Smart Reaction Templating: A Graph-Based Method for Automated Molecular Dynamics Input Generation

Area of Science:

• Computational Chemistry
• Materials Science
• Molecular Dynamics Simulations

Background:

• Manual creation of reaction templates for molecular dynamics simulations is labor-intensive.
• Accurate modeling of chemical reactions requires detailed pre- and postreaction templates.

Purpose of the Study:

• To develop an automated algorithm for generating reaction templates for the LAMMPS REACTION package.
• To reduce manual effort in preparing molecular dynamics simulations of chemical reactions.

Main Methods:

• Utilized graph-theoretical principles and subgraph isomorphism techniques.
• Represented molecular systems as mathematical graphs for automated analysis.
• Developed a Python-based algorithm for template generation.

Main Results:

• Successfully automated the identification of conserved molecular domains, reaction sites, and atom mappings.
• Validated the algorithm on poly addition, poly condensation, and chain polymerization.
• Optimized templates for computational efficiency by retaining essential reactive domains.

Conclusions:

• The algorithm significantly reduces manual effort in generating reaction templates.
• Ensures scalability and consistency for high-throughput computational chemistry and materials science.
• Provides a foundation for future enhancements, including integration with quantum mechanical calculations.