Effective diffusivity of ferric ions and current efficiency in stagnant synthetic copper electrowinning solutions

Moats, Michael S.; Khouraibchia, Youness

doi:10.1007/bf03402537

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…It is important to note that tests 3 and 4 were performed using an electrolyte containing 160 g/L H 2 SO 4 which was different from the concentration used to generate the models. Since the statistical models predicted the results accurately, this confirms the results of our previous work (11) were it was concluded that the sulfuric acid has a minimal effect on current efficiency and no significant effect on energy consumption. Therefore, these statistical models may predict CE and EC for electrolytes containing a sulfuric acid concentration varying from 160 g/L to 220 g/L with minimal error.…”

Section: Verification Of Modelssupporting

confidence: 88%

“…Also it has been shown by Das and Krishna (2) that increasing the electrolyte temperature leads to lowering the EC in CuEW. In our previous work (11) the effect of ferric concentration, copper concentration, current density, electrolyte temperature, sulfuric acid, cobalt, manganese and chloride on CE and EC were evaluated and the analysis of the results showed that the main important parameters which affect the CE and EC are the ferric concentration, copper concentration, current density and electrolyte temperature. According to a 2007 survey conducted by Robinson et al (12), copper electrowinning is industrially carried out under a wide temperature range varying between 25 and 65 o C. Therefore, there is no universal optimum for the temperature and the best temperature is determined by other operation parameters specific to each industrial operation.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the Effect of Copper Electrowinning Parameters on Current Efficiency and Energy Consumption Using Surface Response Methodology

Khouraibchia

Moats

2010

ECS Trans.

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IntroductionProducing high quality copper cathode with minimum energy consumption and maximum current efficiency is a goal for all copper electrowinning (CuEW) operations. To attain this goal, operators need a simple method to understand the effects and interactions between common parameters affecting the production of copper by electrowinning. Therefore, a detailed statistical analysis was performed to understand the effects of several parameters and their resulting synergetic effects on the performance of the CuEW process. In this study, a surface response design was used to organize the experiments to evaluate the effect of ferric concentration, copper concentration and current density, in ranges relevant to industrial operations on current efficiency (CE) and energy consumption (EC) of a laboratory cell. A statistical analysis was performed which allowed for a better understanding of the effect of the studied parameters and revealed the existence of significant interactions between them. In addition, statistical models of CE and EC were developed and that can be used to control and optimize the CuEW process.

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Section: Verification Of Modelssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Evaluation of the Effect of Copper Electrowinning Parameters on Current Efficiency and Energy Consumption Using Surface Response Methodology

Khouraibchia

Moats

2010

ECS Trans.

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“…The purified leach liquor containing 55-90 kg Zn 2+ and 125-175 kg•m −3 of H 2 SO 4 solution is electrolysed at about 30-35°C. Hard rolled aluminium cathodes are employed to attain higher over voltage and Pb-0.5-1.0% Ag alloy anodes (Moats et al 2008) to lower oxygen over-voltage for oxygen evolution, which is advantageous in retarding the corrosion of the anode. At a current density of 300 A•m −2 the cathode current efficiency of zinc deposition is 90% and energy consumption works out to be 3.2 kWh•kg −1 .…”

Section: Electrowinning Of Zincmentioning

confidence: 99%

Role of electrochemical processes in the extraction of metals and alloys – a review

Shamsuddin,

Sohn

2023

Mineral Processing and Extractive Metallurgy: Transactions of t

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This review discusses the electrochemical principles involved in the recovery of metals from aqueous solutions and fused salt electrolytes. In this article we concentrate on electrolytic processing of different types of metals with an emphasis on the significant role of electrochemical principles together with free energy and activity in electrowinning and electrorefining of common and reactive metals. Based on discharge potentials, metals are classified into three categories with respect to their characteristics of deposition from aqueous electrolytes without hydrogen evolution, under hydrogen over-voltage, and only from fused electrolytes.

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“…As shown in figure 1, in the electrolytic refining process, copper is dissolved into copper ions from a fire-treated anode plate and passes through an electrolyte * Author to whom any correspondence should be addressed. made of a mixture of sulfuric acid and copper sulfate to a cathode, where it gains electrons to precipitate pure copper [2]. As shown in figure 2, in an electrolysis plant a large number of cells are distributed in a matrix, with approximately 34 pairs of cathode and anode plates in each cell.…”

Section: Introductionmentioning

confidence: 99%

An attention-based long short-term memory prediction model for working conditions of copper electrolytic plates

Zhu

Pang

Zhou

et al. 2023

Meas. Sci. Technol.

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Copper is an important resource of non-ferrous metals. Electrolytic refining is one of the main methods to produce fine copper. In electrolytic process, plate conditions seriously affects the output and quality of copper. Timely and accurate prediction of the working condition of the plate is of great significance to the copper electrolytic refining process. Aiming at the problems of the traditional plate conditions detection algorithm with large lag, poor anti-interference ability and low accuracy, this paper proposes a plate condition prediction model based on LSTM with attention mechanism. The average gray value of the plate in the infrared image is used to characterize the plate working condition. In hidden layer, double layer LSTM network is used to improve the effect of model training. A unique attention mechanism is added to learn the correlation between input and output better and improve the accuracy of model prediction. Experimental results show that the accuracy of the proposed model for plate condition prediction reaches 95.11%. Compared with the commonly used LSTM algorithm, the plate condition prediction model proposed in this paper has stronger prediction ability.

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Effective diffusivity of ferric ions and current efficiency in stagnant synthetic copper electrowinning solutions

Cited by 7 publications

References 9 publications

Evaluation of the Effect of Copper Electrowinning Parameters on Current Efficiency and Energy Consumption Using Surface Response Methodology

Evaluation of the Effect of Copper Electrowinning Parameters on Current Efficiency and Energy Consumption Using Surface Response Methodology

Role of electrochemical processes in the extraction of metals and alloys – a review

An attention-based long short-term memory prediction model for working conditions of copper electrolytic plates

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