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Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

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Multilevel Approaches within the Local Pair Natural Orbital Framework.

Manuel Sparta¹, Marius Retegan¹, Peter Pinski¹

¹Max Planck Institute for Chemical Energy Conversion, Stiftstrasse 34-36, D-45470 Mülheim an der Ruhr, Germany.

Journal of Chemical Theory and Computation

|June 8, 2017

Summary

This study introduces a new fragmented approach for the linear-scaling local coupled cluster method, DLPNO-CCSD(T). This method allows for varying accuracy levels across different parts of large molecular systems, optimizing computational resources for complex chemical calculations.

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Area of Science:

Quantum Chemistry
Computational Chemistry
Method Development

Background:

Linear-scaling local coupled cluster methods like DLPNO-CCSD(T) enable accurate calculations for large systems.
Accuracy is controlled by truncation thresholds, but higher accuracy increases computational cost.
Many applications require high accuracy only in specific regions of a molecular system.

Purpose of the Study:

To develop a fragmented approach for DLPNO-CCSD(T) that allows for varied accuracy levels across different molecular parts.
To enable focused computational resource allocation for regions of interest.
To provide a flexible method for large-scale quantum chemical calculations.

Main Methods:

Extension of the native DLPNO method to fragment molecular systems.
Application of different truncation thresholds or levels of theory for inter-fragment interactions.
Implementation within the DLPNO-CCSD(T) framework.

Main Results:

Successful implementation of the fragmented DLPNO-CCSD(T) approach.
Demonstrated applicability to dimerization energies, potential energy surfaces, enantiomeric excess, and drug-DNA binding.
Validation of the method's ability to balance accuracy and computational cost.

Conclusions:

The fragmented DLPNO-CCSD(T) method offers a powerful strategy for efficient quantum chemical calculations on large systems.
This approach allows users to tailor computational accuracy based on chemical intuition and system regions.
Provides guidance for setting up calculations using this novel, resource-optimized method.