The explicit bonding reaction ensemble Monte Carlo method.

Area of Science:

• Computational chemistry
• Macromolecular science
• Chemical physics

Background:

• Simulating reversible bonding reactions in macromolecular systems is computationally challenging.
• Existing methods struggle with modeling the formation and breaking of bonds within macromolecules.

Purpose of the Study:

• To introduce and validate a novel computational method, explicit bonding Reaction ensemble Monte Carlo (eb-RxMC), for simulating reversible bonding reactions in macromolecules.
• To demonstrate the method's capability in accurately sampling both reaction and configuration spaces.

Main Methods:

• Developed the explicit bonding Reaction ensemble Monte Carlo (eb-RxMC) method by modifying the reaction ensemble approach.
• Implemented bond creation/deletion between existing particles instead of particle insertion/deletion.
• Biased reaction sampling within an inclusion radius for coupling with molecular dynamics.
• Validated the method using ideal dimerization and polycondensation reactions with known analytical solutions.

Main Results:

• eb-RxMC accurately reproduced analytical results for dimerization reactions, matching degrees of conversion across various conditions.
• Simulation accuracy was independent of inclusion radius choice or bond potential stiffness.
• The method correctly predicted the degree of polymerization and end-to-end distance distributions for polycondensation reactions.
• Demonstrated accurate sampling of both reaction and configuration spaces.

Conclusions:

• The explicit bonding Reaction ensemble Monte Carlo (eb-RxMC) method is a validated tool for simulating reversible bonding in macromolecules.
• This method enables accurate modeling of complex macromolecular systems, paving the way for future research.
• eb-RxMC successfully bridges the gap between reaction dynamics and conformational sampling in complex molecular systems.