The enzymatic hydrolysis of urea is a mild route to the production of ammonia, but the activity of urease depends strongly on the pH value. In operation without buffer, the pH can drift substantially, because ammonia and inorganic carbon repartition rapidly through the equilibria of acids and bases.
In this work, the authors develop a framework for modelling and control that is aware of uncertainty and regulates the pH value with carbon dioxide during the hydrolysis of urea catalysed by urease. A mechanistic model oriented towards control couples the pH dependent kinetics of urease, including inhibition by substrate and product, with the fast speciation, where the pH value follows from electroneutrality, and with the mass transfer of ammonia and carbon dioxide between the liquid and the gas in the headspace. The uncertainty of the kinetic and transfer parameters is propagated with a nonintrusive polynomial chaos expansion.
Building on these predictions, a scheme of stochastic model predictive control is proposed. It tracks a reference value of the pH under constraints on the input, while chance constraints keep the pH value within its safety bounds.
The simulations demonstrate that the pH value can be regulated without buffer salts under the considered scenarios of parametric uncertainty. This provides a foundation for the automated operation of enzymatic reactors under uncertainty. The background of the process model, the experimental protocol and the identification of the parameters are reported in a companion manuscript.
The study is a collaboration between the Institute of Control Systems and the Institute of Process Systems Engineering at Hamburg University of Technology, carried out within the Collaborative Research Centre CRC 1615 (SMART Reactors).
Srimanta Santra, Leandros Paschalidis, Mirko Skiborowski, Timm Faulwasser (2026). CO₂-Driven pH Control in the Enzymatic Hydrolysis of Urea: Stochastic Model Predictive Control under Uncertainty. Ind. Eng. Chem. Res. 65 (28), 15071-15088.
