Dynamic or Programmable Catalysis is an emerging strategy that seeks to enhance the performance of heterogeneous catalytic systems by modulating adsorbate binding energies (BEs). This modulation favors different elementary reaction steps dynamically in time, resulting in overall reaction rates that exceed those of static systems. In doing so, this approach offers a path to overcome limitations imposed by the Sabatier principle, allowing a catalytic system to move back and forth across both sides of a typical Sabatier volcano curve. As a proof of concept, we previously introduced a computational framework for dynamic catalysis problems using simultaneous simulation and optimization techniques, and studied a unimolecular (“A-to-B”) reactive system. In this work, we extend our framework to a more realistic and industrially relevant reaction: ammonia synthesis. This system was chosen not only for its complexity and importance but also to build upon the strong foundation established by other researchers, particularly regarding the detailed microkinetic model, involving nineteen reversible elementary reaction steps.
We investigated system performance under BE oscillations induced by surface strain, focusing on how waveform characteristics, particularly frequency, amplitude, and offset of a sine wave influence catalytic behavior at cyclic steady state. Using a strategy that combines sequential and simultaneous simulation approaches, we explored a broad range of forcing conditions with a significant reduction in computational cost, achieving a 220-fold decrease in runtime compared to using the sequential approach alone. Our results show that frequencies above 1000 Hz and strains greater than 2% can negatively impact the catalyst performance. Ongoing work focuses on expanding the model to account for lateral interactions between adsorbates, exploring alternative waveforms as forcing signals, and further integrating mathematical optimization approaches. These advancements lay the foundations to establish a general and systematic mathematical framework for identifying optimal waveforms across a wide range of dynamic catalysis systems.
