Wave-function frozen-density embedding: Approximate analytical nuclear ground-state gradients | JoVE Visualize

Area of Science:

Computational Chemistry
Quantum Chemistry
Theoretical Chemistry

Background:

Accurate molecular geometry optimization is crucial for understanding chemical properties and reactions.
Traditional methods for large systems are computationally expensive, limiting their application.
Frozen Density Embedding (FDE) offers a more efficient way to model complex molecular environments.

Purpose of the Study:

To derive and implement approximate analytical nuclear gradients for uncoupled frozen density embedding (FDEu).
To enable efficient geometry optimizations for a central molecule interacting with a large, fixed environment.
To assess the accuracy and computational efficiency of the developed FDEu approach for various chemical systems.

Main Methods:

Derivation of approximate analytical nuclear ground-state uncoupled frozen density embedding (FDEu) gradients.
Implementation within the KOALA program for Resolution of Identity (RI) variants of RICC2 and DFT.
Neglect of computationally expensive orbital-exchange terms for efficiency.
Inclusion of dispersion corrections for DFT-based FDE interactions.

Main Results:

Successful geometry optimizations for single molecules in complex environments using RICC2-in-RICC2, RICC2-in-DFT, and DFT-in-DFT FDE levels.
High accuracy demonstrated in case studies: adenine-thymine (max error ~0.08 Å) and CO on MgO surface (max error ~0.1 Å) compared to supermolecular calculations.
Significant computational speed-up achieved compared to conventional supermolecular RICC2 methods, especially with a moderate number of environment molecules.

Conclusions:

The developed FDEu gradient approach provides an accurate and computationally efficient method for molecular geometry optimizations in complex environments.
This method significantly outperforms conventional coupled cluster calculations for such systems, enabling studies of larger and more complex molecular interactions.
The implementation in the KOALA program facilitates practical application in various fields of computational chemistry.