The Optimum Electrolyte Parameters in the Application of High Current Density Silver Electroreﬁning

: Increasing silver production rate has been a challenge for the existing reﬁning facilities. The application of high current density (HCD) as one of the possible solutions to increase the process throughput is also expected to reduce both energy consumption and process inventory. From the recently-developed models of silver electroreﬁning, this study simulated the optimum electrolyte parameters to optimize the speciﬁc energy consumption (SEC) and the silver inventory in the electrolyte for an HCD application. It was found that by using [Cu 2 + ] in electrolyte, both objectives can be achieved. The suggested optimum composition range from this study was [Ag + ] 100–150 g / dm 3 , [HNO 3 ] 5 g / dm 3 , and [Cu 2 + ] 50–75 g / dm 3 . HCD application (1000 A / m 2 ) in these electrolyte conditions result in cell voltage of 2.7–3.2 V and SEC of 0.60–1.01 kWh / kg, with silver inventory in electrolyte of 26–39 kg silver for 100 kg per day basis. The corresponding ﬁgures for the conventional process were 1.5–2.8 V, 0.44–0.76 kWh / kg, and 15.54–194.25 kg, in respective order. These results show that, while HCD increases SEC by app. 30%, the improvement provides a signiﬁcant smaller footprint as a result of a more compact of process. Thus, applying HCD in silver electroreﬁning o ﬀ ers the best solution in increasing production capacity and process e ﬃ ciency.


Introduction
Silver is used in many applications such as coins, jewelry, medicine, dentistry, plating, electrical technology, chemical equipment, catalyst, and photography [1]. The recorded production of silver from 1950 to 2018 shows a linear trend with an increasing rate of approximately 300 tons of silver product per year as can be seen in Figure 1a [2]. In order to meet the increasing demand, increase in the existing capacity or higher kinetics of processing is required. Accordingly, developments in the existing silver electrorefining process were more focused on the increase of processing rate, reduction of metal inventory, and increase of metal recovery rate [3]. One of the developments was high current density (HCD), or the application of current density over 1000 A/m 2 silver electrorefining, which offers a logical solution for the increasing capacity demand. Started in 1980 in Sweden, this process development path has recorded 11 installations of HCD silver electrorefining worldwide until 2014 [4]. Furthermore, the reported-and published research and development of the process shows that recent investigations [4][5][6][7][8][9][10] were focused on the implementation of higher current density as shown by Figure 1b, making it the most renowned improvement in the recent years. Another distinct difference of the conventional and HCD process is the current density with conventional silver electrorefining current density is within the range of 200-800 A/m 2 as shown in Table 1 [1, [5][6][7][8][9]12] whereas the HCD current density targets to 1000 A/m 2 [4,5]. As shown in the same table, conventional cell voltage within the range of 1.5-2.8 V [1, 7,8] leads to specific energy consumption of 0.6-0.8 kWh/kg [11,12]. Meanwhile, HCD cell voltage is approximately 5 V [4] which equal to 1.27 kWh/kg. This higher energy consumption of the silver electrorefining process is another disadvantage of the application of HCD. * calculated from the pH information, and # was unit conversion from amps/sq feet.
At the current state of increasing industrial demand, improvement to the process throughput is getting more important than ever before. On the other hand, the conventional silver electrorefining process itself has a very wide range of operating parameters. Thus, optimization for the process is required to take into account both opportunity of improvements of increasing the process throughput and to have well-designed process parameters for an optimal process.
The disadvantages of high cell voltage and high energy consumption of the HCD application in comparison to the conventional process consequently raised a question of whether HCD could be adapted in the existing silver electrorefining to increase the productivity. The process integration Similar to the conventional electrorefining, HCD silver electrorefining uses cast anodes and AgNO 3 -HNO 3 electrolyte with the arrangement of Moebius cell [4]. Nevertheless, the processes difference in electrolyte parameters.
Another distinct difference of the conventional and HCD process is the current density with conventional silver electrorefining current density is within the range of 200-800 A/m 2 as shown in Table 1 [1, [5][6][7][8][9]12] whereas the HCD current density targets to 1000 A/m 2 [4,5]. As shown in the same table, conventional cell voltage within the range of 1. 5-2.8 V [1,7,8] leads to specific energy consumption of 0.6-0.8 kWh/kg [11,12]. Meanwhile, HCD cell voltage is approximately 5 V [4] which equal to 1.27 kWh/kg. This higher energy consumption of the silver electrorefining process is another disadvantage of the application of HCD. At the current state of increasing industrial demand, improvement to the process throughput is getting more important than ever before. On the other hand, the conventional silver electrorefining process itself has a very wide range of operating parameters. Thus, optimization for the process is required to take into account both opportunity of improvements of increasing the process throughput and to have well-designed process parameters for an optimal process. The disadvantages of high cell voltage and high energy consumption of the HCD application in comparison to the conventional process consequently raised a question of whether HCD could be adapted in the existing silver electrorefining to increase the productivity. The process integration probably has been the cause for the low implementation of HCD from the time it was introduced almost four decades ago. In this investigation, the decisive parameters for the HCD application are defined for the optimum silver electrorefining process based on the current industrial conditions.

Methods
Investigation on the applicability of HCD process to silver electrorefining is conducted through the simulation of the published models as shown by Figure 2. The models in consideration are regression models from the following publications: a.
Empirical model of electrolyte conductivity as a function of electrolyte concentrations and temperature [13]. b.
Silver dissolution as a function of electrolyte concentrations and temperature [14]. c.
Effect of Au content in anode due to anode passivation [15]. d.
probably has been the cause for the low implementation of HCD from the time it was introduced almost four decades ago. In this investigation, the decisive parameters for the HCD application are defined for the optimum silver electrorefining process based on the current industrial conditions.

Methods
Investigation on the applicability of HCD process to silver electrorefining is conducted through the simulation of the published models as shown by Figure 2. The models in consideration are regression models from the following publications: a. Empirical model of electrolyte conductivity as a function of electrolyte concentrations and temperature [13]. b. Silver dissolution as a function of electrolyte concentrations and temperature [14]. c. Effect of Au content in anode due to anode passivation [15]. d. Electrode overpotential [16]. All of the models were constructed with the range of parameters according to the existing industrial practices. Conductivity model was developed with a full factorial design of electrolyte concentrations ( Germany). Meanwhile, the models of silver dissolution and the effect of Au-to-anode passivation were developed from the series of anodic polarization of pure silver and Au-Ag binary alloys with known ranges of Au content. And finally, the electrode overpotential model was developed from galvanostatic measurements with pure silver as working electrode at a current density of 1000 A/m 2 . The tests were conducted at different concentrations and temperature of electrolyte. Statistical analysis the developed models has demonstrated that every model presented in [13][14][15][16] fulfils the requirements of a good model.

Effect of Cu
Kinetics modelling Anode passivation due to Au content in anodes [15] Electrode overpotential [16] High current density silver electrorefining [14] Anode and impurities (Au and Cu) Effect of Au Electrolyte conductivity modelling [13] Silver electrolyte properties Energy consumption, IR drop modelling [16] Figure 2. Method of the investigation on the aspects for the high current density (HCD) application (dashed box) is based on the anodic [14][15][16] and electrolytic [13,16] modelling.
With the strict policy of precious metal refineries, measurements using industrial electrolytes and anodes were not possible. Throughout the study, only a series of industrial tests was conducted in a precious metal refinery to validate the developed the conductivity model from previous study [13] in industrial electrolyte concentration shown in Table 2. The conductivity values measured and calculated by the model for the 20 samples taken at two temperatures of 25 °C and 40 °C. From the validation, additional models of conductivity were also developed and defined as validation (validation) and industrial (industrial) models. Validation model was developed from the concentration coefficients from the empirical model while the temperature coefficient was taken from the validation results. On the other hand, industrial model was independently developed only from the industrial measurements. The schematic of the conductivity modellings and their correlation are shown in Figure 3.  [14][15][16] and electrolytic [13,16] Germany). Meanwhile, the models of silver dissolution and the effect of Au-to-anode passivation were developed from the series of anodic polarization of pure silver and Au-Ag binary alloys with known ranges of Au content. And finally, the electrode overpotential model was developed from galvanostatic measurements with pure silver as working electrode at a current density of 1000 A/m 2 . The tests were conducted at different concentrations and temperature of electrolyte. Statistical analysis the developed models has demonstrated that every model presented in [13][14][15][16] fulfils the requirements of a good model.
With the strict policy of precious metal refineries, measurements using industrial electrolytes and anodes were not possible. Throughout the study, only a series of industrial tests was conducted in a precious metal refinery to validate the developed the conductivity model from previous study [13] in industrial electrolyte concentration shown in Table 2. The conductivity values measured and calculated by the model for the 20 samples taken at two temperatures of 25 • C and 40 • C. From the validation, additional models of conductivity were also developed and defined as validation (κ validation ) and industrial (κ industrial ) models. Validation model was developed from the concentration coefficients from the empirical model while the temperature coefficient was taken from the validation results. On the other hand, industrial model was independently developed only from the industrial measurements. The schematic of the conductivity modellings and their correlation are shown in Figure 3.   All of the developed models were also used as the base to study HCD application with particular attention paid to the cell voltage and specific energy consumption (SEC). Simulations and comparison of HCD and conventional process were conducted based on the electrolyte concentrations from literature. Finally, an optimum condition of HCD silver electrorefining was established in order to have both low energy consumption and low inventory of silver in the electrorefining process.

Theoretical Background
The evaluation of optimum parameters was designed mainly based on two calculated outcome of specific energy consumption (SEC) and silver inventory in the process.

Specific Energy Consumption
Theoretically, the main consumable of an electrorefining process is the electrical energy. With the electrical energy consumption (Econs) outlined in Equation (1), the SEC of a silver electrorefining process is defined as Equation (2) below, where Ecell is the cell voltage (V). With the data of the constants (n, F and MAg) and the current efficiency of conventional process of 92-95% [9,11] and HCD of 98-99% [4], the only variable left from Equation (2) is the cell voltage (Vcell). (2) Cell voltage is the sum of potentials from the process. Excluding the external voltage drops such as busbar or electrical contacts, cell voltage components in silver electrorefining process are voltage drop due to the conductivity of electrolyte, anode polarization with the effect of gold, and cathode polarization. Thus, the cell voltage can be written as Equation (3) =  + | | +  where ηa is the anodic overpotential, ηc is the cathodic, ηpass is the excess polarization due to anode passivation, and IR is the potential drop due to electrolyte resistivity. The effect of conductivity to the IR drop is shown in Equation (4).
where I is current (A), lek is the interelectrode distance (m), A is the surface area (m 2 ) and  is the All of the developed models were also used as the base to study HCD application with particular attention paid to the cell voltage and specific energy consumption (SEC). Simulations and comparison of HCD and conventional process were conducted based on the electrolyte concentrations from literature. Finally, an optimum condition of HCD silver electrorefining was established in order to have both low energy consumption and low inventory of silver in the electrorefining process.

Theoretical Background
The evaluation of optimum parameters was designed mainly based on two calculated outcome of specific energy consumption (SEC) and silver inventory in the process.

Specific Energy Consumption
Theoretically, the main consumable of an electrorefining process is the electrical energy. With the electrical energy consumption (E cons ) outlined in Equation (1), the SEC of a silver electrorefining process is defined as Equation (2) below, where E cell is the cell voltage (V). With the data of the constants (n, F and M Ag ) and the current efficiency of conventional process of 92-95% [9,11] and HCD of 98-99% [4], the only variable left from Equation (2) is the cell voltage (V cell ).
Cell voltage is the sum of potentials from the process. Excluding the external voltage drops such as busbar or electrical contacts, cell voltage components in silver electrorefining process are voltage drop due to the conductivity of electrolyte, anode polarization with the effect of gold, and cathode polarization. Thus, the cell voltage can be written as Equation (3) where η a is the anodic overpotential, η c is the cathodic, η pass is the excess polarization due to anode passivation, and IR is the potential drop due to electrolyte resistivity. The effect of conductivity to the IR drop is shown in Equation (4).
where I is current (A), l ek is the interelectrode distance (m), A is the surface area (m 2 ) and κ is the conductivity (S/m).

Silver Inventory
One of the economic aspects of the silver electrorefining besides the energy consumption is the silver inventory in the process. Silver inventory as the result of HCD can be calculated from the effect of increasing process throughput to the process footprint, in this case the volume of electrolyte. From the Faraday law of electrolysis in Equation (5), the production rate of a plant as function of the electrolyte volume shown in Equation (6) where j is the current density (A/m 2 ), A/V is the effective surface area of anode to electrolyte volume (m 2 /dm 3 ), M Ag is the molar mass of silver, n is the electron valence of silver, F is Faraday constant and V is the electrolyte volume (dm 3 ).

IR Rrop
Energy consumption in an electrorefining process is mainly due to the resistivity of the electrolyte. To estimate the IR drop in this system, an empirical conductivity model based on laboratory measurements shown in Equation (7) was developed and confirmed to be the accurate for the system when electrolyte properties are [Ag + ] of 40-150 g/dm 3 , [Cu 2+ ] of 0-80 g/dm 3 , [HNO 3 ] of 0-15 g/dm 3 and T of 25-45 • C [13] and unlike the other models, conductivity modelling of silver electrolyte had been conducted by previous study [17]. Thus, this model was statistically tested and compared to the previous model by Gordon and Davenport [17] and is proven to be a valid model and has better accuracy in comparison to the model of Gordon and Davenport [13].
In Equation (7) κ is the conductivity of electrolyte (mS/cm) and T is temperature ( • C) and concentrations are given as g/dm 3 .
Furthermore, validation of the model was conducted and according to the method in Figure 3, the developed validation and industrial models are shown in Equations (8) and (9) The accuracy of all models to the industrial measurement values are shown in Figure 4. Figure 4a-c show that the empirical model accurately predicts conductivities at lower temperature while at higher temperatures the model over calculates the electrolyte conductivity. Validation model accuracy which is as shown by Figure 4d-e has the improved prediction of conductivity values at higher temperature are closer to the measurements. On the other hand, the goodness of fit (R 2 ) of the model has become significantly lower as shown by Figure 4f. Finally, the industrial model has the best fit to the measurement values as can be seen in Figure 4g-i. While industrial model is the most representative model for industrial electrolyte, narrow range of the electrolyte concentration creates a challenge for the calculating conductivity of wider range electrolyte concentrations. All models in Equations (7)-(9) were included for further calculation in this study.
Metals 2020, 10, x FOR PEER REVIEW 6 of 13 a challenge for the calculating conductivity of wider range electrolyte concentrations. All models in Equations (7)- (9) were included for further calculation in this study. From the electrolyte concentrations in Table 2, with the exempt of [Ag + ], the impact of applying HCD calculated with the three models were simulated with the assumption of industrial current density of 420 A/m 2 and lek of 5 cm [11] as shown in Figure 5.   Table 2. From the Figure 5, increasing the existing industrial current density to 1000 A/m 2 increases the IR drop significantly from app. 1.6 V calculated by the empirical model to 2 V from the validation and industrial models. The increase accounts for more than 100% of the initial IR drop of the process. The Figure also demonstrates that high [Ag + ] is preferred in order to have lower increase of IR drop. Another potential factor is the effect of [Cu 2+ ] as it is shown to increase the electrolyte conductivity as shown by all of the models outlined in Equations (7) Table 2.
From the electrolyte concentrations in Table 2, with the exempt of [Ag + ], the impact of applying HCD calculated with the three models were simulated with the assumption of industrial current density of 420 A/m 2 and l ek of 5 cm [11] as shown in Figure 5. The simulation of IR drop increase as a function of [Ag + ] demonstrates the impact of HCD application in the range of [Ag + ] from 60-200 g/dm 3 .
From the Figure 5, increasing the existing industrial current density to 1000 A/m 2 increases the IR drop significantly from app. 1.6 V calculated by the empirical model to 2 V from the validation and industrial models. The increase accounts for more than 100% of the initial IR drop of the process. The Figure also demonstrates that high [Ag + ] is preferred in order to have lower increase of IR drop. Another potential factor is the effect of [Cu 2+ ] as it is shown to increase the electrolyte conductivity as shown by all of the models outlined in Equations (7)- (9). In a recent study, having [Cu 2+ ] in electrolyte was also encouraged as the study suggest electrolyte compositions of [Ag + ] > 60 g/dm 3 , [Cu 2+ ] < 60 g/dm 3 , and [HNO 3 ] < 7 g/dm 3 [18]. Thus, further simulation of the effect of [Ag + ] and [Cu 2+ ] is required to have an optimum condition of electrolyte for a minimum impact of HCD application due to the increase of IR drop. Calculation of the conventional process IR drop by using the Equation (4) from the data in Table  1 shows IR drop values within the range of 0.8-2.3 V which equal to 55-82% of the total cell potential. As it can be expected, HCD process results in higher cell potential thus the role of electrolyte conductivity is significant. With the positive effect of [Cu 2+ ] to the conductivity of electrolyte, it is important to take a study of the possibility of having [Cu 2+ ] in smaller ratios of [Cu 2+ ]/[Ag + ] to achieve both optimum conductivity and to avoid the co-deposition of Cu on the cathode. A comparison of the [Cu 2+ ]/[Ag + ] levels from previous studies is shown in Table 3.  [6] and in HCD of 100-150 g/dm 3 [4], the IR drop values in the range of [Ag + ] of 60-200 g/dm 3 were simulated by using the models in Equations (7)- (9) at the range of [Cu 2+ ]/ [Ag + ] as shown in Figure 6 with the constant values of [HNO3] of 5 g/dm 3 at median temperature of 35 °C.  Calculation of the conventional process IR drop by using the Equation (4) from the data in Table 1 shows IR drop values within the range of 0.8-2.3 V which equal to 55-82% of the total cell potential. As it can be expected, HCD process results in higher cell potential thus the role of electrolyte conductivity is significant. With the positive effect of [Cu 2+ ] to the conductivity of electrolyte, it is important to take a study of the possibility of having [Cu 2+ ] in smaller ratios of [Cu 2+ ]/[Ag + ] to achieve both optimum conductivity and to avoid the co-deposition of Cu on the cathode. A comparison of the [Cu 2+ ]/[Ag + ] levels from previous studies is shown in Table 3. From the suggested general [Ag + ] of > 60 g/dm 3 [6] and in HCD of 100-150 g/dm 3 [4], the IR drop values in the range of [Ag + ] of 60-200 g/dm 3 were simulated by using the models in Equations (7)- (9) at the range of [Cu 2+ ]/[Ag + ] as shown in Figure 6 with the constant values of [HNO 3 ] of 5 g/dm 3 at median temperature of 35 • C.  Table 4. In the table, the empirical model shows the lowest IR drop calculation while the industrial model has the highest value.  Figure 3. As mentioned in Section 2, the validation tests were conducted to a type of industrial electrolyte only, thus the model has questionable validity to be applied in different types of electrolyte. With these weakness of each model in correlation to the range industrial application, all the models were taken into account in predicting the outcome in terms of specific energy consumption of HCD in the suggested electrolyte condition from this study.

Anodic and Cathodic Overpotential (ηa and ηc)
From the modelling of the galvanostatic results [15], cathodic overpotential when operating at 1000 A/m 2 current density could not be measured and modelled reliably due to the dendritic deposition, nevertheless the measured cathodic overpotentials were 147-297 mV and decreasing with   Table 4. In the table, the empirical model shows the lowest IR drop calculation while the industrial model has the highest value. As can be seen from Table 4, the difference of empirical with the industrial conductivity values is significant. This was mainly caused by the actual concentration of the industrial electrolyte where more dissolved contents were presents, while the empirical model was built only with the effect of major concentrations such as [Ag + ], [HNO 3 ], [Cu 2+ ], and [Pb 2+ ]. Validation model connects empirical and industrial model with the correlation schematically shown in Figure 3. As mentioned in Section 2, the validation tests were conducted to a type of industrial electrolyte only, thus the model has questionable validity to be applied in different types of electrolyte. With these weakness of each model in correlation to the range industrial application, all the models were taken into account in predicting the outcome in terms of specific energy consumption of HCD in the suggested electrolyte condition from this study.

Anodic and Cathodic Overpotential (η a and η c )
From the modelling of the galvanostatic results [15], cathodic overpotential when operating at 1000 A/m 2 current density could not be measured and modelled reliably due to the dendritic deposition, nevertheless the measured cathodic overpotentials were 147-297 mV and decreasing with increasing silver concentration. The anodic overpotential at 1000 A/m 2 as function of electrolyte conditions was modelled as follows: where η a is the anodic overpotential (mV), concentrations in g/dm 3 and temperature in degrees centigrade. Using the electrolyte concentrations in Table 4, the anodic overpotential is within the range of 20-107 mV. Anodic Tafel slope (b a ) model of Ag in AgNO 3 -HNO 3 from the study of Ag kinetic dissolution [14] can be written as Equation (11) with model accuracy shown in Figure 7a, while the difference of both values are shown in Figure 7b. As can be seen from the model and measurements, the anodic Tafel slope is within the range of 0.24-0.45 V. Thus, by using the correlation of current density and anodic overpotential outlined in Equation (12), increase of current density from 420 A/m 2 to 1000 A/m 2 requires small increase of anodic overpotential of 0.09-0.2 V. This suggests that increasing current density to 1000 A/m 2 does not increase the anodic overpotential substantially.
where ηa is the anodic overpotential (mV), concentrations in g/dm 3 and temperature in degrees centigrade. Using the electrolyte concentrations in Table 4, the anodic overpotential is within the range of 20-107 mV. Anodic Tafel slope (ba) model of Ag in AgNO3-HNO3 from the study of Ag kinetic dissolution [14] can be written as Equation (11) with model accuracy shown in Figure 7a, while the difference of both values are shown in Figure 7b. As can be seen from the model and measurements, the anodic Tafel slope is within the range of 0.24-0.45 V. Thus, by using the correlation of current density and anodic overpotential outlined in Equation (12), increase of current density from 420 A/m 2 to 1000 A/m 2 requires small increase of anodic overpotential of 0.09-0.2 V. This suggests that increasing current density to 1000 A/m 2 does not increase the anodic overpotential substantially.

Passivation Overpotential (ηpass)
Gold in silver anodes causes anode passivation. This is due to anode surface enrichment by gold along silver dissolution. In earlier studies, application of HCD in high [Ag + ] electrolyte (min 100 g/dm 3 ) was shown to be kinetically efficient for maximum Au content less than 6% in the anode [15]. The passivation range due to Au content in anode can be calculated by using Equation (13)

Passivation Overpotential (η pass )
Gold in silver anodes causes anode passivation. This is due to anode surface enrichment by gold along silver dissolution. In earlier studies, application of HCD in high [Ag + ] electrolyte (min 100 g/dm 3 ) was shown to be kinetically efficient for maximum Au content less than 6% in the anode [15]. The passivation range due to Au content in anode can be calculated by using Equation (13) [16].
With the limitation of Au content to maximum of 6%, the effect of passivation overpotential is minimized when using the electrolyte concentrations in Table 4. This results in passivation overpotential of 0.2 V.

Circulating Electrolyte volume
For the value of A/V set to a constant of 0.004, 1 m 2 of anode surface per 250 dm 3 of bulk electrolyte, taken from the general industrial practices for Moebius cell [11]. At the rate of production of 100 kg/day, electrolyte volume as a function of applied current density is shown by Equation (14).
From above equation, to have the same productivity, higher current density process requires smaller volume of electrolyte.

Cell Voltage, SEC, and Silver Inventory
For summary, the electrolyte concentrations in Table 4  • η a and η c = 0.32-0.40 V • η Au = 0.02 V As can be seen from the components above IR drop is the most dominant by contributing 86-91% of the cell voltage. This was further supported by the anodic Tafel slope model which shows that increase of current density insubstantially affects the anodic overpotential.
The increasing portion of IR drop to the cell voltage were simulated as shown in Figure 8. The contribution of IR drop to cell voltage increases with increase in current density and IR drop contributes more than 85% of the cell voltage at 1000 A/m 2 operation. In addition, operating at lower range of electrolyte concentration increases the IR drop portion to more than 90% of the cell voltage for electrolyte with lower [Ag + ]. From the simulation, increase of electrolyte concentrations reduce the IR drop portion of cell voltage significantly while increase of temperature is shown to have less impact. While IR drop can be reduced by increasing both temperature and concentrations of the electrolyte, it cannot be avoided that IR drop contribution to cell voltage at 1000 A/m 2 is significant as calculated by all the models of the current study.  Table 4.   Table 4.
Towards the potential application of HCD as an improvement to the current silver electrorefining practices, competitiveness of the process key figures in comparison to the conventional process is of importance. Accordingly, the key figures of both processes are outlined in Table 5. The suggested parameters from this study are compared to the HCD from previous publication [4] and to the conventional silver electrorefining [7][8][9][10][11][12].  Table 5 shows that HCD in this study has competitive advantage in comparison to both previous HCD and conventional silver electrorefining process. When the current density of HCD is increased to more than double of the conventional process, the cell voltage is shown to increase only for 30-40%. This increase of SEC is a significant improvement from the 1.27-1.28 kWh/kg from the previous HCD [4] which accounts more than 60% increase of SEC in comparison to the conventional process. With the same [Ag + ] level, the utilization of [Cu 2+ ] an [HNO 3 ] to boost the conductivity was the cause of significantly lower SEC.
From Table 5, electrolyte volume and silver inventory were calculated for the same throughput. Comparison of HCD to the conventional process on the basis of 100 kg/day production rate shows that the median value of HCD silver inventory of approximately 32 kg which is far less than the median value of approximately 105 kg of the conventional process [7][8][9][10][11][12]. The required electrolyte volume of HCD was also shown to be less than half of the conventional process. Thus, the HCD application could turn to be highly beneficial as it is not only increasing the capacity due to the high throughput of the process but also has the possibility to reduce the process inventory and the equipment footprint. This suggests feasibility also from the economic point of view of the process.

Conclusions
This study simulates the impact of HCD, 1000 A/m 2 current density operation in silver electrorefining through the optimization of the electrolyte composition. With the objective to increase the applicability and competitiveness of HCD in comparison to the conventional process, an optimum range of electrolyte composition was developed through simulation. With the prudential practice of precious metal refineries, the study has the limitation in the measurements of industrial electrolytes and anodes with only a validation of conductivity model was conducted. Therefore, this study was mainly focused on the simulation of the developed models from previous publications.
From the simulation, it was found that by increasing the electrolyte conductivity through the introduction of [Cu 2+ ] would lower the cell voltage from the IR drop significantly. While conductivity is in general an important property in electrorefining process, the higher current density in an HCD operation amplifies the significance of IR drop. Its contribution to cell voltage increased to more than 85% which is higher than the 55-82% range in the conventional process. The optimum concentrations for HCD electrolyte were suggested being within the range of 100-150 g/dm 3 for [Ag + ] and 50-75 g/dm 3 for [Cu 2+ ]. While increasing electrolyte silver and copper concentrations reduce the IR drop substantially, the effect of temperature is shown to have less impact. As a conclusion, HCD operation in the suggested electrolyte results in 0.60-1.01 kWh/kg of SEC with silver inventory in the electrolyte within the range of 25.9-38.85 kg for a 100 kg/day production rate. While this study elaborated the potential improvement of silver electrorefining process, study of the economic and environmental impact of HCD will add values to this process improvement.