Predicting molecule size distribution in hydrocarbon pyrolysis with the aid of random graphs

What is it about?

Hydrocarbon pyrolysis is a complex chemical reaction system with thousands of chemical species generated by tens of thousands types of chemical reactions. The contemporary approaches to studying hydrocarbon pyrolysis include reactive molecular dynamics (MD) simulations and kinetic Monte Carlo algorithms. Reactive molecular simulations require large computing resources and take a long time. Kinetic Monte Carlo is much more efficient but relies on reaction data learned from MD simulations and requires a new run for temperature and each initial molecular composition. We developed a model based on random graph theory that predicts molecule size distribution in seconds of computation time.

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Photo by Terry Vlisidis on Unsplash

Photo by Terry Vlisidis on Unsplash

Why is it important?

Our new approach allows us to predict the size distribution of molecules undergoing hydrocarbon pyrolysis in seconds compared to the days required for reactive molecular dynamics simulations. The approach also gives the conditions wherein a “giant component” or a large molecule containing most of the atoms in the system can arise.