Developing an accurate predictive model for the complex nonlinearity of electric-field-enhanced pyrolusite leaching presents a significant challenge. The manganese leaching process involves crushing and grinding the pyrolusite ore (MnO2) to increase its surface area.

This use case focuses on creating a predictive model for leaching rates in manganese ore processing. By addressing the nonlinear dynamics of the leaching process, we aim to enhance the efficiency and accuracy of manganese extraction.