutions on the removal process was studied by varying to 0.2, 0.3, and 0.4 M. The dissolution level of the process increases with an increase in 9722
dx.doi.org/10.1021/ie400345g | Ind. Eng. Chem. Res. 2013, 52, 9719−9725
Industrial & Engineering Chemistry Research
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Table 3. Experimental Design Matrix and Dissolution Yield experiment no
X1
X2
X3
10 5 2 8 4 9 3 13 1 14 12 15 7 6 16 11
+ + + + − + + − − − + + − − − −
+ + + − + + − − + + − − + − − −
+ − − − − + + + + + + − − − − +
17 18 19 20 21 22 23 24 25 26
−1.664 +1.664 0 0 0 0 0 0 0 0
0 0 −1.664 +1.664 0 0 0 0 0 0
0 0 0 0 −1.664 +1.664 0 0 0 0
1* 2* 3*
0 0 0
0 0 0
0 0 0
X4
X5
First−Order Model + + − + + − + + + + − − + − + + − + + − − + − − − − − + + − − − Second−Order Model 0 0 0 0 0 0 0 0 0 0 0 0 −1.664 0 +1.664 0 0 −1.664 0 +1.664 Central Point Experiments 0 0 0 0 0 0
YAg with MW
YAg (Model) with MW
YAg without MW
79.25 85.59 91.74 68.19 76.37 74.01 58.71 53.15 60.46 65.61 55.92 64.05 70.52 50.15 54.07 41.78
80.95 83.73 88.76 69.64 75.75 75.92 61.83 48.82 62.91 67.94 56.81 64.61 70.72 61.60 56.63 43.80
72.40 75.63 80.08 59.86 63.85 66.75 51.64 41.06 53.90 55.21 50.01 54.68 65.44 42.83 48.87 34.31
57.61 78.52 51.06 80.52 72.18 59.09 63.09 70.40 65.33 68.43
56.94 78.60 47.72 79.54 74.27 61.28 63.59 71.96 66.55 68.78
45.92 68.96 49.20 76.06 61.24 55.44 54.08 60.53 55.79 58.92
71.16 73.14 72.79
67.66 67.66 67.66
63.45 62.25 64.71
Table 4. Analysis of Variancea
a
source of variation
sum of squares
df
mean squares
F ratio
P values
decision (α = 0.05)
X1 X2 X3 X4 X5 X1 X2 X1 X3 X1 X4 X1 X5 X2 X3 X2 X4 X2 X5 X3 X4 X3 X5 X4 X5 curvate lack of fit experimental error total
693.66 1550.98 322.11 124.38 4.61 6.14 8.37 3.97 3.72 20.23 0.02 5.07 1.26 4.79 1.61 115.63 20.23 2.23 2868.75
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 18
693.66 1550.98 322.11 124.38 4.61 6.14 8.37 3.97 3.72 20.23 0.02 5.07 1.26 4.79 1.61 115.63 20.23 1.12
621.21 1388.98 288.48 111.39 4.13 5.50 7.49 3.56 3.33 18.12 0.01 4.55 1.13 4.29 1.44 103.55 18.11
0.0016
