Analytical Energy Gradients for the Cluster-in-Molecule MP2 Method and Its Application to Geometry Optimizations of...

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry

Background:

• Accurate molecular geometry optimization is crucial for understanding chemical properties and reactions.
• Traditional methods like second order Møller-Plesset perturbation theory (MP2) become computationally expensive for large systems.
• The cluster-in-molecule (CIM) approach offers a potential solution for scaling these methods.

Purpose of the Study:

• To develop an efficient analytical energy gradient algorithm for the cluster-in-molecule (CIM) second order Møller-Plesset perturbation theory (MP2) method.
• To enable accurate geometry optimizations for large molecular systems.
• To assess the performance of the CIM-MP2 method against conventional MP2 calculations.

Main Methods:

• An analytical energy gradient algorithm was developed for the CIM-MP2 method.
• Gradient contributions from nonseparable two-body density matrix terms are extracted from localized cluster calculations.
• Density matrices for the entire system are constructed using contributions from all clusters.

Main Results:

• The CIM-MP2 method accurately reproduces conventional MP2 gradients and geometries for large systems.
• Tight CIM parameters are required for accurate gradients when using basis sets with diffuse functions.
• An optimized 174-atom oligopeptide structure using CIM-MP2 showed good agreement with experimental crystal structure.

Conclusions:

• The developed CIM-MP2 gradient algorithm provides an efficient and accurate approach for large molecular systems.
• This method allows for geometry optimizations of systems with hundreds of atoms on standard workstations.
• The CIM-MP2 method is a viable tool for computational chemists studying complex molecular structures.