Predicting molecule size distribution in hydrocarbon pyrolysis using random graph theory.

• DOI: 10.48550/arxiv.2205.13664
• Publication Date: 2023-01-09
• Authors: Vincent Dufour-Dé...; Christopher Moakler; Evan J. Reed; Maria Cameron
• Keywords: High Energy Physics - Theory; Chemical Physics (physics.chem-ph); FOS: Physical sciences; Mathematical Physics (math-ph); Computational Physics (physics.comp-ph); 01 natural sciences; High Energy Physics - Theory (hep-th); 13. Climate action; Physics - Chemical Physics; 0103 physical sciences; Physics - Atomic and Molecular Clusters; Atomic and Molecular Clusters (physics.atm-clus); Physics - Computational Physics; Mathematical Physics

Hydrocarbon pyrolysis is a complex process involving large numbers of chemical species and types of chemical reactions. Its quantitative description is important for planetary sciences, in particular, for understanding the processes occurring in the interior of icy planets, such as Uranus and Neptune, where small hydrocarbons are subjected to high temperature and pressure. We propose a computationally cheap methodology based on an originally developed ten-reaction model and the configurational model from random graph theory. This methodology generates accurate predictions for molecule size distributions for a variety of initial chemical compositions and temperatures ranging from 3200 to 5000 K. Specifically, we show that the size distribution of small molecules is particularly well predicted, and the size of the largest molecule can be accurately predicted provided that this molecule is not too large.