First-principles-based reaction kinetics from reactive molecular dynamics simulations: Application to hydrogen...

Area of Science:

• Computational Chemistry
• Chemical Engineering
• Materials Science

Background:

• Accurate kinetic parameters are crucial for optimizing technologies like combustion and chemical vapor deposition.
• Quantum mechanics (QM) provides accuracy but is computationally prohibitive for large-scale simulations.
• Bridging atomistic detail with macroscopic behavior requires efficient methods for extracting reaction kinetics.

Purpose of the Study:

• To present a vision for using in silico methods to extract reaction mechanisms and kinetic parameters for complex condensed-phase chemical processes.
• To enable analytic descriptions of chemical system evolution for process optimization.
• To demonstrate the practicality of extracting reaction kinetics from reactive molecular dynamics (RMD) simulations.

Main Methods:

• Utilizing reactive force fields (ReaxFF) trained to QM for reactive molecular dynamics (RMD) simulations.
• Developing an automated strategy (RMD2Kin, specifically ReaxMD2Kin for QM-ReaxFF) to extract mechanisms and rate parameters.
• Employing RMD to bridge the gap between QM accuracy and the scales needed for kinetic analysis.

Main Results:

• Demonstrated the practicality of extracting reaction mechanisms and kinetics from RMD simulations.
• Showcased an automated approach for obtaining kinetic information without prior chemical knowledge.
• Established a proof of concept for the RMD2Kin methodology.

Conclusions:

• The developed in silico approach (RMD2Kin) is practical for extracting reaction mechanisms and kinetics.
• This method allows for the integration of detailed reaction chemistry into larger-scale simulations.
• The strategy offers a pathway to optimize reactive processes and avoid unwanted byproducts.