Optimization and transferability of non-electrostatic repulsion in the polarizable density embedding model.

Area of Science:

• Computational chemistry
• Quantum mechanics
• Molecular modeling

Background:

• Embedding techniques combined with response theory are effective for calculating molecular properties and excited states in large systems.
• The polarizable density embedding (PDE) model enhances accuracy by including explicit electronic densities of the nearest environment molecules, improving short-distance intermolecular interaction descriptions.

Purpose of the Study:

• To determine an optimal scaling factor for the non-electrostatic repulsion term in the PDE model.
• To validate the improved PDE model by comparing its results with full quantum-mechanical calculations.

Main Methods:

• Investigated intermolecular interaction energies using embedding techniques and compared them to reference interaction energies from full quantum-mechanical calculations.
• Determined an optimal scaling factor for the non-electrostatic repulsion term in the PDE model.
• Applied the optimized PDE model to calculate ground- and excited-state properties of molecules in polarizable environments.

Main Results:

• An optimal scaling factor for the non-electrostatic repulsion term was identified.
• The optimized PDE model demonstrated improved accuracy in describing intermolecular interactions at short distances.
• Calculations of molecular properties in polarizable environments using the improved PDE model showed good agreement with reference data.

Conclusions:

• The scaling of the non-electrostatic repulsion term is crucial for accurate intermolecular interaction energies in the PDE model.
• The optimized PDE model provides a more reliable approach for studying molecular properties and excited states in condensed phases.
• This work advances the application of embedding methods for large molecular systems, including solutions and proteins.