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This study introduces a reactive coarse-grained (RCG) method to model chemical reactions. The RCG method adapts bonding topology, enabling accurate simulations of molecular transformations previously challenging for coarse-grained models.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Chemical Physics

Background:

  • Coarse-grained (CG) models simulate systems at long time and length scales.
  • Current CG models lack the ability to represent chemical reactions due to fixed bonding topologies.
  • Developing adaptive CG models is crucial for simulating reactive systems.

Purpose of the Study:

  • To develop a reactive coarse-grained (RCG) method capable of adapting its bonding topology.
  • To enable CG models to capture chemical reaction dynamics.
  • To bridge the gap between atomistic accuracy and CG efficiency for reactive systems.

Main Methods:

  • A novel reactive coarse-grained (RCG) method was developed.
  • The RCG method utilizes all-atom (AA) data to parameterize CG models.
  • The method allows for dynamic changes in bonding topology and site-site interactions.
  • Applied to SN2 reactions in methanol solvent.

Main Results:

  • The RCG method successfully modeled chemical reactions by adapting bonding topology.
  • Calculated potential of mean force (PMF) results closely matched fully atomistic (AA) simulations.
  • Accurate representation of SN2 reactions, including an asymmetric case, was achieved.

Conclusions:

  • The developed RCG method enables CG models to simulate chemical reactions.
  • This approach offers a computationally efficient way to study reactive molecular systems.
  • The RCG method provides a promising avenue for advancing molecular simulations of chemical transformations.