Extending the range and physical accuracy of coarse-grained models: Order parameter dependent interactions

Area of Science:

• Computational chemistry
• Materials science
• Statistical mechanics

Background:

• Coarse-grained (CG) models simplify complex systems using collective variables (order parameters).
• Standard CG models often rely on pairwise interactions, which can be insufficient for accurately representing structural distributions, especially in interfacial systems.
• Limitations arise when pairwise interactions fail to capture the nuances of free energy surfaces.

Purpose of the Study:

• To introduce an approach for expanding the basis sets in multiscale coarse-graining (MS-CG) methodology by including order parameters.
• To investigate the effectiveness of additive local and global order parameters in improving CG model descriptions of interfacial systems.
• To assess the performance of single-site CG models for methanol and acetonitrile in liquid-vapor coexistence and confined geometries.

Main Methods:

• Developed an extension to the MS-CG methodology to incorporate order parameters.
• Employed additive local order parameters (e.g., density) and global order parameters (e.g., distance from a hard wall).
• Studied methanol and acetonitrile liquid-vapor coexistence and acetonitrile confined by hard walls using single-site CG models.

Main Results:

• The inclusion of order parameters significantly enhanced the accuracy of CG models in reproducing structural properties of interfacial systems.
• Compared to models using only pairwise interactions, the enhanced models showed improved agreement with fine-grained (FG) reference data.
• Both local (density) and global (distance from wall) order parameters demonstrated effectiveness in improving model performance.

Conclusions:

• Order parameters are crucial for improving the accuracy of CG models, particularly for interfacial phenomena.
• The MS-CG methodology can be effectively expanded to include order parameters, leading to better structural predictions.
• The developed approach offers a pathway to more reliable CG simulations of complex fluids and confined systems.