A generalized solid state kinetic expression for reaction interface-controlled reactivity

Abstract

The ICTAC-recommended approach was used to characterize the gasification of high-purity, highly crystalline, large natural graphite flakes in oxygen. The average activation energy was found to be 157.7 ± 4.2 kJ mol−1. The graphite properties and the simple gasification reaction taking place make this an ideal material for the study of reaction interface-controlled reactivity. Based on simple structural and geometrical observations, it was expected that the conversion function would be that of a shrinking disc. However, the experimental conversion function exhibited a behaviour which could not be linked to any of the commonly established reaction models. A factor contributing to this disconnection is the use of an arbitrary scaling procedure in classic solid state kinetics. A more integrated approach has recently been proposed in the literature with the potential for reconciling disparate models into a single comprehensive scheme. A generalization of the classic solid state kinetic expressions for interface-controlled reactivity is proposed which fits into the integrated approach. It is based on fundamental considerations for the subset of reactions in which reactivity is controlled by the reaction interface alone. The fundamental nature of the approach yields an expression for which all the variables are directly measurable, without any assumptions regarding the conversion function. The generalized conversion function will always start at a value of one, making interpretation and direct comparison of any active surface area (ASA) progression possible. Visual observations indicate the growth of defect structures within the macro graphite flakes, leading to an increase in ASA. This leads to a behaviour resembling nucleation and growth, despite the interface-controlled reaction taking place on a disc-shaped solid. The random nature of the oxidized flake microstructure makes it difficult to develop representative analytical models for this behaviour.