A Computational Framework for Cyclic Steady-State Simulation of Dynamic Catalysis Systems: Application to Ammonia Synthesis

Dynamic or Programmable Catalysis is an innovative strategy to improve heterogeneous catalysis processes by modulating the binding energies (BE) of adsorbates on a catalytic surface. The technique enables the periodic favoring of different reaction steps, overcoming limitations imposed by the Sabatier Principle and allowing for higher overall reaction rates, otherwise unattainable. Previously, we implemented a simultaneous simulation approach using the algebraic modeling language Pyomo and the solver IPOPT to obtain cyclic steady state results for a unimolecular reactive system with up to four-order of magnitude increases in computational performance compared to the previously reported sequential approach. The flexibility of the method allowed for the investigation of the influence of forcing signal parameters on system behavior and provided a framework for waveform design. In this study, we use a hybrid framework that combines the sequential and the simultaneous simulation approaches to find the cyclic steady state of a more complex system, of ammonia synthesis, comprising 19 reversible elementary reaction steps. The framework allowed us to investigate sine wave parameters with approximately 220 times less computational effort compared to the sequential approach alone. With the parameters studied, our findings indicate that frequencies exceeding 1000 Hz and compressive strains greater than 2% can negatively impact the system performance. Future work will focus on expanding the model to include lateral interactions between molecules, using other waveform as forcing signals, and integrating systematic mathematical optimization approaches. These advancements pave the way to establishing a general framework for identifying optimal waveforms across diverse dynamic catalysis systems.