Monoxide: (CuO, FeO, FeO1.5, AlO1.5, CaO, MgO), Bragg-Williams Formalism (BWF), Olivine: [Fe2+, Ca2+, Mg2+, Zn2+]M2[Fe2+, Ca2+, Mg2+, Zn2+]M1SiO4, ...
Thermodynamic database for pyrometallurgical copper extraction Cu-Fe-O-S-Si + Al-Ca-Mg + (Pb-Zn-Sn-Cr-Sn-As-Bi-Ag-Au) Dr Denis Shishin, Dr Taufiq Hidayat, Dr Sergei Decterov, and Prof Evgueni Jak
PYROSEARCH centre
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Contents • Importance of large thermodynamic databases for industry • Quality of the database: “Wide” and “Deep” • Integrated experimental and modelling research. Examples • Minor elements: Slag, matte, metal, gas • Example of implementation Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Industry-academic collaboration towards increase of process economic efficiency and environmental sustainability University side Global optimization toolboxes
Non-equilibria factors, User interface
Fully integrated experimental and theoretical modelling
Process optimization
Process simulation: kinetics
Thermodynamic software and databases
Experimental study
FactSage, ChemApp
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
Industry side Key performance indicators (KPI), $ to all process parameters
Process automation
Feedback systems, computer advisers
Process control
Increase throughput Complex concentrates By-product treatment Recovery Energy savings Flexibility
Measure temperature, composition, input and output
Professional education Thermodynamic: link between chemistry, phase equilibria and energy balance 3
Cu consortium: Open to join
Software support: CRCT (FactSage)
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Thermodynamic database
• “Wide” – Many elements, all phases, covers whole compositional range for major elements Slag: (Cu+1, Fe+2, Fe+3, Si+4, Al+3, Ca+2, Mg+2, Pb2+, Zn2+, Sn2+, Cr+2, Cr+3, Sb+3, As+3, Bi+3, Ag+1 , Au+1 )(O-2, S-2), Modified Quasichemical Formalism in Quadruplet Approximation Spinel: [Cu+1,
Fe+2, Fe+3, Al+3, Mg+2, Zn+2, Cr+2]tetr[Cu+1, Fe+2, Fe+3, Al+3, Ca+2, Mg+2, Cr+2 , Cr+3 , Zn+2, Vacancy0]2octO4, Compound Energy Formalism Liquid matte/metal: (CuI,
CuII, FeII, FeIII, PbII, ZnII, CrII, SnII, SbIII, AsIII,
BiIII, AgI, AuI, OII,SII), Modified Quasichemical Formalism in Pair Approximation Monoxide: (CuO, FeO, FeO1.5, AlO1.5, CaO, MgO), Bragg-Williams Formalism (BWF), Olivine: [Fe2+, Ca2+, Mg2+, Zn2+]M2[Fe2+, Ca2+, Mg2+, Zn2+]M1SiO4, CEF Melilite: [Ca2+, Pb2+]2[Fe2+, Fe3+, Al3+, Zn2+][Fe3+, Al3+, Si4+]2O7, CEF, Pyroxenes: [Fe2+, Ca2+, Mg2+]M2[Fe2+, Fe3+, Mg2+, Al3+]M1[Fe3+, Al3+, Si4+]BSiAO6, CEF Dicalcium silicates: (Ca2SiO4, Fe2SiO4, Mg2SiO4 , Pb2SiO4 , Zn2SiO4), BWF, Wollastonite: (CaSiO3, FeSiO3, MgSiO3 , ZnSiO3), BWF, Willemite: [Zn2+, Fe2+, Mg2+][Zn2+, Fe2+, Mg2+]SiO4, Corundum: (FeO1.5, AlO1.5), BWF , fcc and bcc solids alloys: (Fe, Cu, O, S, Pb, Zn, As, Sb), BWF Digenite-bornite: (Cu2S, FeS, PbS, ZnS, Vacancy2S), BWF
Ideal gas: >100 species, More solid sulfide and oxide solutions and compounds, etc.. Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Thermodynamic database
• “Deep” – all subsystems, all types of experimental data, consistency between phases Cu-Fe-O-S-Si + Al-Ca-Mg + (Pb-Zn-Sn-Cr-Sn-As-Bi-Ag-Au). Next: Ni, Se, Te, Pt, Pd Cu-Fe-O-S-Si
Cu-Fe-O-S Cu-Fe-S Cu-Fe
Cu-Fe-O-Si
Cu-Fe-O
Fe-O-S-Si
Cu-O-S
Fe-O-S
Fe-S
Cu-O
Cu-S
Published in a journal
Cu-O-S-Si Fe-O-Si Fe-O
Published in a thesis
Cu-Fe-S-Si
Cu-Fe-Si Si-O
Cu-O-Si Si-S
Submitted to a journal
Other recent publications Ca-Fe-O, Al-Fe-O, Ca-Fe-O-Si, Ca-Cu-Fe-O Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Thermodynamic database “Deep” – Experimental data: phase equilibria
P(O2)
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Thermodynamic database “Deep” – Experimental data: heat effects
Heat capacity cubic CuFe2O4 Heat of mixing between FeO and SiO2
Submitted to Journal Phase Equilbria and Diffusion
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Thermodynamic database “Deep” – activity data D. Shishin: "Development of a thermodynamic database for copper smelting and converting", Ph. D. thesis, Ecole Polytechnique of Montreal, 2013.
P(O2) at P(SO2) = 1 atm
P(S2) over liquid Cu-Fe-S
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Integrated experimental and modelling study
Using new data to improve the database
Assessment of existing literature data. Identifying the gaps
Experimental studies: gaps in low-order systems, new data in multicomponent
Preliminary database. Experimental planning
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Example of integrated modellingexperimental study: effect Fe/SiO2 Cu in slag
Spinel saturation
???
S in slag
SiO2 saturation
• The initial database created based on literature data • No data for slag/matte/spinel saturation • Predicted: Higher Cu and S at Spin
Slag, Matte, 1 atm, 1200 °C, SiO2 or Spin sat, P(SO2) = 0.16 atm, 40-80wt% Cu in matte
Fe/SiO2 in slag
Copied from Molten Seattle, USA, May 2016
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Example of integrated modellingexperimental study: effect Fe/SiO2 SiO2 sat
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
Spin sat
Slag, Matte, 1 atm, 1200 °C, SiO2 or Spin sat, P(SO2) = 0.25 atm, 40-80wt% Cu in matte
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Example: Cu-Fe-O-S-Si effect of T Slag, Matte, 1 atm, 1200, 1250, 1300 °C, SiO2 sat, P(SO2) = 0.25 atm, 40-80wt% Cu in matte
1300 1250
1200
1200 1250 1300
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Example: Cu-Fe-O-S-Si effect of T Slag, Matte, 1 atm, 1200, 1250, 1300 °C, SiO2 sat, P(SO2) = 0.25 atm, 40-80wt% Cu in matte
1300 1250 1200
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Minor elements Cu-Fe-O-S-Si + Al-Ca-Mg + (Pb-Zn-Sn-Cr-Sn-As-Bi-Ag-Au) Slag, Metal, 1 atm, 1200 °C, SiO2 or Spin sat, ME Henrian
Slag/metal
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
Slag, Matte, 1 atm, 1200 °C, SiO2 sat, P(SO2) = 0.25 atm, 40-80wt% Cu in matte Slag/matte ME Henrian 15
Minor elements Cu-Fe-O-S-Si + Al-Ca-Mg + (Pb-Zn-Sn-Cr-Sn-As-Bi-Ag-Au) Matte/metal
Slag, Matte, 1 atm, 1200 °C, SiO2 sat, Cu metal 40-80wt% Cu in matte ME Henrian Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
Slag/metal
Slag/matte
Laser ablation ICP MS
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Gas phase: issues Slag, Matte, 1 atm, 1200 °C, SiO2 sat, P(SO2) = 0.25 atm, 40-80wt% Cu in matte ME Henrian (0.02 mole %) • • • •
Most fundamental thermodynamic data are for high molecular species In copper production – low molecular species Cp, S – statistical thermodynamics + quantum methods (revision needed) ∆Hf – Knudsen cell mass spectrometry. Not accurate enough!
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Thermodynamic calculation for Isasmelt Air, Fuel furnace Offgas Feed Lance Refractory
Frozen slag coating
-
Partitioning of major and minor elements between phases Energy balance Liquidus calculation Search of process parameters to meet targets Possible linking to converting and refining calculation to monitor full process from concentrate to anode copper Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
Stirred bath
Tap hole
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Multi-target, multi-parameter calculations
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Calculation results Isasmelt by Fountain et al. 1991 Plant assay [53]
Nagamori (1994) [54]
Base case
Case 1
This study
Case 2
Case 3
Case 4
High vol%O2 20 24.7 1.45 1.29 0.82 0.10 7173 50 7125 21
Poor concentrate 20 20.0 1.76 1.44 1.54 0.10 21115 24.7 7125 21
High temperatu 2 24 1.3 1.2 1.8 0.1 2134 24 712 2
Concentrate Cu in conc. SiO2 flux CaCO3 flux Coal Oil Lance vol% O2 Ingress air vol% O2
[t/hr] [wt%] [t/hr] [t/hr] [t/hr] [t/hr] [Nm3/hr] [vol%] [Nm3/hr] [vol%]
20 24.7 1.02 0.78 2.24 0.29 20232 24.7 no data no data
20 24.7 1.02 0.78 0.03 0.3 30800 25.9 not used not used
20 24.7 1.40 1.28 1.65 0.10 20232 24.7 7125 21
High matte grade 20 24.7 2.34 1.64 1.54 0.10 21670 24.7 7125 21
Slag Fe/SiO2 CaO/SiO2 Cu
[t/hr] [wt%/wt%] [wt%/wt%] [wt%]
no data
8.60 not reported not reported not reported
8.99 1.16 0.23 0.4
11.33 1.16 0.23 0.4
9.03 1.16 0.23 0.4
10.07 1.16 0.23 0.4
8.9 1.1 0.2 0
Matte Matte grade Cu in matte
[t/hr] [wt%] [t/hr]
no data
9.68 51.3 4.97
10.24 51.3 5.25
8.74 60.0 5.24
10.24 51.3 5.25
9.19 51.3 4.71
10.2 51 5.2
Temprerature Heat loss
[°C] [MW]
1180±10 no data
1180 28.40%
1190 -3.0
1190 -3.0
1190 -3.0
1190 -3.0
122 -3
1.16 0.23 0.5
51.3
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Calculation results Isasmelt by Fountain et al. 1991 Plant assay [53]
Partitioning in gas, %
Partitioning in slag, %
Partitioning in matte, %
As Pb Zn Sb Bi Sn Ag Au
As Pb Zn Sb Bi Sn Ag Au
As Pb Zn Sb Bi Sn Ag Au
87.2 43.2 12.4 17.2 85.9 no data 3.8 -0.9
6.9 10.1 56.0 44.0 0.0 no data 0.7 1.0
5.9 46.0 31.6 38.1 14.1 no data
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
95.5 99.9
Nagamori (1994) [54]
Base case
Case 1
Case 2
Case 3
Case 4
This study
High matte grade
High vol%O2
Poor concentrate
High temperature
87.9 37.3 12.3 17.0 77.9 not reported not reported not reported
70.9 45.7 14.9 19.4 91.9 40.3 1.7 1.0
72.5 44.9 12.8 17.5 94.1 45.1 2.0 1.0
59.3 30.9 7.6 11.2 85.7 29.0 1.4 1.0
72.8 48.4 14.1 19.7 92.8 42.8 1.8 1.0
74.9 54.8 22.2 25.5 93.5 45.1 2.1 1.0
3.2 3.5 80.2 45.2 6.9 not reported not reported not reported
6.7 5.7 68.8 37.8 0.3 12.9 0.8 0.3
9.6 8.7 76.7 57.8 0.4 24.3 1.1 0.3
11.2 7.5 74.7 44.4 0.6 17.3 0.8 0.3
7.5 6.6 72.2 42.5 0.3 15.0 1.0 0.3
5.3 5.3 63.5 34.5 0.2 11.1 0.9 0.3
8.9 59.3 7.6 37.8 15.2 not reported not reported not reported
22.4 48.6 16.3 42.8 7.8 46.8 97.5 98.7
17.8 46.4 10.5 24.7 5.5 30.6 96.9 98.6
29.5 61.6 17.7 44.4 13.7 53.7 97.8 98.7
19.7 45.0 13.7 37.7 6.9 42.3 97.2 98.6
19.7 39.9 14.3 40.0 6.3 43.8 97.0 98.7
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Thank you for the attention! Join our consortia:
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Example: Cu-Fe-O-S-Si-(Al) effect of Al2O3 0 3 6 9
0 3 6 9
Slag, Matte, 1 atm, 1200 °C, SiO2 sat, P(SO2) = 0.25 atm, 40-80wt% Cu in matte 0, 3, 6, 9 wt%Al2O3 in slag
0 3 6 9
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Interaction of Cu and S in slag. Fe-O-S-Si system
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
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Cu - CuS - Cu3As
Extension of matte/metal to speiss o
2
1200 C, P=10 atm, As(liq) iso-activities
T = 1200 °C [1968Asa] cited in [1994Des] [1948Kle] [1966Ger] [1981Cho]
0.2
0 [a 0. 5 (As Me liq ) tal 0.6 ] or Sp 0.7 eis s( 0 L2 .8 )
0. 1
0.9
Cu3As
-1 .5
0.6
0. 4
0
0.5
0.3
L1 + L2
0.8
0.2
0.7
-2.5
0.4
Lo g1
0.3
-2.0
-1.
-3.0
Cu
0.1
0.9
0.8
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
0.7
0.6
0.5
0.4
mole fraction
0.3
0.2
0. 9
-3.5 -4.0
Matte (L1)
0.1
CuS 25
Cu-Fe-O-Si: Spinel vs Tridymite Cu2O - FeO - SiO2 - Cu
o
Cu/(Cu2O+FeO+SiO2) (mol/mol) = 1, 1250 C, 1 bar
Distribution coefficients of ME for fayalite slag–liquid copper equilibria at 1250 °C
Log10L
0 .6 0 .5 0 .3 0 .2
0.8
0.7
0.6
0.5
0.4
0.3
0 .1
mole fractions /(Cu 2O+FeO+SiO2)
Nov 13-16, 2016, MMIJ and JMIA, Kobe, Japan
0.2
0.1
As SiO₂ sat
-4 -5
üs
Slag + Cu(liq) + Spinel
W ) + (li q Cu 0 .9
Slag + Cu(liq)
0.9
Spinel sat
-3
g+
0 .8
4
Wüstite sat
-2 Wüstite sat
Sla
SiO2
Cu2O
3
) (li q Cu 0 .7
0 .6
el + Spin
2
Spinel sat
-1
g+
+ (li q)
1
0 Sla
0 .5
+ Cu
Slag + Cu(liq) + SiO2
Pb
SiO2 sat
1
2 SiO )+ (li q .4 Cu 0
0 .7
g+
0 .3 Slag
0 .4
2
Sla
0 .2
0 .8
0 .1
0 .9
SiO2
FeO
-11
-9 -7 Log10[P(O2), atm]
Slag + Cu(liq) + Spinel
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