Nitromethane Decomposition via Automated Reaction Discovery and an Ab Initio Corrected Kinetic Model

Area of Science:

• Computational Chemistry
• Chemical Kinetics
• Reaction Dynamics

Background:

• Kinetic models are crucial for understanding complex chemical processes like nitromethane decomposition.
• Accurate kinetic modeling requires detailed reaction pathways and rate parameters, often computationally expensive to obtain.

Purpose of the Study:

• To systematically construct computationally affordable kinetic models for nitromethane decomposition.
• To integrate accelerated simulations with accurate quantum chemical data for improved model fidelity.

Main Methods:

• Utilized accelerated molecular dynamics simulations with the ReaxFF reactive force field to discover reaction pathways.
• Optimized reaction paths and introduced a reaction barrier correction scheme combining ReaxFF and density functional theory (DFT) data.
• Validated the kinetic models against experimental data in various thermodynamic regimes.

Main Results:

• Developed a computationally efficient method for generating kinetic models from in silico data.
• Achieved predictions for gas-phase CO and NO concentrations and high-pressure induction times comparable to experimental results.
• Identified fundamental decomposition reactions governing nitromethane behavior under different conditions.

Conclusions:

• The proposed methodology enables the construction of accurate and affordable kinetic models for complex chemical systems.
• The validated models provide insights into the key reaction pathways of nitromethane decomposition.
• This approach offers a viable route for advancing the understanding of energetic materials and combustion processes.