Hydrometallurgy 81 (2006) 130 – 141
www.elsevier.com/locate/hydromet
Dissolution behavior of Fe, Co, and Ni from non-ferrous
smelter slag in aqueous sulphur dioxide
Philip K. Gbor, Shamia Hoque, Charles Q. Jia ⁎
Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, Ontario, Canada M5S 3E5
Received 19 October 2004; received in revised form 27 September 2005; accepted 23 October 2005
Abstract
Large amounts of non-ferrous slags containing Co, Ni, and Cu are produced and stockpiled by metallurgical industries. These
industries also produce sulphur dioxide, an air pollutant. Using sulphur dioxide as a leaching reagent to leach the valuable metals
from slag would reap both economical gains and environmental benefits. Extraction of these metals using aqueous sulphur dioxide
(SO2(aq)) is being carried out in our group.
The OLI software, was applied to study the thermodynamics of slag–SO2 system. A private data bank was created and
incorporated into the OLI software. Unknown thermodynamic data, mainly for metal-S(IV) complexes, were estimated and used
for the simulation. The solubility of slag in SO2(aq) increased with increasing concentration of SO2(aq) and decreased with increase
in temperature, ionic strength and pH. The main species in the system were the metal-S(IV) species. About 80% of dissolved Fe
was present as FeSOo3, while FeHSO+3 and Fe2+ each accounted for about 10%. Co– and Ni–SO3 complexes contributed about 60%
of the dissolved Co and Ni while the Co– and Ni–HSO3 complexes and free metal ions each contributed about 20%. As the total
concentration of S(IV) increased in the system the species FeSOo3 would become saturated and precipitate as FeSO3·3H2O. This
suggested that iron could be removed from the system as sulphite and the Co and Ni in the solution could be enriched. Lower
temperatures and ionic strengths enhanced the formation of this precipitate. The calculated solubility was compared with
experimental results and a good agreement was obtained.
Experimentally, when the pH of the leach solution was increased FeSO3·3H2O precipitate was obtained. As a result the ratio of
Co to Fe in solution doubled while Ni to Fe ratio increased nearly four times. The increase of ratio was less than expected likely
due to the coprecipitation of Co and Ni with Fe. The metal / Fe ratio in solution was sensitive to pH. High metal / Fe ratio is obtained
within a pH range of 3–4; pH values above 5 result in overall removal of metals from the solution.
© 2005 Published by Elsevier B.V.
1. Introduction
Large amounts of non-ferrous smelter slags are
produced and stockpiled by pyrometallurgical industries. In Canada alone, over ten million tons are
produced each year (Dresler et al., 1997). Though
these slags generally contain low levels of valuable
⁎ Corresponding author. Fax: +1 416 978 8605.
E-mail address: [email protected] (C.Q. Jia).
0304-386X/$ - see front matter © 2005 Published by Elsevier B.V.
doi:10.1016/j.hydromet.2005.10.007
metals like Co, Ni, and Cu (each b 1%), they are a good
secondary source of minerals if an economic process can
be devised for metal extraction. One approach being
investigated in our group is the application of SO2 to
extract valuable metals from slag. SO2 is readily
available at metallurgical sites and is usually expensive
to convert and market as sulphuric acid. Therefore, its
utilization onsite for economic benefits is prudent.
The slag is composed mainly of fayalite (Fe2SiO4).
Co exists as an oxide in solid solution with the silicate
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
phase. Cu and Ni however, exist as mixed oxides and
sulphides, with the sulphides present mainly as
entrained matte prills (Gbor, 2003). Leaching studies
have indicated that there isn't significant selectivity of
the valuable metals over iron when slag is leached with
SO2(aq). The overall dissolution of the valuable metals
therefore depends on the dissolution of the bulk silicate
phase, which results in solutions containing high
amounts of Fe compared to Co and Ni.
Iron removal from hydrometallurgical systems has
mainly been achieved as iron hydroxide, jarosite,
goethite and hematite. Anand et al. (1983) reported
that, 92% Cu, 95% Ni, 95% Co and only 0.8% Fe
extraction was achieved from Ghatsila smelter slag
using dilute sulfuric acid at a temperature of 130 °C and
oxygen partial pressure of 0.59 MPa. Iron was rejected
as hematite. Sulphuric acid pressure leaching has been
used for the recovery of nickel from limonitic laterites
(Papangelakis et al., 1996) where iron is rejected by
precipitation as hematite or basic ferric sulphate under
the leaching conditions (250–270 °C). Banza et al.
(2002) employed hydrogen peroxide to decrease iron
dissolution from over 90% to less than 5% during
sulphuric acid leaching of copper smelter slag at 70 °C
and at a pH of 2.5. The iron precipitated out as goethite.
Precipitation of Fe out of a system as sulfites is also a
possibility not yet explored extensively. Linkson (1982)
discussed the possibilities of the formation of sulfites of
Fe, Ni and Co. Linkson and Larsen (1984) have also
discussed the possibility of precipitating zinc as zinc
sulphite (ZnSO3·2.5H2O) at pH values of 2 from the
leach solution after the extraction of the metal from its
sulphide ore, without a description of the procedure.
Spink et al. (1991) developed a flow sheet for the
production of pure ZnO. In this process zinc is
selectively precipitated out as ZnSO3, which is then
roasted to produce ZnO. The insolubility of ZnSO3
gives a selective production of pure ZnO. Due to the fact
that slag contains b1% of Co, Ni and Cu, the application
of high pressure or high temperature to extract the
metals might not be economically feasible. A more
economical method could be precipitating the iron out
as sulfite using only aqueous SO2.
An in-depth study of the solubility of slag in aqueous
SO2 will provide important information on the behavior
of the slag–SO2 system. The understanding of the slag–
SO2 system can be enhanced by the application of
thermodynamic modeling. Thermodynamic modeling
tools are increasingly being applied to better comprehend complex systems. There are a number of tools
available for thermodynamic modeling of aqueous
systems. Among them, the OLI Systems software has
131
been successfully used to simulate a number of
thermodynamic systems, including, the solubility of
hematite in H2SO4 at high temperatures (Liu et al.,
2003), solubility of calcium sulphate in mixed HCl and
CaCl2 solutions (Li et al., 2002), and also to provide a
guide for determining the solubility of metal hydroxides
in environmental systems (Dyer et al., 1998).
In this paper the simulation of slag solubility in SO2
(aq) is discussed. Innovative methods used to estimate
unknown thermodynamic data are mentioned. Furthermore, the thermodynamic simulation results are compared with available data on solubility of slag in SO2 (aq).
Next, results obtained from experiments carried out based
on the simulation predictions have been discussed.
2. Experimental
2.1. Materials
The two main materials used for the experiments
were slag and SO2 gas. The slag is composed mainly of
fayalite (Fe2SiO4). Small amounts of spinel and albite
were found. Fe and Co were present mainly as oxides
(over 90%) but significant amounts of Cu and Ni were
present as sulphides (30–90%) (Gbor et al., 2000; Gbor,
2003). Table 1 is a summary of the metal percentages
present in the slag at different particle size distribution.
2.2. Apparatus and procedure
Fig. 1 is the schematic representation of the
experimental setup used for leaching slag with SO2.
The main apparatus of the experiment consisted of a
glass reactor (500 cm3) with five ports. The reactor was
fitted with pH/ORP probe, thermometer, Teflon sampling tube, condenser, stirrer and a gas sparger. To
maintain temperature, the glass reactor was placed in a
water bath fitted with thermostatic heater (Cole Parmer
Polystat Immersion Circulator, Model 01266-02). For
stirring purposes, a mechanical mixer that was attached
Table 1
wt.% of the components present in slag
Component wt.% present in slag
b28 μm
25–38 μm 53–75 μm 75–106 μm
(slow cooled (fast cooled (fast cooled (fast cooled
slag)
slag)
slag)
slag)
Co
Ni
Cu
Fe
Si
0.18
0.69
0.75
32.31
∼17
0.14
0.25
0.02
30.7
∼17
0.12
0.27
0.01
33.3
17.4
0.13
0.27
0.02
33.6
17.7
132
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
Gases
20
1
10
H2O
3
14
13
11
12
2
21
9
19
8
4
5
18
7
6
15
16
17
Key
1. Motor
2. Shaft
3. Bearing
4. Impeller
5. Reactor vessel
6. Wooden support
7.Heater with stirrer
8. Temperature controller
9. Water bath
10. Stirrer controller
11.Sampling tube
12. Thermometer
13. pH/ORP probe
14. pH meter
15. Computer
16. SO2 (g) tank
17. N2 (g) tank
18. Flow meters
19. Gas mixer
20. Condenser
21. Gas sparger
Fig. 1. Schematic representation of experimental apparatus.
to a motor was used. According to the experimental
requirements the mechanical mixer was substituted for a
magnetic stirrer. In cases where a magnetic stirrer was
used the heater controlled the temperature.
Before the beginning of any experiment SO2 (aq) was
prepared using the following method. Nitrogen gas was
passed into a cylindrical reactor (600 cm3) containing
deionized water through a gas sparger at the maximum
flow rate for about 30 min to remove dissolved oxygen.
The water was then cooled to 5 °C and SO2 gas was
passed through it for a desired time period. The
concentration of the resulting solution, SO2 (aq), was
measured using the IC, ion chromatograph. Usually
after 90 min of passing SO2 gas at 700 cm3/min the
concentration attained was 1.2 M.
N2 gas was flowed through the system throughout the
duration of leaching at 50 cm3/min to maintain an inert
atmosphere. A measured quantity of the aqueous SO2
was poured into the reactor and the glass reactor placed
into the water bath. The heater was turned on and the
temperature of the solution observed. The mechanical
mixer was set at 600 rpm. SO2 gas flow was then turned
on and set at 700 cm3/min. The flow rate of N2 and SO2
was monitored with the help of calibrated flow meters.
Depending on the required solids loading, slag of a
particular particle size was measured into the reactor
after the solution had reached the desired temperature
level. The mechanical mixer was then started. At
specific intervals, samples were collected and stored in
plastic vials for metal analysis using the ICP. The
sulphite concentration was measured every half hour
during the run. At the end of the dissolution the leach
solution was decanted into a second similar reactor. The
solution was stirred continuously with a magnetic stirrer.
Next 2 M NaOH was injected slowly into the solution
through the Teflon tube and the pH of the solution was
monitored with the help of a pH/ORP probe. At specific
time intervals samples were collected from the reactor
and stored for metal analysis. The precipitate that
formed was filtered, washed and dried for XRD
analysis.
3. Thermodynamic modeling
3.1. Theoretical background
The properties of species in aqueous-phase thermodynamics is generally represented as:
O
E
P¯ i ¼ P¯ i þ P¯ i
ð1Þ
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
where, P¯ i = any partial molal thermodynamic property,
The superscripts, O and E refers to standard state and
excess properties, respectively. The excess term is
directly related to the activity.
Various models have been proposed to estimate the
thermodynamic properties of aqueous species at different temperatures and pressures. Among them, the
Helgeson–Kirkham–Flower (HKF) model (Shock and
Helgeson, 1988) has gained popularity for its accuracy
and availability of data for the parameters of the
proposed equation. OLI Systems (Rafal et al., 2003)
has incorporated this model into its software. However,
for many aqueous reactions there is a lack of
experimental data to allow HKF parameters to be
included in the original databases. The simplest
equation for estimating equilibrium constant is the
Van't Hoff's equation.
Different methods have been developed over the
years to determine activity coefficients. A very useful
method is the Bromley model. The Bromley–Zemaitis
model including the extended terms is (Bromley, 1973):
pffiffi
pffiffi
Ajzþ z− j I ð0:06 þ 0:6BÞjzþ z− j I
p
ffiffi
loggF ¼ −
þ
2
1þ I
1:5
I
1þ
jzþ z− j
þ BI þ CI 2 þ DT 3
ð2Þ
where, γ± = mean molal activity coefficient of an
electrolyte,
A
I
z+, z−
B, C, D
Debye–Huckel constant
Ionic strength (molal)
Charge of cation and anion, respectively
Interaction parameters which depend on temperature only.
Bromley developed a number of individual cation–
anion interaction parameters at 25 °C. Another approach
133
to derive interaction parameters is the model substance
approach (Rafal et al., 1994). In this approach all
interactions involving cations and anions of charge +1
and − 1, respectively are assumed to be equal to that of
the model substance, usually taken as NaCl. OLI applies
the framework of Bromley, Zemaitis, Pitzer, and
Debye–Huckel, and others for the determination of
activity coefficients.
3.2. Thermodynamic data acquisition
The species relevant to the slag–SO2(aq) system has
been listed in Table 2. In this work various thermodynamic data sources have been consulted to obtain a valid
set of data. The ratio of Co to Ni to Fe in the slag was
taken to be 0.13 : 0.25 : 35 (Gbor, 2003). Co was
assumed to exist as oxide in the slag, while 50% of
the Ni was assumed to exist as oxide, with the rest being
sulphide. Cu was not included in the model since it
precipitates either as metallic Cu or Chevreul's salt
(CuIISO3CuI2SO3·2H2O) in the presence of SO2 only.
To conduct modeling by applying OLI accurately, the
fundamental thermodynamic data required for any
species are: Gibbs' free energy of formation (ΔGfo),
enthalpy of formation (ΔHfo), reference state entropy
(So) and the equilibrium constant's dependence on
temperature. The sections below discuss the estimation
of data that was required for species absent in the
database.
3.2.1. Iron species
All the above Fe species were available in the OLI
databank, except, FeSO3o, FeHSO3+, FeSO3·3H2O(s).
For these species in solution, data could not be found in
literature. Only ΔGfo of FeSO3·3H2O was available in
literature. ΔGfo of FeSO3o and ΔHfo for all the three
species were estimated. The estimated values are shown
in Table 3.
Table 2
List of possible species in the slag–SO2 system
Ions
+
H
OH−
SO2−
3
HSO−3
S2O2−
5
H3SiO−4
H2SiO2−
4
2+
Fe
FeOH+,
Fe(OH)−3
Fe(OH)2−
4
FeHSO+3
2+
Co
CoOH+
Co(OH)−3
CoHSO+3
Co(OH)2−
4
2+
Ni
NiOH+
Ni(OH)−3
Ni(OH)2−
4
NiHSO+3
Dissolved molecules
Solids
Fe(OH)o2
FeSOo3
Co(OH)o2
CoSOo3
Ni(OH)o2
NiSOo3
Fe2SiO4
Fe(OH)2
FeSO3·3H2O
SiO2
CoO
Co(OH)2
CoSO3·5H2O
NiO
NiS
Ni(OH)2
NiSO3·5H2O
SO2
SiO2
134
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
Table 3
Thermodynamic data for Fe–S(IV) compounds estimated or found in
literature
Name
ΔGo298.15K
(kJ/mol)
ΔHo298.15K
(kJ/mol)
So298.15K
(J/mol. K)
FeSOo3
FeHSO+3
FeSO3·3H2O(s)
− 585.5a
− 615.8a
− 1297b
− 727.6a
− 667.4a
− 1552.0a
−109.5c
194c
211.6c
Estimated, bLinkson (1982), cCalculated from ΔGo = ΔHo − TΔSo.
a
The data were estimated using an approach involving
the identification of relationships between thermodynamic data of similar materials. It was observed that a
relation exists between log K of Fe 3+ and Fe 2+
complexes with different ligands. A plot of log K for
Fe3+ and Fe2+ complexes of 5 inorganic complexes that
could be obtained (3 OH−, Cl− and SO42− , complexes
(Kotrly and Sucha, 1985; Dean, 1999)) is shown in Fig.
2a. Interestingly, a good correlation was observed
between these. This correlation was used to estimate
ΔGfo values for Fe2+–SO32− and Fe2+–HSO3− complexes, since the corresponding values for the Fe3+
complexes are known (Brandt and van Eldik, 1995;
Gbor, 2003). A similar plot was made for organic
ligands (Dean, 1999) and interestingly, a fairly good
correlation was also observed (Fig. 2b).
Berlung et al. (1993) and Fronaeus et al. (1998),
suggested the formation of MnHSO3+ complex from
Mn2+ and HSO3− from their kinetic studies. Using
additional information from Connick and Zhang (1996)
gives a log K for MnHSO3+ formation to be 1.78, or
probably less. This value is about 0.6 times that of
MnSO3 (Roy et al., 1991). Interestingly, the estimated
stability constant for FeHSO3+ is also about 0.5 times
that of FeSO3o.
(a)
The values of ΔHfo for FeSO3o , FeHSO3+ and
FeSO3·3H2O(s) were also estimated using a similar
approach as before. A correlation was observed to exist
between ΔHfo of aqueous complexes and solids of
sulphate and sulphite compounds. Fig. 3 shows such a
correlation for 12 complexes or salts obtained from
thermodynamic handbooks (Bard et al., 1985; Barin,
1995; Dean, 1999). Since the ΔHfo of FeSO4o and
FeHSO4+ are known (Fillippou et al., 1995), those of
FeSO3o and FeHSO3+ were estimated using the correlation developed. The ΔHfo of formation of FeSO3·3H2O
(s) was estimated using the correlation developed and
the ΔHfo for FeSO4·3H2O(s), which was obtained by
interpolation from the ΔHfo of FeSO4(s), FeSO4·H2O(s)
and FeSO4·7H2O(s) (Bard et al., 1985).
3.2.2. Cobalt and nickel species
The cobalt species that are not present in OLI
database are, CoSO3o, CoHSO3+, CoSO3·5H2O. Among
these only ΔGfo of CoSO3·5H2O and log K for CoSO3o
are available. The other thermodynamic properties were
estimated (See Table 4).
Log K of CoHSO3+ was assumed to be also about 0.5
times that of CoSO3o, following the observations made
on the stability constant of MnHSO3+ /MnSO3o and
FeHSO3+/FeSO3o complexes. This was used to calculate
ΔGfo of CoHSO3+. ΔHfo of CoSO3o was calculated using
ΔHfo of CoSO4o (Dean, 1999) and the relationship shown
in Fig. 3. The ΔHfo of CoSO3·5H2O(s) was also
estimated using the correlation shown in Fig. 3 and
the ΔHfo of CoSO4·5H2O(s) which was interpolated
from that of CoSO4(s) and CoSO4·7H2O (Dean, 1999).
No data was found for ΔHfo of CoHSO4+ so another
approach was used to estimate those values. A
correlation was found between ΔHfo of aqueous
(b)
25
y = 0.3009x + 0.632
8
logK(Iron (II)complex)
logK(Iron (II)complex)
10
R2 = 0.9901
6
4
2
inorganic ligands
y = 0.6593x - 2.2697
20
R2 = 0.8200
15
10
5
organic ligands
0
0
0
10
20
30
logK(Iron(III) complex)
40
0
10
20
30
40
logK(Iron(III) complex)
Fig. 2. (a) Log K of iron (II) complexes versus iron (III) complexes of inorganic ligands (3 OH−, Cl− and SO2−
4 complexes) and (b) same plot for 15
organic ligands.
3000
-Enthalpy of formation of
bisulphite/bisulphate [kJ/mol]
-Enthalpy of formation of sulphite
[kJ/mol]
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
y = 0.9937x - 264.39
R2 = 0.9985
2500
2000
1500
1000
500
0
0
1000
2000
3000
4000
-Enthalphy of formation of sulphate [kJ/mol]
Fig. 3. Enthalpy of formation of sulphite versus sulphate complexes or
salts of various metals. A total of 12 data points were obtained for
sulphite and sulphate complexes or salts of Ca, K, Cs, Mg, Li, Ag, and
Na.
metal–sulphate/metal–sulphite complexes and the
corresponding metal–bisulphate/metal–bisulphite complex (Fig. 4). Since the ΔHfo of CoSO3o has already been
determined, that for CoHSO3+ was determined using that
of CoSO3o and the correlation developed.
The nickel species that are not present in OLI
database are, NiSO3o , NiHSO3+ , and NiSO3·6H2O.
Among these only ΔGfo of NiSO3·6H2O and logK for
NiSO3o are available (Table 4). The other thermodynamic properties were estimated in a manner similar to
that for cobalt species.
3.3. Simulation
The simulation was done using the Stream Analyser
module, the windows interface of OLI. First, a private
databank was created. The data bank included all the
species that were absent from the OLI public databanks.
The private databank was then imported into the Stream
Analyser module. A large number of Bromley parameters are included in OLI's database. The Bromely's
Table 4
Thermodynamic data for Co–S(IV) compounds estimated or found in
literature
Name
ΔGo298.15K
(kJ/mol)
ΔHo298.15K
(kJ/mol)
So298.15K
(J/mol. K)
CoSOo3
CoHSO+3
CoSO3·5H2O(s)
NiSOo3
NiHSO+3
NiSO3·6H2O(s)
− 558.2a
− 590.3b
−1740.5c
− 548.2a
− 581.0b
−1970.7c
− 696.8b
− 639.3b
− 2102.9b
− 692.7b
− 635.1b
− 2394.59b
94.7d
205.9d
320.6d
− 114d
189d
347d
Calculated from log K (Roy et al., 1991), bEstimated, cLinkson
(1982), dCalculated from ΔGo = ΔHo − TΔSo.
a
135
1000
950
900
y = 1.025x - 74.938
R2 = 0.9923
850
800
750
700
650
600
650
750
850
950
1050
-Enthalpy of formation of
sulphite/sulphate [kJ/mol]
Fig. 4. Enthalpy of formation of bisulphite/bisulphate versus
enthalpy of formation of sulphite/sulphate. Data for Fe2+/Fe3+–SO2−
4 /
HSO−4 complexes were taken from Fillippou et al. (1995). Data for
−
Fe2+–SO2−
3 /HSO3 complexes were taken from Table 1.
parameters that were not present were automatically
generated by OLI, and were based on the model
substance approach. For temperature extrapolation,
van't Hoff's equation was used. Detailed OLI methodology can be found in Rafal et al. (1994).
The precipitation point of fayalite was used for the
simulations, unless otherwise stated. This is equivalent
to adding slag to SO2(aq) solutions, until fayalite starts
to precipitate. Since the output from Stream Analyser is
in moles of substances, all the output concentrations
were converted to molal units, using the mass of water
present at equilibrium.
4. Results and discussion
This section first discusses the results and predictions
obtained from the thermodynamic simulation. It then
focuses on experimental results.
4.1. Modeling results
4.1.1. Speciation of S(IV) in solution
The speciation of S(IV) was carried out using a
solution containing one molal of H2SO3. The pH was
varied using HNO3 and NaOH. The results are shown in
Fig. 5.
The distribution of S(IV) species is similar to what is
normally reported in literature (Brandt and van Eldik,
1995), indicating that the simulation is reliable. The
region of dominance of different S(IV) species is
important since metals form complexes with different
sulphur (IV) species and the stability of these
complexes varies with the type of S(IV) forming the
complex.
136
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
1
1.0
0.8
Concentration (molal)
Concentration, molal
0.9
0.7
0.6
SO2(aq)
0.5
HSO3-1
0.4
SO3-2
0.3
S2O5-2
0.2
0
0
2
4
6
8
10
FeT2+
o
FeSO3
0.8
ST of FeSO3.3H2O
0.8
0.6
0.6
0.4
0.4
0.2
0.2
0.0
0.5
1.0
0.5
1.0
1.5
2.0
1.5
0.0
2.0
Fig. 7. Concentration of various iron species in solution at different
total concentration of S(IV). T = 25 °C.
species in solution is shown in Fig. 7. The main species
that controlled the solubility under those conditions was
FeSO3o. The other species, which were present in
significant amounts, were FeHSO3+ and Fe2+.
The simulation was repeated but with Co and Ni
present in the fayalite, in proportions similar to the
amount of these metals present in slag, as mentioned
earlier. The amount of slag supplied was similar to that
observed from the precipitation point simulation when
fayalite alone was used. This did not cause any
significant change in the solubility of fayalite, as the
percentages of Co and Ni in the slag are small. However,
there was a small drop in solubility of fayalite, as the Co
and Ni species consumed some of the H+ and S(IV)
species in solution.
Fig. 8 shows the speciation of the Co species. A
similar distribution was found for Ni. The speciation
followed a similar trend as Fe, with the major species in
0.007
0.006
Concentration, molal
1.0
1.4
Scaling Tendency (ST) of FeSO3.3H2O
4.1.2. Effect of total concentration of S(IV) on solubility
of Fe2SiO4
The solubility of Fe2SiO4 (represented by total
dissolved iron) in different total concentrations of total
S(IV) is shown in Fig. 6. Concentration of total S(IV) in
the plots indicates the concentration of all sulphite
species in the system.
The solubility of Fe2SiO4 increased with increasing
concentration of total amount of S(IV). This is due to
increase in supply of hydrogen ions and S(IV) ions
which leads to solubilisation of the silicate. However, as
the concentration of total S(IV) was increased to 1.4
molal, Fe started to precipitate as FeSO3·3H2O (scaling
tendency = 1). The scaling tendency of a solid is the ratio
of the real-solution solubility product to the thermodynamic limit based on the thermodynamic equilibrium
constant. Precipitation occurs when the scaling tendency
for the solid is 1. The concentration of the major Fe
Concentration, molal
0.4
Concentration of total S(IV) (molal)
Fig. 5. Distribution of sulphur (IV) species at various pH. [H2SO3] =
1 m, T = 25 °C.
0.0
Fe+2
Fe(OH)+1
0.6
0.0
0.0
12
pH
1.0
FeHSO3+
0.8
0.2
0.1
1.2
FeSO3o
0.005
0.004
Total Co
CoSO3
CoHSO3+
Co2+
0.003
0.002
0.001
0.000
0
0.5
1
1.5
2
Concentration of total S(IV), molal
Concentration of total S(IV)
Fig. 6. Concentration of total dissolved Fe (Fe2+
T ) and scaling tendency
of FeSO3·3H2O(s) (ST) for different concentration of total S(IV).
T = 25 °C.
Fig. 8. Concentration of various Co species in solution at different total
concentration of S(IV), for solubility of fayalite containing Co and Ni.
The ratio of Co to Ni to Fe in the slag was taken to be 0.13 : 0.25 : 35.
Co was assumed to be oxide. T = 25 °C.
4.1.3. Effect of temperature
Fig. 9 shows the simulation of solubility of Fe2SiO4
at different temperatures and different concentrations of
H2SO3. The solubility of Fe2SiO4 generally decreased
with increase in temperature. It was observed that
precipitation of Fe as FeSO3·3H2O occurred from a
concentration of H2SO3 of 1.3 molal. The precipitation
occurred within a temperature range of 30 to 35 °C. This
range for precipitation increased as the concentration of
H2SO3 was increased. At 1.5 molal H2SO3, precipitation
of Fe as FeSO3·3H2O occurred from 25 to 40 °C.
Fig. 10 shows the distribution of the major Fe species
and scaling tendency for FeSO3·3H2O(s). The general
decrease in Fe2SiO4 solubility can be attributed to the
decrease in the concentration of FeSO3o with temperature. The decrease in FeSO3o concentration is due to the
decrease in its stability constant with temperature.
Though the stability constant for the formation of
FeHSO3+ (and also HSO3−) increased with temperature,
the increase was not high enough to compensate for the
1.3m H2SO3
1.5m H2SO3
1.0
0.8
0.6
1.2
1
0.8
0.6
0.4
0.2
0
10
30
40
30
40
50
60
70
80
60
70
80
1.4
1.2
1.2
1
1
0.8
0.8
0.6
0.6
0.4
0.4
0
20
50
Temperature (°C)
0.5m H2SO3
1.0m H2SO3
1.5m H2SO3
ST at 1.5m H2SO3
0.2
0.4
0.2
10
20
4.1.4. Effect of ionic strength
The solubility of Fe2SiO4 was studied at different
ionic strengths. NaNO3 was used to vary the ionic
strength of the solution (0 to 5 m) since NO3− does not
form strong complexes with metal ions (Gbor, 2003). It
was observed that the ionic strength did not have a
significant effect on the solubility of Fe2SiO4 (Fig. 11).
Concentration, molal
Concentration of FeT(molal)
1.2m H2SO3
[Fe]T
FeSO3
FeHSO3+
Fe+2
ST
1.4
decease in stability constant of FeSO3o . Also, the
stability constant for the formation of FeSO3·3H2O(s)
increased with temperature. This led to precipitation of
Fe as FeSO3·3H2O(s) when temperature was higher than
20 °C. However, the decrease in total dissolved Fe with
temperature and increase in tendency for S(IV) to form
HSO3− caused the tendency for FeSO3·3H2O(s) to
precipitate to diminish when temperature was higher
than 40 °C.
1.0m H2SO3
1.2
1.6
Fig. 10. Concentration of various Fe species, including total dissolved
Fe ([Fe]T) and scaling tendency of FeSO3·3H2O(s) (ST) at different
temperatures. Concentration of H2SO3 = 1.5 molal.
0.5m H2SO3
1.4
137
0
1
2
3
4
5
ST at 1.5m H2SO3
solution being the metal–SO32− complexes. Co and Ni
were completely soluble except the sulphide of Ni,
which remained practically insoluble under the simulation conditions. Since the Co and Ni species did not
cause any significant change in the solubility of the
fayalite, they were not included in further simulations,
unless mentioned.
The species controlling the concentration of Co2+
and Ni2+ in solution are CoSO3o and NiSO3o. These
species do not precipitate out as FeSO3o does. As a result
when the concentration of total S(IV) reaches 1.4 molal
the concentration of Co and Ni continues to rise while
the concentration of Fe becomes constant. This can be
seen by comparing Figs. 7 and 8.
Concentration (molal) and Scaling tendency (ST)
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
0.2
6
0
Ionic Strength, molal
Temperature (°C)
Fig. 9. Concentration of total dissolved Fe at different temperatures for
different concentrations of total S(IV).
Fig. 11. Total dissolved Fe and scaling tendency of FeSO3·3H2O(s) (at
1.5 m H2SO3), at different ionic strength for different concentrations of
H2SO3. T = 25 °C. Ionic strength was varied by adding NaNO3.
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
The solubility generally decreased slightly with increase
in ionic strength. However, the solubility was lower for
the case where Fe precipitated as FeSO3·3H2O (for
H2SO3 = 1.5 m and ionic strength less than 2 molal).
Though Fe precipitates as FeSO3·3H2O for a 1.5 molal
H2SO3 at 25 °C (Fig. 6), the precipitated sulphite redissolved when ionic strength was increased, indicating
that higher ionic strength is not favorable for precipitation of Fe as a sulphite in the slag–SO2(aq) system.
1
0
-1
Log [Fe]T
138
-2
Model
Exp
-3
-4
-5
-6
4.1.5. Effect of pH
The solubility of Fe2SiO4 at different pH values was
also simulated. HNO3 and NaOH were used to change
the pH of the system. Two moles of Fe2SiO4 were added
to a solution containing 0.5 m H2SO3 to conduct the
simulation. Below a pH of 5.5, all of the fayalite
dissolved. Beyond pH of 5.5, some fayalite remained in
solution, indicating that a solubility limit had been
reached. The results are shown in Fig. 12. The solubility
was high at low pH but decreased with pH. The fayalite
was practically insoluble beyond a pH of 7.5 ([Fe]T at
pH 8 = 0.0026 m). Similar results were obtained for
1.0 m H2SO3, where the total dissolved Fe at a pH of
8 was 0.0029 m. The solubility was enhanced at low pH
as more hydrogen ions were available to dissolve the
silicate phase. Under low pH conditions, the major Fe
species in solution were Fe2+ and FeHSO3+. However, as
the pH increased the percentage of Fe2+ and FeHSO3+
decreased while that of FeSO3o increased to a maximum
at pH of 6.5. Though more SO32− was in solution beyond
pH of 6.5, the solubility decreased as the tendency for
the silicate to dissolve was hampered by the absence of
hydrogen ions in solution.
Concentration (molal)
3.0
2.5
FeT
2.0
Fe+2
FeHSO3+
1.5
SO32-
0
0.5
1
1.5
2
2.5
3
3.5
4
Conc. of total S(IV) (molal)
Fig. 13. Comparison between model solubility of Fe (from Fe2SiO4 at
25 °C) and experimental values (from slag dissolution, under ambient
conditions). Experimental concentrations were in molar units.
4.2. Comparison between model and experimental
results
Fig. 13 shows the comparison between model
solubility of iron from slag and experimental data
(Hoque, 2004) from dissolution experiments of slag in
aqueous sulphur dioxide and under a continuous supply
of sulphur dioxide gas. The figure shows that experimental solubility values correlated well with the model
values.
5. Experimental results
Table 5 summarizes the results of five experiments.
The initial concentration of metals in solution,
predominantly iron, after dissolution determines the
pH at which the precipitation would begin. Higher
concentrations of ions led to precipitation at lower pH,
which is expected. Concentrations of Co, Ni were
proportional to that of Fe in solution since the solution
was obtained from leaching slag. The sulphite ion
concentration in the solution also correlated well with
that of Fe.
FeSO3o
Table 5
Influence of concentration on pH
1.0
Code
0.5
0.0
5
6
7
8
9
10
pH
Fig. 12. Concentration of various species, including [Fe]T at different
pH values. T = 25 °C.
A–1
A–2
A–3
A–4
A–5
Initial concentration of ions
(M)
Fe2+
Co2+
Ni2+
0.13
0.13
0.26
0.62
0.68
0.00059
0.00062
0.00108
0.0027
0.0029
0.00062
0.00064
0.00117
0.0032
0.0037
Initial SO2−
3
concentration
(M)
pH at which
precipitate
formed
0.74
0.75
1.74
2.15
2.19
5.22
5.06
4.2
3.8
3.5
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
Code Before [M / Fe]
After [M / Fe]
pH
0.0048
0.0047
0.0051
0.692
0.629
0.556
0.01
0.01
0.0063
0.026
0.025
0.018
4.22
4.41
1.25
5.06
4.2
3.5
% removal of metals
Fe
80
Co
Ni
Si
70
60
50
40
30
20
10
0
A-2
A-3
A-5
Fig. 14. Percent removal of Fe, Co and Ni.
ratio showed a slight increase while Co / Fe ratio
remained unchanged.
Without controlling the pH, immediately after the
precipitate formed (at pH ∼4) there was an increase in
the Co, Ni and Si / Fe ratio. After that though there was
a decrease in the ratio. Evidently the precipitation of Fe
is more sensitive to the pH change than the other ions.
With time the precipitation of Co, Ni and Si also
occurred resulting in a decrease in the ratio. In the next
4 h Ni / Fe ratio remained higher than Co / Fe ratio. Next
day the pH of the solution was 2. Ni / Fe ratio had
dropped to near its initial value while Co / Fe had
remained steady. The concentration of the metals in
solution had decreased except for silicon, whose
concentration remained constant. It appears that with
time more Ni precipitated out of the solution compared
to iron resulting in the decrease of Ni to Fe ratio. On the
contrary the ratio of Co to Fe remains fairly constant.
This indicates that the removal of Co is more influenced
by Fe than Ni. Si / Fe ratio remains unchanged
overnight.
0.7
160
0.6
140
120
0.5
100
0.4
Si
Ni
80
0.3
60
0.2
Co
0.1
Fe
40
20
0
0
0
[Co / Fe] [Ni / Fe] [Si / Fe] [Co / Fe] [Ni / Fe] [Si / Fe]
A–2 0.0046
A–3 0.0042
A–5 0.0043
90
Conc. of Fe and Si (mM)
Table 6
Metal to Fe ratio before and after precipitation
100
Conc. of Co and Ni (mM)
The overall concentration of the ions in solution
decreases when precipitation takes place. Since the
concentration of iron is 100 times more than that of
nickel and cobalt, iron would reach saturation point
earlier and hence precipitate out earlier. Table 6 shows
the change of ratio immediately the precipitate formed.
While the exact numbers vary, it can be concluded from
the data that there is an immediate enrichment of
solution for Co, Ni and Si.
The increase in metal to Fe ratio is higher for nickel,
nearly a five times increase while the ratio of Co to Fe
nearly doubles. The increase in Si / Fe ratio is very high.
This happens because Fe precipitates out but a very little
amount of Si precipitates out.
Fig. 14 shows the extent of removal of the metals
from solution. Fe removal is the highest followed by
cobalt and nickel. The removal of Co and Ni was not
expected since they are not saturated under the condition
of the precipitation experiments. However, the actual
removal of Co and Ni may be attributed to coprecipitation of Co and Ni with Fe.
Several researchers (Dutrizac and Dinardo, 1983;
Guise and Castro, 1996) have studied the influence of
coprecipitation. Coprecipitation is enhanced if the ionic
radii of the concerned metal ions are close and if the
precipitate formed is of amorphous nature. It has been
stated in literature (Kumar et al., 1993, 1990) that Co
could substitute Fe in goethite because of the close ionic
radii of the two ions Fe3+ (0.64 Å) and Co3+ (0.63 Å).
The ionic radii of Fe2+, Co2+, and Ni2+ are 0.74, 0.73,
and 0.69 Å, respectively. The influence of Fe on the
removal of the Co and Ni could be due to the close ionic
radii of the three ions. Fe, Ni and Co co-precipitation has
previously been studied with synthetic concentrated iron
(II) solution containing nickel and cobalt in sulphuric
acid at 90 °C (Koren et al., 1997). Iron was precipitated
out as goethite in two-step filtration process using H2O2
as the oxidant.
Experiments were conducted to determine what
happened if the pH was maintained at a specific level
or if the pH was not controlled. Maintaining the same
pH over a period of three hours did not significantly
affect the ratio of Co, Ni and Si to Fe. Ni / Fe and Si / Fe
139
1
2
3
4
5
6
7
8
pH
Fig. 15. Effect on concentration of cobalt, nickel, iron and silicon in
solution with gradual increase in pH. T = 25 °C.
140
P.K. Gbor et al. / Hydrometallurgy 81 (2006) 130–141
500
450
FS= FeSO3.3H2O
400
Counts/s
350
pH=5
FS
FS
FS
300
FS
250
200
150
100
50
0
10
15
20
25
30
35
40
Range
Fig. 16. X-ray diffraction patterns of the precipitate obtained at pH = 5
from experiment A-2.
When the pH of the solution, after precipitation, was
increased the concentration of the metals in solution
decreased. Fig. 15 shows the change of concentration of
the metals with changing pH. The data used for the
analysis was recorded after the pH had been maintained
for one hour. At lower pH, the removal of Fe and Co is
more sensitive to the change in pH. At higher pH, the
removal of Si becomes more sensitive. Most significant
removal of Si occurred when pH increased from 6 to 7.
Under acidic conditions Si remained in solution and did
not have much influence on the behavior of Co, Ni and
Fe. Only when the pH becomes alkaline the concentration of silicon drops sharply. At a pH of 8 the
concentration of metals in solution had reached below
detection limits.
Fig. 16 is an XRD analysis of the precipitate formed
at a pH of 5 from experiment A-2. It shows that the
major component of the precipitate is FeSO3·3H2O (as
suggested by the model). The form in which cobalt and
nickel precipitates out is not clear since XRD analysis of
the precipitate could not identify any clear cobalt or
nickel compounds. At pH values above 6, Fe, Co and Ni
dominate as hydroxides (Linkson, 1982).
6. Conclusions
The OLI Systems software was successfully used to
simulate the solubility of slag in aqueous sulphur
dioxide. The solubility of slag in SO2(aq) generally
increased with increase in the amount of SO2(aq)
supplied. In the solution saturated with fayalite the
species: FeSO3o, CoSO3o and NiSO3o were the main
metal-cation species. The secondary Fe phase that
precipitated in solution during the slag solubility study
was FeSO3·3H2O. The presence of small amounts of Co
and Ni did not have a significant effect on the solubility
of the fayalite. The solubility of slag decreased with
increase in temperature, ionic strength, and pH. Lower
temperatures and lower ionic strengths favored precipitation of FeSO3·3H2O.
Experimentally iron was removed from the solution
as ferrous sulphite precipitate confirming the model
predictions. With the precipitation of FeSO3·3H2O, Ni /
Fe ratio increased nearly four times while Co / Fe ratio
doubled. The increase in these ratios was lower than
expected due to the coprecipitation of these metals with
Fe, particularly Co. The pH at which the precipitate
forms is very important in determining the metal / Fe
ratio in the resulting solution. Lower pH is desirable in
maximizing the metal / Fe ratios while high pH should
be avoided to prevent the formation of amorphous silica.
Acknowledgements
We are grateful to Prof. Vladimiros G. Papangelakis
for providing us with the OLI Software and Dr Haixia
Liu for technical assistance. Financial assistance from
the Centre for Chemical Process Metallurgy (CCPM) at
the University of Toronto is greatly appreciated.
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