Pressure Vessel Measurements and
Modelling of Metal Solubility in
Aqueous Processes
Vladimiros G. Papangelakis
Dept. of Chemical Engineering &
Applied Chemistry,
University of Toronto,
Canada
Reagents
Feed
Vent
Discharge
Outline





Acid concentration measurements
pH measurements
Chemical modeling
Examples
Conclusions
1
Aqueous Processing Hydrometallurgy
T = 260oC
H2SO4
Steam
CaCO3
Feed
AUTOCLAVE
PRESSURE LEACHING
NEUTRALIZATION
DISPOSAL
PURIFICATION
2
High temperature on-line acid sensor




Many industrial chemical processes are acid
driven:
 Produce adequate yields – Equilibria
 Reduce process times - Kinetics
 Often added in excess
Excess acid must be partially or completely
neutralized within the process:
 Cost of base addition (CaO – CaCO3)
 Waste management problem (CaSO4.2H2O)
Other factors:
 Excess acid detrimental to equipment
 Puts more impurities into solution
Monitoring solution acidity is crucial to process
control
3
Grotthuss Conduction


Hydrogen ion is more mobile than other ions
Moves by jumping on water molecules
4
Limiting equivalent conductivities of
different ions in water up to 250°C
Limiting Equavalent Conductivity
4
-1
2
-1
(10 *Ω m equiv. )
1000
+
H
800
2-
SO4
2+
Ba 2+
Ca 2+
Mg
600
400
-
HSO4
200
0
0
50
100
150
200
250
o
Temperature ( C )
5
Electrodeless Conductivity
6
7
Leach Temperature
250°C
Solids Loading
27%wt.
Acid/Ore Ratio
0.2
Divalent Metal Sulphates
0.01 to 0.17M
Trivalent Metal Sulphates
0.009 to 0.04M
Absolute Average Difference = 4.6%, S.D. = 3.0%
8
Leach Temperature
Solids Loading
Acid/Ore Ratio (pre-acidified to 0.2)
250°C
40%wt.
0.3
Divalent Metal Sulphates
0.22 to 0.27M
Trivalent Metal Sulphates
0.05 to 0.15M
Absolute Average Difference = 3.6%, S.D. = 0.9%
9
3Fe2(SO4)3 + 2NaOH + 10H2O = 2NaFe3(SO4)2(OH)6(s) + 5H2SO4
Leach Temperature
Solids Loading
Acid/Ore Ratio (pre-acidified to 0.2)
250°C
40%wt.
1/8 stoich. NaOH
Divalent Metal Sulphates
0.20 to 0.23M
Trivalent Metal Sulphates
0.06 to 0.002M
Absolute Average Difference = 1.5%, S.D. = 0.7%
10
High temperature pH measurements
11
The yttria-stabilized zirconia (YSZ) pH sensor



The YSZ pH sensor consists of an oxygen ion conducting
ZrO2 (9 wt% Y2O3) ceramic tube
The sensor can be represented as:
H2O, H+ | ZrO2(Y2O3) | HgO | Hg
The reactions that occur at the membrane interfaces can be
represented as:
External: Oo + 2H+ = Vo.. + H2O
Internal: Vo.. + HgO + 2e- = Oo + Hg
where:
Oo – oxygen ion in a normal anion site in the lattice
Vo.. – oxygen ion vacancy in the lattice
12
Potentials in the flow-through
electrochemical cell

Irreversible thermodynamic contributions:
 DfSTR – streaming potential (left - RE, right - YSZ)
 DfTD – thermal diffusion potential
 DfD – diffusion potential
 DfTE – thermoelectric potential
13
Calculation of the diffusion potential
(Henderson equation)
 i zi
B
A
(
m

m

i
i )
RT i zi
Df D  f B  f A  
ln
B
A
F   i zi (mi  mi )
i






B

z
m
 i i i
i
A

z
m
 i i i
i
(A) – acidic solution
(B) – reference electrode solution
(i) – ith ionic species
 – ionic conductivity, taken from OLI Systems software
z – valence
m – molality, taken from OLI Systems software
14
Leach solutions L1 and L2
3
T = 250oC
Sat. Mg & Al
Exp., Leach solution L1
Exp., Leach solution L2
2.5
Model, No Al
Model, Sat. Al
2
1.22
pH
2.43
4.86
7.29
1.5
9.72
12.2 g/L Mg
0.0
1
0.5
Mg
0
0
10
20
30
40
50
60
70
80
H2SO4, g/L
15
Diluted, acid-adjusted leach solutions D1 to D5
3
T = 250oC
Sat. Mg & Al
Exp., Solution D1
Exp., Solution D2
2.5
Exp., Solution D3
Exp., Solution D4
2
Exp., Solution D5
1.22
pH
2.43
4.86
7.29
1.5
9.72
12.2 g/L Mg
0.0
1
0.5
Model, No Al
Model, Sat. Al
Mg
0
0
10
20
30
40
50
60
70
80
H2SO4, g/L
16
Prediction of [H2SO4]25C to attain pHT=1 based on
[Mg2+]25C and [Ni2+]25C
100
pH(270 oC)=1 at 25 oC
90
80
H2SO4, g L-1
70
60 pH(250oC)=1 at 25oC
Ni saturation (270 oC) at 25 oC
50
o
o
Ni saturation (250 C) at 25 C
40
Mg saturation (270 oC) at 25 oC
30
Mg saturation (250 oC) at 25 oC
o
20
Limonite 250 C (this work)
Limonite 270 oC (Papangelakis et al., 2004)
o
Blend 250 C (this work)
o
Blend 270 C (Papangelakis et al., 2004)
10
0
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Pseudo-MgSO4 or -NiSO4, mol kg-1
17
Solid - Aqueous Equilibria
M z   nL  ML(nz  n )
Aqueous
solution
Precipitation
Leaching
REDOX Reactions
Solid
18
Simulating Concentrated Electrolyte Solutions
at High Temperatures: Challenges




Inadequate theory to account for the physics of
ionic interactions and structures
Inconsistent-incomplete thermodynamic
databases
Experimental data is hard to obtain due to
corrosion, and lack of in situ sensors
Weak mathematical framework, when it based
on the “infinite dilution” – “ideal solution”
hypothetical standard state
Extrapolation of already uncertain
thermodynamic data!
19
Mixed Solvent Electrolyte (MSE) Model
 Features



Electrolytes in organic or water or mixed organic + water
solvents from infinite dilution to pure electrolytes
Unit scale: mole fraction x
Reference state: Symmetrical reference state
 The activity coefficient expression
ln  i  ln  iLR  ln  iMR  ln  iSR
C
A
LR: Long Range electrostatic interactions between ions, PitzerDebye-Hückel expression is used
C
A
MR: Middle Range interactions involving charged ions, Ion-Ion,
Ion-Molecule
C
A
M1
M2
SR: Short Range interactions between all species, Ion-Ion, IonMolecule, Molecule-Molecule, UNIQUAC equation is used
M
22
MSE Middle Range Interaction Term
ln  iMR   xi x j Bij ( I x )
i
j
Bij ( I x )


   ni   xi x j
 2 xi Bik ( I x )
nk
i
 i
 i j
Bij : Middle range parameters, ionic strength dependent
Bii= Bjj=0,
Bij= Bji=0
Bij  bij  cij  exp(  I x  0.01)
bij= BMD0+BMD1T+BMD2/T
cij= CMD0+CMD1T+CMD2/T
23
Software

OLI Systems

An extensive databank of over 3,000 species

Advanced thermodynamic framework to calculate
thermodynamic properties like free energy, entropy,
enthalpy, heat capacity, pH, ionic strength, density,
conductivity, osmotic pressure etc.

Built-in data regression capabilities to obtain
thermodynamic model parameters based on
experimental data

Wide applicability for the aqueous phase:
-50<T<300 C, 0<P<1500 Bar, 0 < I < 30 molal
24
Sulphuric Acid Species at 25°C in the Whole Acid
Concentration Range
MSE results, 25 C
MSE results, 25 C
Clegg Exp data (1995)
Young Exp data (1959)
Young Exp data (1959)
Young Exp data (1959)
Walrafen Exp data, 2000
100
90
MSE results, 25 C
Clegg Exp data (1995)
Young Exp data (1959)
Young Exp data (1959)
Young Exp data (1959)
Walrafen Exp data, 2000
25 oC
80
HSO4-
Species%
70
60
50
SO42-
40
H2SO4(aq)
30
20
10
0
0.0
0.2
0.4
0.6
0.8
1.0
(xH2SO4 )1/2
Clegg S.L., Brimblecombe P., 1995. Journal of Chemical Engineering Data, 40, 43-64.
Walrafen G.E., Yang W.H., Chu Y.C., Hokmabadi M.S., 2000. Journal of Solution Chemistry, 29(10), 905-936.
T.F. Young, L.F. Maranville, H.M. Smith, The Structure of Electrolyte Solutions, 1959, p. 35.
25
MSE model prediction of sulphuric acid species
vs. temperature in H2SO4-NaCl-H2O system
100
Dickson et al. (1990) Exp data
[H2SO4]=0.002 molal
90
80
[NaCl]=0.098 molal
SO4
Species, %
70
2-
60
50
40
30
20
-
HSO4
10
0
25
50
75
100 125 150 175 200 225 250
o
Temperature, C
Dickson A.G., Wesolowski D.J., Palmer D.A., Mesmer R.E., 1990. Dissociation Constant of Bisulfate Ion in Aqueous Sodium
Chloride Solutions to 250°C. J. of Phys. Chemistry, 94, 7978-7985.
26
MSE model prediction for sulphuric acid species
vs. temperature at different acid concentrations
27
Anhydrite Solubility in PAL Solutions
vs. NiSO4 concentration from 150 to 200°C
0.016
Solid phase: CaSO4 (s)
[Al2(SO4)3]=0.005 M
CaSO4 solubility, molal
o
0.012
This work, 150 C
o
This work, 175 C
o
This work, 200 C
[H2SO4]=0.33 M
[MgSO4]=0.22 M
0.008
0.004
0.000
0.05
0.10
0.15
0.20
0.25
0.30
0.35
NiSO4, molal
28
Anhydrite Solubility in PAL Solutions
vs. H2SO4 concentration from 150 to 250°C
0.025
Solid phase: CaSO4 (s)
o
CaSO4 solubility, molal
0.020
0.015
This work, 150 C
o
This work, 175 C
o
This work, 200 C
o
This work, 250 C
[Al2(SO4)3]=0.005 M
[NiSO4]=0.06 M
[MgSO4]=0.23 M
0.010
0.005
0.000
0.20
0.25
0.30
0.35
0.40
0.45
H2SO4, molal
29
Prediction of anhydrite solubility in different
electrolyte solutions: Scaling potential
0.030
Solid: CaSO4 (s)
CaSO4 solubility, molal
0.025
0.020
In pure water
[H2SO4]=0.22 M
[H2SO4]=0.22 M, [NiSO4]=0.06 M
[H2SO4]=0.22 M, [MgSO4]=0.2 M
0.015
0.010
0.005
0.000
150
175
200
225
250
o
Temperature, C
30
Conclusions




New sensors have been developed for
stoichiometric acid and pH measurements as in
multicomponent systems at high temperatures
Application of thermodynamics is becoming an
essential tool in industrial process design and
development
OLI Systems offer the best available software for
chemical modelling of both low and high
temperature industrial processes
Proprietary databanks have been developed at
the UofT and are growing for applications in
hydrometallurgy
31
Acknowledgments
Anglo American plc
Barrick Gold Corporation
Norilsk Nickel
Sherritt International Corporation
Vale Inco Ltd.
32