The polarizable embedding coupled cluster method.

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Molecular Dynamics

Background:

• Accurate quantum mechanical (QM) calculations are computationally expensive for large systems.
• Molecular mechanics (MM) methods are efficient but lack electronic detail.
• Combined QM/MM methods offer a balance, but polarizable embedding (PE) QM/MM with advanced QM methods is challenging.

Purpose of the Study:

• To develop and implement a novel QM/MM method combining self-consistent PE with coupled cluster (CC) theory.
• To enable efficient calculation of molecular properties, including excitation energies and absorption spectra, in polarizable MM environments.
• To investigate the role of electronic correlation and environmental effects on molecular properties and spectral characteristics.

Main Methods:

• Formulation of a QM/MM method using a self-consistent PE scheme.
• Application of coupled cluster (CC) methods for the QM region, incorporating electrostatic and polarization effects.
• Development of efficient CC density-like intermediates for low computational cost QM/MM terms.
• Implementation of linear and quadratic response functions for molecular properties.
• Integration with molecular dynamics (MD) for statistical averaging of solvated properties.

Main Results:

• Efficient calculation of excitation energies, one- and two-photon absorption properties, polarizabilities, and hyperpolarizabilities.
• Demonstrated low computational cost of QM/MM terms with increasing MM sites.
• Systematic investigation of multipole and polarizability contributions to two-photon absorption in formamide solution.
• Application to a full protein (photoactive yellow protein) to study excitation energy shifts.

Conclusions:

• The new PE-QM/MM-CC method provides an efficient and accurate approach for studying electronic properties of molecules in condensed phases.
• The method successfully captures environmental effects, including polarization and correlation, crucial for accurate spectral predictions.
• This work advances the capability of computational chemistry for complex biological systems and photochemical processes.