In copper electrorefining and electrowinning, the conductivity and viscosity of the electrolyte affect the energy consumption, and for electrorefining the purity of cathode copper. Consequently, accurate models for predicting these properties are highly important. Although the modeling of conductivity and viscosity of synthetic copper electrolytes has been previously studied, only a few models have been validated with actual industrial electrolytes. The conductivity and viscosity models outlined in this study were developed using conductivity and viscosity measurements from both synthetic and industrial solutions. The synthetic electrolytes were investigated over a temperature range between 50–70 °C and typical concentrations of Cu (40–90 g/dm3), Ni (0–30 g/dm3), Fe (0–10 g/dm3), Co (0–5 g/dm3), As (0–63.8 g/dm3), H2SO4 (50–223 g/dm3) as well as other solution impurities like Sb in some cases. Validation of the synthetic electrolyte models was performed through industrial measurements at three copper plants across Europe. Generally, the developed models predicted the conductivities and viscosities of industrial solutions with high accuracy. The viscosity models covered extended ranges of both [H2SO4] and [Cu] with percentage errors of only (2.08 ± 0.59) - (2.48 ± 0.61). For conductivity, two different models for low (<142 g/dm3) and high (>142 g/dm3) [H2SO4] electrolytes were utilized. Their error margins were (−1.96 ± 0.84) - (−1.44 ± 0.35) and (1.17 ± 0.27) - (2.52 ± 0.28), respectively. In the case of high [H2SO4] electrolytes, the validations focused on conductivity, and the highest level of accuracy was obtained when the effects of Sb and other minor impurities were considered.
SormenjälkiSukella tutkimusaiheisiin 'Industrial validation of conductivity and viscosity models for copper electrolysis processes'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.
- 1 Päättynyt
Lundström, M., Porvali, A., Aromaa, R., Aromaa, J., Wilson, B., Kalliomäki, T., Karppinen, A., Revitzer, H., Zhang, J., Chernyaev, A., Zou, Y., Hu, F., Ke, P., Liu, F., Rinne, M., Khalid, M. K., Palomäki, H., Partinen, J., Seisko, S., Peng, C., Sahlman, M., Wang, Z., Shukla, S., Forde, G. & Ruismäki, R.
01/01/2019 → 30/04/2021
Projekti: Business Finland: Other research funding