Optimization of hemihydrate process operating parameters: A combined approach of experimentation, modeling and simulation

Abstract BACKGROUND This study investigates the optimization of the hemihydrate process for producing high concentration phosphoric acid from low to medium grade phosphate rock. The research evaluates critical operating parameters, including particle size, agitation speed, temperature, and reactant feed rates, to maximize production efficiency and state the main aims of establishing a predictive framework. RESULTS Experimental trials utilizing a particle size between 40 and 250 μm and an agitation speed of 800 rpm at 98 °C yielded a phosphoric acid mass fraction of 0.4246. While initial thermodynamic modeling using the electrolyte‐NRTL framework resulted in a 3.92% deviation from experimental data, a custom kinetics‐based model implemented in Python significantly improved predictive accuracy. By accounting for fluorapatite dissociation and hemihydrate crystallization, this kinetic model reduced the deviation to just 0.46%. These results demonstrate that combining experimental data with advanced simulation provides a robust framework for optimizing production. CONCLUSION The integration of experimental data with advanced simulation provides a robust framework for optimizing production. By combining flowsheet simulation for plant sizing with kinetic modeling for real‐time reactor tuning, fluctuations in phosphate rock quality can be effectively managed. This dual approach ensures process design integrity and high‐precision chemical performance, offering a scalable method to improve yield and purity under industrial conditions. © 2026 Society of Chemical Industry (SCI).