Automated reaction generation for polymer networks

Most of the theoretical studies on polymer kinetics has been performed by manually reducing the chemical system to a few simple reaction mechanisms having a repeatable nature. Not being constrained by such reducibility, this work considers the polymerization as a product of a complex network of reactions that need not to be known in advance. Combining various ideas from graph theory, combinatorics and random graphs, we introduce a new modeling approach to complex polymerization that automatically constructs a reaction network, solves kinetic model, and retrieves such topological properties of the final polymer network as, for instance, distribution of molecular weight. In this way, the new approach acts as an intermediate layer that propagates the knowledge of the basic chemistry in order to capture and understand the complexity of the real world polymerizing systems.