Advanced kinetic models through mechanistic understanding: Population balances for methylenedianiline synthesis

Abstract

The recent development of amorphous silica-alumina catalysts for the heterogeneously-catalyzed production of methylenedianiline (MDA) has resulted in an economically and environmentally attractive alternative to the industrially employed HCl catalyst. However, the quantitative kinetic description of the complex reaction network, a key prerequisite for reactor choice and process assessment, is unfeasible when using classical power-law based models due to the wealth of components and interactions involved. Based on high throughput batch experiments coupled with a detailed product analysis, we herein reveal that all possible reactions in an MDA mixture can be represented in terms of interactions between a small number of reoccurring functional groups. A corresponding categorization of all mixture components enables the description of the reaction network using population balance equations, an approach previously applied to polymerization, aggregation, and cell-growth processes. Thereby, every possible binary interaction between two molecules in the system can be accounted for, resulting in an unprecedented resolution regarding oligomeric species and improved predictive capabilities based on a small number of parameters. The translation of the deepened mechanistic understanding into advanced kinetic models enables to circumvent previous limitations, and is expected to accelerate the industrial realization of the sustainable process.