Lewis Structures from Open Quantum Systems Natural Orbitals: Real Space Adaptive Natural Density Partitioning

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Chemical Physics

Background:

• Building accurate chemical models from electronic structure calculations is challenging due to high-dimensional wave function data.
• Existing methods like adaptive natural density partitioning (AdNDP) provide Lewis structures but require complex higher-order cumulant density matrices.
• A need exists for simpler, more accessible methods to translate electronic structure data into intuitive chemical language.

Purpose of the Study:

• To develop a novel real-space adaptive natural density partitioning (rs-AdNDP) method.
• To enable the construction of chemical models using only spatial information and the one-particle density matrix.
• To provide an efficient and robust technique for generating Lewis structures from quantum chemical calculations.

Main Methods:

• Utilized an open quantum systems (OQS) perspective.
• Employed rigorously defined OQS fragment natural orbitals.
• Developed a real-space adaptive natural density partitioning (rs-AdNDP) approach based on spatial information and the one-particle density matrix.

Main Results:

• Demonstrated that OQS fragment natural orbitals can form the basis for a consistent rs-AdNDP.
• Showcased that the rs-AdNDP method relies solely on accessible spatial information and the one-particle density matrix.
• Validated the rs-AdNDP approach as a computationally inexpensive, efficient, and robust technique.

Conclusions:

• The rs-AdNDP method successfully integrates electron counting arguments into the real-space domain.
• This new approach offers a simplified pathway to obtain intuitive Lewis structures from electronic structure calculations.
• The rs-AdNDP method presents a significant advancement in computational chemistry for model building.