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Related Experiment Video

Updated: Aug 14, 2025

On-line Analysis of Nitrogen Containing Compounds in Complex Hydrocarbon Matrixes

On-line Analysis of Nitrogen Containing Compounds in Complex Hydrocarbon Matrixes

Published on: August 5, 2016

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

Vincent Dufour-Décieux¹, Christopher Moakler², Evan J Reed¹

¹Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, USA.

The Journal of Chemical Physics

|January 14, 2023

Summary

This summary is machine-generated.

We developed a fast, accurate method to predict molecule size distributions during hydrocarbon pyrolysis. This approach aids understanding chemical processes inside icy planets like Uranus and Neptune.

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Last Updated: Aug 14, 2025

On-line Analysis of Nitrogen Containing Compounds in Complex Hydrocarbon Matrixes

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Qualitative Characterization of the Aqueous Fraction from Hydrothermal Liquefaction of Algae Using 2D Gas Chromatography with Time-of-flight Mass Spectrometry

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Published on: April 8, 2020

Area of Science:

Planetary Science
Chemical Kinetics
Computational Chemistry

Background:

Hydrocarbon pyrolysis is a complex chemical process crucial for understanding planetary interiors.
Icy planets like Uranus and Neptune experience high temperatures and pressures, leading to hydrocarbon reactions.

Purpose of the Study:

To develop a computationally inexpensive methodology for predicting molecule size distributions in hydrocarbon pyrolysis.
To apply this method to conditions relevant to icy planetary interiors.

Main Methods:

Utilized an original ten-reaction model.
Incorporated the configurational model from random graph theory.
Simulated pyrolysis across temperatures from 3200 to 5000 K.

Main Results:

The methodology accurately predicts molecule size distributions for various initial compositions.
Small molecule size distributions are particularly well predicted.
The size of the largest molecule is accurately predicted for moderately sized molecules.

Conclusions:

The proposed methodology offers an efficient and accurate way to model hydrocarbon pyrolysis.
This approach enhances our understanding of chemical processes within icy planetary bodies.
The model provides valuable insights into the composition of planetary interiors under extreme conditions.