Potential models for the simulation of methane adsorption on graphene: development and CCSD(T) benchmarks

Area of Science:

• Computational Chemistry
• Materials Science
• Physical Chemistry

Background:

• Accurate molecular modeling requires reliable force fields.
• Graphene-methane interactions are crucial for understanding gas adsorption and separation.
• Previous models lacked sufficient accuracy for complex systems.

Purpose of the Study:

• To develop and validate accurate force fields for the graphene-methane system.
• To evaluate different atomistic and pseudo-atom models with various charge schemes.
• To benchmark model performance against high-level quantum chemical calculations and experimental data.

Main Methods:

• Density Functional Theory (DFT) calculations for interaction energies.
• Coupled Cluster with Single, Double, and Triple Excitations (CCSD(T)) for benchmarking.
• Optimization of force field parameters against DFT data.
• Validation using self-diffusion coefficients and experimental interaction energies.

Main Results:

• Both pseudo-atom and full atomistic models accurately describe graphene-methane interactions.
• Optimized potentials correctly predict interaction energies for methane dimers and various molecular orientations.
• Atom-atom potentials with specific charge schemes (no-charge, Hirshfeld) accurately predict self-diffusion coefficients.
• Predicted graphene-methane interaction energy (2.89 kcal/mol) closely matches experimental values (3.00 kcal/mol).

Conclusions:

• Developed force fields provide reliable descriptions of graphene-methane systems.
• The models are suitable for simulating dynamic properties like self-diffusion.
• The study offers accurate computational tools for materials science and chemical engineering applications.