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Modelling Cobalt Solvent Extraction using Aspen Custom Modeler
Jiří Jaromír Klemeš, Petar Sabev Varbanov and Peng Yen Liew (Editors) Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24 June 15-18, 2014, Budapest, Hungary. Copyright © 2014 Elsevier B.V. All rights reserved.
Modelling Cobalt Solvent Extraction using Aspen Custom Modeler Heather A. Evansa, Parisa A. Bahria*, Linh T.T. Vua, Keith R. Barnardb a
School of Engineering and Information Technology, Murdoch University, South Street, Murdoch 6150, Australia b CSIRO Process Science and Engineering, PO Box 7229 Karawara, WA 6152, Australia [email protected]
Abstract The cobalt solvent extraction system using Cyanex 272, a phosphinic acid based extractant, has been modelled using the Aspen Custom Modeler mathematical modelling software. The principle advantage of this method is that the model can easily be imported into Aspen Plus and run as part of an integrated flowsheet containing other unit operations. The cobalt solvent extraction circuit operates on a counter-current basis, with the barren organic entering the final stage and the aqueous feed entering at the first stage. Since the metal extraction efficiencies were dependent on the conditions of the outlet streams, a solver must be selected to simultaneously solve a set of algebraic nonlinear model equations. Initial sensitivity analysis for a single stage Aspen Custom Modeler model has shown that increasing pH or the organic to aqueous (O:A) ratio significantly increases individual metal extraction efficiencies. To achieve the ultimate aim of maximising cobalt extraction while minimising magnesium and nickel coextraction and reagent consumption, an economic objective function has been formulated within the optimisation problem to solve for the optimum pH setpoint and O:A ratio. The optimised single stage results indicate operating at pH 4.5 and O:A of 0.78 to achieve 95 % cobalt extraction, while limiting nickel extraction to <1% Keywords: Aspen Custom Modeler, Cobalt Solvent Extraction, modelling, Cyanex 272
1. Introduction Cobalt has a range of uses from colouring agents to alloys designed for enhanced wear resistance and batteries for use in electric and hybrid electric vehicles, mobile phones and other electronic devices (CDI, 2012). Cobalt is usually recovered as a by-product of other metal ore bodies, typically nickel and copper. One common method for recovering cobalt and other metals is using a hydrometallurgical process whereby the metal ore is dissolved into an aqueous solution via acid addition. Cobalt can then be recovered from the resulting mixed metal aqueous pregnant leach solution (PLS) via solvent extraction (SX) using Cyanex 272 containing the active component bis (2,4,4 trimethlylpentyl) phosphinic acid as the organic extractant (Bacon and Mihaylov, 2002). The use of SX for cobalt and other metal recovery was thoroughly discussed in a review of modern hydrometallurgical flowsheets (Sole, 2008). In recent years this system has been modelled by Cytec, the manufacturer of Cyanex 272 (Soderstrom et al., 2010). A simulation software package named MINCHEM used in copper SX, has recently been expanded to allow evaluation of more complex metal/ligand interactions, such as those pertaining to cobalt SX (Bourget et al., 2011). However, this is a standalone, in-house model not currently compatible with existing flowsheeting packages used by
506
H.A. Evans et al.
engineering companies. Currently, the client provides potential feed scenarios to Cytec who model the system and return the results to the client. The principle advantage of this current project is that the Aspen Custom Modeler (ACM) cobalt solvent extraction (CoSX) model can potentially be exported as a .msi package into Aspen Plus and run as part of an integrated flowsheet containing other unit operations. The CoSX system was studied experimentally to generate data for subsequent modelling work (Evans et al., 2008). Equilibrium constants (k) for cobalt, nickel and magnesium were previously calculated using least squares regression techniques, from experimentally determined pH extraction isotherms for a given set of operating conditions (Evans et al., 2012).These k values were then used in the modelling equations to predict the extraction extents of cobalt, nickel and magnesium under a range of conditions in order to determine the optimal set of conditions to maximise cobalt extraction whist minimising the co-extraction of the other metals.
2. Model development Like most commercial SX circuits (incluing cobalt SX), the CoSX model routinely operates on a counter-current basis, with the barren organic entering the final stage and the aqueous feed entering at the first stage. The input variables are the initial concentration of the extractant, metal tenors of the aqueous feed and organic feed, temperature, aqueous feed flow, organic to aqueous ratio (O:A) and pH setpoint. Fixed parameters include the constants A and B determined from prior experimental work, which are used to calculate the equilibrium constant for each metal. The model uses a series of mass balance equations to calculate the extraction extent for each metal and hence the tenors of the organic and aqueous streams leaving each stage for a given set of operating conditions. The model was initially designed as a single stage with three inlet streams (aqueous feed(PLS), barren organic (BOrg) and alkali (Alk) for pH control) and two outlet streams (aqueous raffinate (Raff) and loaded organic (LOrg)) as shown in Figure 1. The metal concentrations to two significant figures and flowrates are shown for the aqueous and organic phases with the addition of the uncomplexed extractant concentration [RH] shown at the bottom of the organic streams.
Co _ cm k g /m3 Mg _ cm k g /m3 N i_ cm k g /m 3 F m 3 /h r RH _ c k m o l/m 3
Figure 1. Single stage CoSX ACM model, using Cyanex 272 (0.59M RH) at 35 °C, pH 5.0.
Modelling Cobalt Solvent Extraction using Aspen Custom Modeler
507
Phosphinic acid extractant RH exists in the dimeric form (RH)2 in non-polar solutions such as kerosene. The extraction reactions for Co, Mg and Ni with the dimer are given in Eqs.(1) - (3), respectively (Manksi et al. 2002). The individual metal extraction efficiencies (XeffM) (where M = Co, Ni or Mg), are given by Eq.(4). ʹܥ ሺܽݍሻ ʹሺܴܪሻʹ ሺܱ݃ݎሻ ՞ ܥሺܴʹ ܪሻʹ
ሺ݃ݎሻ
ʹ݃ܯ ሺܽݍሻ ʹሺܴܪሻʹ ሺܱ݃ݎሻ ՞ ݃ܯሺܴʹ ܪሻʹ ܰ݅ʹ ሺܽݍሻ ͵ሺܴܪሻʹ ሺܱ݃ݎሻ ՞ ܴܰ݅ʹ ሺܴܪሻͶ
ʹܪ ሺܽݍሻ
(1)
ሺ݃ݎሻ
ʹܪ ሺܽݍሻ
(2)
ሺ݃ݎሻ
ʹܪ ሺܽݍሻ
(3)
Since the individual metal extraction efficiencies were dependent on the conditions of the outlet streams, specifically the available extractant concentration [RH] (in kmol/m3) following extraction (as expressed in Eq.(5))as well as the kM value and pH setpoint, a solver must be selected to simultaneously solve a set of algebraic nonlinear model equations. This is typically done using a mathematical modelling software such as ACM or MATLAB. ݂݂ܺ݁ெ ൌ
ಾ Ǥሾோுሿ ಾ Ǥሾோுሿ ାሾுሿమ
ሾܴܪሿ ൌ ሾܴܪሿூ െ
(4)
where z = 2 for Co, Mg and z= 3 for Ni
ோுሺ ାಾ ାಿ ሻ
(5)
ிೀೝ
In the above equations, (RH)nM is the amount of RH reacted in kmol/h during the extraction reaction for each metal, FOrg is the organic flowrate in m3/h and [RH]In is the initial concentration in kmol/m3 of extractant entering the extractor vessel. More complex models incorporating multiple stages have been built based on the principles used in the initial single stage model. The single stage model was first modified by the addition of a splitter and a mixer to allow for the recycle of the organic phase back to the mixer to reflect typical operating conditions to manage losses due to entrainment. However there is minimal variation to the unit extraction once equilibrium has been obtained. The next step was to add additional extraction units as shown schematically in Figure 2.
Alk
Alk
Alk
Alk
En-1
En
PLS
Raff E1
LOrg
E2
BOrg
Figure 2. Schematic of a CoSX model with n stages. The multi-stage counter-current system presents its own unique challenges due to the co-dependency of the metal extraction efficiency and the amount of available extractant in each stage.
508
H.A. Evans et al.
3. System optimisation An optimisation problem was set up for a single stage extraction model using a baseline set of conditions, namely 20 % Cyanex 272 in kerosene as the organic extractant and a PLS with flowrate of 300 m3/h containing 0.5 g/L cobalt, 5.0 g/L magnesium and 4.0 g/L nickel in a sulfate system at 35°C. The optimisation variables were the O:A ratio and the pH setpoint. The objective function was formulated using an economic model Eq.(6) based on the selling price (SP) of cobalt and an assumed penalty price (PP) for co-extracted magnesium and nickel, where ݉ represents the mass of metal extracted and reagent costs (RC) including extractant, kerosene, alkali, acid. Maximise
(6)
ܲ ݐ݂݅ݎൌ ܵܲ ݉ െ ܲܲெ ݉ெ െ ܲܲே ݉ே െ ܴܥ
Subject to: x The set of equality constraints represented by Eq.(4) and Eq.(5); x The set of inequality constraints including: o 0 ≤ XeffM≤1; o 4 ≤ pH setpoint ≤ 5.5; o 0 ≤ [RH]; and o 0.5 ≤ O:A ≤ 1.1
4. Results and Discussion The results for cobalt, magnesium and nickel extraction from the sensitivity analysis on O:A ratio and pH setpoint using the baseline single stage ACM model (20 % Cyanex 272 in kerosene as the organic extractant and a PLS with flowrate of 300 m3/h containing 0.5 g/L cobalt, 5.0 g/L magnesium and 4.0 g/L nickel in a sulfate system at 35 °C) are shown in Figures 3 and 4. Co
100
Metal Extraction %
80 60 Mg 40 20 0 1.5 5 1 4.8 Ni
4.6
0.5 4.4 OA ratio
0
4.2 pH
Figure 3. Effect of O:A ratio and pH setpoint for a single stage CoSX model, using 20 % v/v Cyanex 272 (0.59M RH) at 35 °C with a PLS of 300 m3/h containing 0.5 g/L Co, 5.0 g/L Mg and 4.0 g/L Ni.
Modelling Cobalt Solvent Extraction using Aspen Custom Modeler
509
100 90 Co O:A 0.6
Metal Extraction %
80
Co O:A 1.0
70
Mg O:A 0.6
60
Mg O:A 1.0 Ni O:A 0.6
50
Ni O:A 1.0 40 30 20 10 0
4.1
4.2
4.3
4.4
4.5
4.6
4.7
4.8
4.9
5.0
5.1
pH
Figure 4. Effect changing of O:A ratio from 0.6 to 1.0 on extraction results for various pH setpoints for a single stage CoSX model, using 20 % v/v Cyanex 272 (0.59M RH) at 35 °C.
These results show that while cobalt extraction is consistently high (83-99%) across the range of O:A and pH setpoints modelled, and nickel co-extraction is consistently <1 %, a better (more selective) separation between cobalt and magnesium can be achieved by lowering the pH and O:A ratio. This limits the magnesium extraction, while still achieving acceptable cobalt recoveries. Magnesium is a common impurity element in CoSX that can consume the active sites on Cyanex 272, limiting the availability of the reagent for cobalt extraction. Limiting the magnesium extraction has additional cost benefits as the amount of reagents used for pH control in the extraction and subsequent stripping of the loaded magnesium can be reduced. The sensitivity analysis is a first stage approach to determining the optimal operating conditions for this system. However this can be improved by using optimisation techniques. For instance, applying the optimisation problem in Eq.(6)suggests the optimum conditions for a single stage of CoSX under these base line conditions to be an O:A ratio of 0.78 and a pH setpoint of 4.5. This produces a raffinate grade of 0.025 g/L Co, 4.7 g/L Mg and 4.0 g/L Ni corresponding to extractions of 95 % Co, 6.4 % Mg and 0.14 % Ni. The cobalt metal price is currently ~USD 27,000 /t for 99.9 % Co. Depending on the end market of the cobalt product, certain impurities may be tolerated although penalties will be imposed for them. To determine if changing the cobalt price had any impact on the optimal operating conditions, the cobalt price was normalised to 1 and incrementally changed in the optimisation problem, while keeping the magnesium and nickel penalties and reagent costs constant. Initial results indicate that the pH setpoint is relatively independent of cobalt price with the setpoint only changing by < 0.2 pH units during a doubling of the price. The O:A ratio was more sensitive but the optimisation point stayed within the range 0.5 to 0.8.
510
H.A. Evans et al.
5. Future work If lower cobalt raffinate grades are required, it is suggested that multiple stages be employed to achieve a better separation of cobalt from the impurity elements. For example using multiple stages of counter-current extraction allows for higher extraction extents in the final stage, as lower tenor solutions are contacted with barren organic (i.e. more available RH) thereby increasing extraction efficiencies. In a multistage model, changing the pH profile across the extraction circuit can result in some scrubbing of the loaded magnesium by new cobalt entering the circuit. This needs to be addressed by the inclusion of additional equilibrium equations representing the exchange reaction between cobalt, magnesium and nickel complexes.
6. Conclusions Initial sensitivity analysis for a single stage ACM model has shown that increasing pH or the O:A ratio significantly increases individual metal extraction efficiencies. Using an optimisation economic function based on the cobalt price and penalty rates for impurities, the optimum operating conditions were determined to be an O:A 0.78 and pH setpoint of 4.5 to achieve 95 % cobalt extraction, while limiting magnesium coextraction to 6.4 % and nickel coextraction to <1 %.
Acknowledgement The authors would like to thank the Parker Centre for the initial project funding, CSIRO and the Minerals Down Under National Research Flagship for the provision of laboratory facilities and Murdoch University for ongoing support.
References G. Bacon, I. Mihaylov, 2002, Solvent extraction as an enabling technology in the nickel industry, ISEC 2002: International Solvent Extraction Conference, Johannesburg, South Africa, South African Institute of Mining and Metallurgy, 1-13. C. Bourget, M. Soderstrom, B. Jakovljevic, J. Morrison, 2011, Optimization of the design parameters of a Cyanex 272 circuit for recovery of nickel and cobalt, Solvent Extraction and Ion Exchange, 29,823-836. Cobalt Development Institute,, Accessed on 1/10/2013. H. A. Evans, P. A. Bahri, J. A. Rumball, K. R. Barnard, 2008, Modelling cobalt extraction with Cyanex 272, ISEC 2008: International Solvent Extraction Conference,Tucson, AZ, United States, Canadian Institute of Mining, Metallurgy and Petroleum, 459-466. H. A. Evans, L. T. T. Vu, P. A. Bahri, K. R. Barnard, 2012, Development of an integrated model for cobalt solvent extraction using Cyanex 272, Computer Aided Chemical Engineering, 31, 550-554. R. Manski, H.-J. Bart, A. Görge, M. Traving, J. Strube, W. Bäcker, 2002, Solvent extraction as an enabling technology in the nickel industry, ISEC 2002: International Solvent Extraction Conference, 161-166. M. Soderstrom, C. Bourget, B. Jakovljevic, T. Bednarski, 2010, Development of Process Modelling for Cyanex 272, ALTA Nickel-Cobalt 2010. K. C. Sole, 2008, Solvent Extraction in the Hydrometallurgical Processing and Purification of Metals : Process Design and Selected Applications, Solvent Extraction and Liquid Membranes Fundamentals and Applications in New Materials, CRC Press,USA.
Modelling Cobalt Solvent Extraction using Aspen Custom Modeler Heather A. Evansa, Parisa A. Bahria*, Linh T.T. Vua, Keith R. Barnardb a
School of Engineering and Information Technology, Murdoch University, South Street, Murdoch 6150, Australia b CSIRO Process Science and Engineering, PO Box 7229 Karawara, WA 6152, Australia [email protected]
Abstract The cobalt solvent extraction system using Cyanex 272, a phosphinic acid based extractant, has been modelled using the Aspen Custom Modeler mathematical modelling software. The principle advantage of this method is that the model can easily be imported into Aspen Plus and run as part of an integrated flowsheet containing other unit operations. The cobalt solvent extraction circuit operates on a counter-current basis, with the barren organic entering the final stage and the aqueous feed entering at the first stage. Since the metal extraction efficiencies were dependent on the conditions of the outlet streams, a solver must be selected to simultaneously solve a set of algebraic nonlinear model equations. Initial sensitivity analysis for a single stage Aspen Custom Modeler model has shown that increasing pH or the organic to aqueous (O:A) ratio significantly increases individual metal extraction efficiencies. To achieve the ultimate aim of maximising cobalt extraction while minimising magnesium and nickel coextraction and reagent consumption, an economic objective function has been formulated within the optimisation problem to solve for the optimum pH setpoint and O:A ratio. The optimised single stage results indicate operating at pH 4.5 and O:A of 0.78 to achieve 95 % cobalt extraction, while limiting nickel extraction to <1% Keywords: Aspen Custom Modeler, Cobalt Solvent Extraction, modelling, Cyanex 272
1. Introduction Cobalt has a range of uses from colouring agents to alloys designed for enhanced wear resistance and batteries for use in electric and hybrid electric vehicles, mobile phones and other electronic devices (CDI, 2012). Cobalt is usually recovered as a by-product of other metal ore bodies, typically nickel and copper. One common method for recovering cobalt and other metals is using a hydrometallurgical process whereby the metal ore is dissolved into an aqueous solution via acid addition. Cobalt can then be recovered from the resulting mixed metal aqueous pregnant leach solution (PLS) via solvent extraction (SX) using Cyanex 272 containing the active component bis (2,4,4 trimethlylpentyl) phosphinic acid as the organic extractant (Bacon and Mihaylov, 2002). The use of SX for cobalt and other metal recovery was thoroughly discussed in a review of modern hydrometallurgical flowsheets (Sole, 2008). In recent years this system has been modelled by Cytec, the manufacturer of Cyanex 272 (Soderstrom et al., 2010). A simulation software package named MINCHEM used in copper SX, has recently been expanded to allow evaluation of more complex metal/ligand interactions, such as those pertaining to cobalt SX (Bourget et al., 2011). However, this is a standalone, in-house model not currently compatible with existing flowsheeting packages used by
506
H.A. Evans et al.
engineering companies. Currently, the client provides potential feed scenarios to Cytec who model the system and return the results to the client. The principle advantage of this current project is that the Aspen Custom Modeler (ACM) cobalt solvent extraction (CoSX) model can potentially be exported as a .msi package into Aspen Plus and run as part of an integrated flowsheet containing other unit operations. The CoSX system was studied experimentally to generate data for subsequent modelling work (Evans et al., 2008). Equilibrium constants (k) for cobalt, nickel and magnesium were previously calculated using least squares regression techniques, from experimentally determined pH extraction isotherms for a given set of operating conditions (Evans et al., 2012).These k values were then used in the modelling equations to predict the extraction extents of cobalt, nickel and magnesium under a range of conditions in order to determine the optimal set of conditions to maximise cobalt extraction whist minimising the co-extraction of the other metals.
2. Model development Like most commercial SX circuits (incluing cobalt SX), the CoSX model routinely operates on a counter-current basis, with the barren organic entering the final stage and the aqueous feed entering at the first stage. The input variables are the initial concentration of the extractant, metal tenors of the aqueous feed and organic feed, temperature, aqueous feed flow, organic to aqueous ratio (O:A) and pH setpoint. Fixed parameters include the constants A and B determined from prior experimental work, which are used to calculate the equilibrium constant for each metal. The model uses a series of mass balance equations to calculate the extraction extent for each metal and hence the tenors of the organic and aqueous streams leaving each stage for a given set of operating conditions. The model was initially designed as a single stage with three inlet streams (aqueous feed(PLS), barren organic (BOrg) and alkali (Alk) for pH control) and two outlet streams (aqueous raffinate (Raff) and loaded organic (LOrg)) as shown in Figure 1. The metal concentrations to two significant figures and flowrates are shown for the aqueous and organic phases with the addition of the uncomplexed extractant concentration [RH] shown at the bottom of the organic streams.
Co _ cm k g /m3 Mg _ cm k g /m3 N i_ cm k g /m 3 F m 3 /h r RH _ c k m o l/m 3
Figure 1. Single stage CoSX ACM model, using Cyanex 272 (0.59M RH) at 35 °C, pH 5.0.
Modelling Cobalt Solvent Extraction using Aspen Custom Modeler
507
Phosphinic acid extractant RH exists in the dimeric form (RH)2 in non-polar solutions such as kerosene. The extraction reactions for Co, Mg and Ni with the dimer are given in Eqs.(1) - (3), respectively (Manksi et al. 2002). The individual metal extraction efficiencies (XeffM) (where M = Co, Ni or Mg), are given by Eq.(4). ʹܥ ሺܽݍሻ ʹሺܴܪሻʹ ሺܱ݃ݎሻ ՞ ܥሺܴʹ ܪሻʹ
ሺ݃ݎሻ
ʹ݃ܯ ሺܽݍሻ ʹሺܴܪሻʹ ሺܱ݃ݎሻ ՞ ݃ܯሺܴʹ ܪሻʹ ܰ݅ʹ ሺܽݍሻ ͵ሺܴܪሻʹ ሺܱ݃ݎሻ ՞ ܴܰ݅ʹ ሺܴܪሻͶ
ʹܪ ሺܽݍሻ
(1)
ሺ݃ݎሻ
ʹܪ ሺܽݍሻ
(2)
ሺ݃ݎሻ
ʹܪ ሺܽݍሻ
(3)
Since the individual metal extraction efficiencies were dependent on the conditions of the outlet streams, specifically the available extractant concentration [RH] (in kmol/m3) following extraction (as expressed in Eq.(5))as well as the kM value and pH setpoint, a solver must be selected to simultaneously solve a set of algebraic nonlinear model equations. This is typically done using a mathematical modelling software such as ACM or MATLAB. ݂݂ܺ݁ெ ൌ
ಾ Ǥሾோுሿ ಾ Ǥሾோுሿ ାሾுሿమ
ሾܴܪሿ ൌ ሾܴܪሿூ െ
(4)
where z = 2 for Co, Mg and z= 3 for Ni
ோுሺ ାಾ ାಿ ሻ
(5)
ிೀೝ
In the above equations, (RH)nM is the amount of RH reacted in kmol/h during the extraction reaction for each metal, FOrg is the organic flowrate in m3/h and [RH]In is the initial concentration in kmol/m3 of extractant entering the extractor vessel. More complex models incorporating multiple stages have been built based on the principles used in the initial single stage model. The single stage model was first modified by the addition of a splitter and a mixer to allow for the recycle of the organic phase back to the mixer to reflect typical operating conditions to manage losses due to entrainment. However there is minimal variation to the unit extraction once equilibrium has been obtained. The next step was to add additional extraction units as shown schematically in Figure 2.
Alk
Alk
Alk
Alk
En-1
En
PLS
Raff E1
LOrg
E2
BOrg
Figure 2. Schematic of a CoSX model with n stages. The multi-stage counter-current system presents its own unique challenges due to the co-dependency of the metal extraction efficiency and the amount of available extractant in each stage.
508
H.A. Evans et al.
3. System optimisation An optimisation problem was set up for a single stage extraction model using a baseline set of conditions, namely 20 % Cyanex 272 in kerosene as the organic extractant and a PLS with flowrate of 300 m3/h containing 0.5 g/L cobalt, 5.0 g/L magnesium and 4.0 g/L nickel in a sulfate system at 35°C. The optimisation variables were the O:A ratio and the pH setpoint. The objective function was formulated using an economic model Eq.(6) based on the selling price (SP) of cobalt and an assumed penalty price (PP) for co-extracted magnesium and nickel, where ݉ represents the mass of metal extracted and reagent costs (RC) including extractant, kerosene, alkali, acid. Maximise
(6)
ܲ ݐ݂݅ݎൌ ܵܲ ݉ െ ܲܲெ ݉ெ െ ܲܲே ݉ே െ ܴܥ
Subject to: x The set of equality constraints represented by Eq.(4) and Eq.(5); x The set of inequality constraints including: o 0 ≤ XeffM≤1; o 4 ≤ pH setpoint ≤ 5.5; o 0 ≤ [RH]; and o 0.5 ≤ O:A ≤ 1.1
4. Results and Discussion The results for cobalt, magnesium and nickel extraction from the sensitivity analysis on O:A ratio and pH setpoint using the baseline single stage ACM model (20 % Cyanex 272 in kerosene as the organic extractant and a PLS with flowrate of 300 m3/h containing 0.5 g/L cobalt, 5.0 g/L magnesium and 4.0 g/L nickel in a sulfate system at 35 °C) are shown in Figures 3 and 4. Co
100
Metal Extraction %
80 60 Mg 40 20 0 1.5 5 1 4.8 Ni
4.6
0.5 4.4 OA ratio
0
4.2 pH
Figure 3. Effect of O:A ratio and pH setpoint for a single stage CoSX model, using 20 % v/v Cyanex 272 (0.59M RH) at 35 °C with a PLS of 300 m3/h containing 0.5 g/L Co, 5.0 g/L Mg and 4.0 g/L Ni.
Modelling Cobalt Solvent Extraction using Aspen Custom Modeler
509
100 90 Co O:A 0.6
Metal Extraction %
80
Co O:A 1.0
70
Mg O:A 0.6
60
Mg O:A 1.0 Ni O:A 0.6
50
Ni O:A 1.0 40 30 20 10 0
4.1
4.2
4.3
4.4
4.5
4.6
4.7
4.8
4.9
5.0
5.1
pH
Figure 4. Effect changing of O:A ratio from 0.6 to 1.0 on extraction results for various pH setpoints for a single stage CoSX model, using 20 % v/v Cyanex 272 (0.59M RH) at 35 °C.
These results show that while cobalt extraction is consistently high (83-99%) across the range of O:A and pH setpoints modelled, and nickel co-extraction is consistently <1 %, a better (more selective) separation between cobalt and magnesium can be achieved by lowering the pH and O:A ratio. This limits the magnesium extraction, while still achieving acceptable cobalt recoveries. Magnesium is a common impurity element in CoSX that can consume the active sites on Cyanex 272, limiting the availability of the reagent for cobalt extraction. Limiting the magnesium extraction has additional cost benefits as the amount of reagents used for pH control in the extraction and subsequent stripping of the loaded magnesium can be reduced. The sensitivity analysis is a first stage approach to determining the optimal operating conditions for this system. However this can be improved by using optimisation techniques. For instance, applying the optimisation problem in Eq.(6)suggests the optimum conditions for a single stage of CoSX under these base line conditions to be an O:A ratio of 0.78 and a pH setpoint of 4.5. This produces a raffinate grade of 0.025 g/L Co, 4.7 g/L Mg and 4.0 g/L Ni corresponding to extractions of 95 % Co, 6.4 % Mg and 0.14 % Ni. The cobalt metal price is currently ~USD 27,000 /t for 99.9 % Co. Depending on the end market of the cobalt product, certain impurities may be tolerated although penalties will be imposed for them. To determine if changing the cobalt price had any impact on the optimal operating conditions, the cobalt price was normalised to 1 and incrementally changed in the optimisation problem, while keeping the magnesium and nickel penalties and reagent costs constant. Initial results indicate that the pH setpoint is relatively independent of cobalt price with the setpoint only changing by < 0.2 pH units during a doubling of the price. The O:A ratio was more sensitive but the optimisation point stayed within the range 0.5 to 0.8.
510
H.A. Evans et al.
5. Future work If lower cobalt raffinate grades are required, it is suggested that multiple stages be employed to achieve a better separation of cobalt from the impurity elements. For example using multiple stages of counter-current extraction allows for higher extraction extents in the final stage, as lower tenor solutions are contacted with barren organic (i.e. more available RH) thereby increasing extraction efficiencies. In a multistage model, changing the pH profile across the extraction circuit can result in some scrubbing of the loaded magnesium by new cobalt entering the circuit. This needs to be addressed by the inclusion of additional equilibrium equations representing the exchange reaction between cobalt, magnesium and nickel complexes.
6. Conclusions Initial sensitivity analysis for a single stage ACM model has shown that increasing pH or the O:A ratio significantly increases individual metal extraction efficiencies. Using an optimisation economic function based on the cobalt price and penalty rates for impurities, the optimum operating conditions were determined to be an O:A 0.78 and pH setpoint of 4.5 to achieve 95 % cobalt extraction, while limiting magnesium coextraction to 6.4 % and nickel coextraction to <1 %.
Acknowledgement The authors would like to thank the Parker Centre for the initial project funding, CSIRO and the Minerals Down Under National Research Flagship for the provision of laboratory facilities and Murdoch University for ongoing support.
References G. Bacon, I. Mihaylov, 2002, Solvent extraction as an enabling technology in the nickel industry, ISEC 2002: International Solvent Extraction Conference, Johannesburg, South Africa, South African Institute of Mining and Metallurgy, 1-13. C. Bourget, M. Soderstrom, B. Jakovljevic, J. Morrison, 2011, Optimization of the design parameters of a Cyanex 272 circuit for recovery of nickel and cobalt, Solvent Extraction and Ion Exchange, 29,823-836. Cobalt Development Institute,