A memory-based approach to modeling chemical reaction kinetics

This work explores the application of a memory-based approach to modeling chemical reaction kinetics. The key idea is that the past reaction rates impact the current reaction rate via a memory kernel. In this way, the chemical reaction kinetics is path-dependent in the sense that the reaction trajectory determines, via temporal correlations, the current reaction rate. One arrives at a memory-based kinetics model represented as integro-differential equations. Memory models can be seen as the bridge between models based on fractional calculus and classical integer order derivatives in the time domain. However, memory-based models can be made affordable for practitioners since concepts involved in fractional calculus are not required. Two examples are used to illustrate the model development and the parameter estimation. It was concluded that the intrinsic local time chemical kinetics may be quite simple (e.g., first order), but memory effects can add complexity to the reacting system behavior.