Mechanism Inference from Information-Rich Time-Varying Spectrokinetic Data: A Conceptual Framework

Combining the microkinetic modeling, reaction kinetics studies, and operando molecular spectroscopy experiments together has been applied to identify the reaction mechanism of heterogeneous catalytic reaction. Traditionally, kinetic experiments are performed at steady state reaction conditions. On the other hand, time varying kinetic experiments such as modulated excitation spectroscopy (MES) and temporal analysis of product (TAP) allows for capturing fast-time scale transients of the reaction system which are often missed in steady state kinetic study. Despite providing rich information about the reaction system, such time-varying data in combination with DFT is rarely used to develop mechanistic models of heterogeneously catalyzed reaction systems beyond simple demonstrations of few step first order reactions.

In this work, we develop a statistical and microkinetic modeling framework to extract the kinetic information from modulated kinetic experiments. We showcase the reaction mechanism is recovered by progressively incorporating mechanistic information in the microkinetic model. This work demonstrates the feasibility of identifying the reaction mechanism with the combination of microkinetic modeling and modulated kinetic experiments.