Dynamic catalysis is a novel and promising approach that
aims to
improve the catalyst performance by modulating the binding energies
of adsorbates to favor different reaction steps periodically. In this
work, we investigate a unimolecular dynamic catalytic system, with
a focus on methods for simulating the transient behavior and identifying
the optimal wave parameters for the modulations. Employing the modeling
language Pyomo and the solver IPOPT, we formulate a Boundary Value
Problem with limit cycle conditions to obtain results with orders-of-magnitude
improvements in computational efficiency when compared to forward
integration methods. Leveraging this flexible approach, mathematical
optimization was applied to the parameters of piecewise and continuous
forcing functions to identify the maximum time-averaged turnover frequency
(avTOF). We relate the results to the Extended Sabatier Volcano graphical
representation, which provides insight into the behavior and optimal
parameters of the target systems. Our results further support the
notion that periodic shifts in rate-controlling elementary steps lead
to a rate of reaction enhancement beyond the Sabatier limit.