CO ₂ -Driven pH Control in the Enzymatic Hydrolysis of Urea: Stochastic Model Predictive Control under Uncertainty

High Resolution Image Download MS PowerPoint Slide Enzymatic urea hydrolysis is a mild route to ammonia production, but urease activity is strongly pH dependent. In buffer-free operation, pH can drift substantially because ammonia and inorganic carbon rapidly repartition through acid–base equilibria. Detailed process-modeling background, experimental protocol, and parameter identification context are reported in a companion manuscript by Dittmer, K. R. ( 2026 ). Here, in contrast, we develop an uncertainty-aware modeling and control framework for CO 2 -driven pH regulation during urease-catalyzed urea hydrolysis. A control-oriented mechanistic model couples pH-dependent urease kinetics with substrate and product inhibition, fast speciation with electroneutrality-based pH computation, and gas–liquid mass transfer of NH 3 and CO 2 in a headspace. Parametric uncertainty in kinetic and transfer parameters is propagated using nonintrusive polynomial chaos expansion. Building on these predictions, we propose a stochastic model predictive control (SMPC) scheme that tracks a pH reference under input constraints while enforcing chance constraints on pH safety bounds. Simulations demonstrate uncertainty-aware pH regulation without buffer salts under the considered parametric uncertainty scenarios, providing a foundation for automated operation of enzymatic reactors under uncertainty.