Focus of this paper is the experimental demonstration of forced periodic operation applied to the synthesis of methanol. A theoretical analysis using the nonlinear frequency response (NFR) method and rigorous mathematical optimization provide a general guideline for analyzing simultaneously carried modulations of inlet composition and total volumetric flow rate. Influences of the forcing parameters (amplitudes, frequencies, phase differences, and shapes of forcing functions) were studied for well‐mixed reactors (CSTR) and theoretically for tubular reactors. Predictions of promising operating conditions were made exploiting a kinetic model developed and validated for an industrial Cu/ZnO/Al ₂ O ₃ catalyst. Confirming the trends of the theoretical results, in an experimental study using a laboratory CSTR, higher time‐averaged product amounts and improved yields were achieved compared to conventional steady state operation applying the optimized phase‐shift. Hereby, square wave modulations of the inputs outperformed sinusoidal modulations. A severe and unsolved problem concerns the deactivation of the catalyst observed in the course of the three months experimental campaign, which caused performance reductions for both steady state and periodic operation.

The transition of the chemical industry towards the utilization of feedstocks based on renewable energies results in a more dynamic process behavior. Advanced mathematical methods are a key factor to handle this complexity. In this contribution, methanol synthesis from hydrogen, carbon dioxide and carbon monoxide is investigated as promising power-2-X technology. Optimal experimental design is used to recalibrate an existing mechanistic kinetic model. Subsequently, the most uncertain sub-model, namely the reversible catalyst dynamics, is partially replaced by neural networks. Several architectures were evaluated, and optimal experimental design was applied to enhance the performance of a chosen architecture. All experiments were realized in an experimental setup able to acquire time-resolved data. A commercial CuO/ZnO/Al₂O₃ catalyst was used in a well-mixed Berty type reactor. The combination of optimal experimental design with hybrid modeling led to an improved quality of the kinetic model needed for process control and optimization.

This study evaluates the intensification potential of forced periodic operation (FPO) for methanol synthesis performed in a cooled continuous stirred tank reactor (CSTR) using nonlinear frequency response (NFR) methodology. A comprehensive dynamic reactor model incorporating the mass and energy balances, temperature-dependent kinetics, and dynamic changes of different active centres was used. The theoretical approach enables time-saving prediction of time-averaged reactor performance under periodic modulation of single and simultaneous input variables. Single-input forcing of inlet temperature and H2 resulted in modest improvements in methanol production, whereas modulation of CO, CO₂, or volumetric flow rate predominantly caused performance deterioration. In contrast, simultaneous two-input modulation (CO & flow rate, CO2 & flow rate and H2 & flow rate) generated substantially stronger positive effects. Modulation of CO & flow rate increased the methanol productivity and yield based on hydrogen up to 33.1%, while deteriorating yield based on total carbon. Hereby, the yield of methanol based on total carbon was predicted to increase most pronouncedly in the case of H2 & flow rate modulations (up to 28.6%). Multi-objective optimisation showed that it is also possible to select points on the resulting Pareto front at which the system can be improved in terms of both productivity and yield compared to the steady state. The results of the present study demonstrate that dynamic reactor operation can surpass steady state limitations. NFR analysis is an analytical and efficient tool for a priori screening and design of intensified operating strategies. It is applicable to other reactions and operating concepts.