Reactive symbol sequences for a model of hydrogen combustion
Mohammad Alaghemandi1, Jason R Green2
1Department of Chemistry, University of Massachusetts Boston, Boston, MA 02125, USA. jason.green@umb.edu.
Physical Chemistry Chemical Physics : PCCP
|January 6, 2016
Summary
We developed a new method to simplify complex chemical reactions, like hydrogen combustion, by analyzing symbolic dynamics. This approach reveals how reaction time scales and chain lengths depend on temperature and density.
Area of Science:
- Chemical kinetics
- Molecular dynamics
- Computational chemistry
Background:
- Macroscopic chemical disequilibrium arises from microscopic molecular dynamics.
- Temporal patterns and statistics of chemical species encode dynamical and kinetic information.
- Analyzing these patterns can simplify complex reaction systems.
Purpose of the Study:
- To define and analyze chemically-informed symbolic dynamics for classical molecular dynamics.
- To investigate hydrogen combustion using this symbolic dynamics approach.
- To understand how reaction time scales and chain lengths are influenced by system parameters.
Main Methods:
- Generated sequences of chemical species using reactive molecular dynamics simulations.
- Derived probability distributions for sequence observables, including reaction time scales and chain lengths.
- Analyzed the dependence of these observables on chain length, temperature, and density.
Main Results:
- Symbolic dynamics analysis revealed strong dependencies of time scales and sequence likelihood on chain length, temperature, and density.
- Temperature exhibited differential effects on chain length uncertainty for hydrogen versus oxygen sequences.
- The method effectively reduces chemical complexity from atomistic to molecular levels.
Conclusions:
- Chemically-informed symbolic dynamics offers a powerful tool for analyzing complex reaction systems.
- This approach simplifies the representation of molecular dynamics, aiding in understanding chemical kinetics.
- The method shows potential for application to more intricate chemical reaction networks.
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