Abstract
The depletion of high-grade molybdenum ores and the need to process complex sulfide concentrates pose significant challenges for the hydrometallurgical industry. Traditional approaches to processing experimental data based on manual calculations are characterized by high labor intensity, risk of computational errors, and information fragmentation. This paper describes the development of a specialized information system for modeling and analyzing the hydrometallurgical processing of molybdenite concentrates. The software is implemented using the Django web framework and includes modules for experimental data input, automated calculation of material balances for leaching and sorption processes, and visualization of results through interactive analytical dashboards. The system has been validated using data from 6 leaching experiments and 9 molybdenum sorption experiments. The modular three-tier architecture ensures solution scalability and enables its adaptation for modeling other hydrometallurgical processes. The developed calculators allow predicting molybdenum recovery rates at various stages of the technological cycle without conducting additional physical experiments. The practical significance of this work lies in creating a digital twin of the technological process that establishes a unified information space for researchers, ensures transparency and reproducibility of experiments, and lays the foundation for industrial scaling of molybdenite concentrate processing technology.