DFT-based Green's function pathways model for prediction of bridge-mediated electronic coupling.

Area of Science:

• Computational Chemistry
• Theoretical Chemistry
• Quantum Chemistry

Background:

• Accurate prediction of electron transfer rates is crucial for understanding chemical reactions and designing new materials.
• Existing methods often face a trade-off between accuracy and computational cost.
• Predicting electronic coupling and tunneling pathways in complex systems remains a significant challenge.

Purpose of the Study:

• To develop an accurate and computationally inexpensive model for predicting electron transfer rates.
• To enable quantitative predictions of electronic coupling and tunneling pathways.
• To provide a flexible framework for analyzing electron transfer in donor-bridge-acceptor systems.

Main Methods:

• Development of a density functional theory-based Green's function pathway model.
• Application of the model to organic and biological systems.
• Benchmarking against experimental data and comparison across different computational parameters (density functional type, basis set, localization scheme).
• Adaptation of a localized molecular orbital Green's function pathway method (LMO-GFM).

Main Results:

• Electronic coupling predictions within 0.1 eV of experimental values for moderately large systems.
• Demonstration of modest computational expense.
• Quantitative prediction of electronic coupling and tunneling pathways in covalently bound donor-bridge-acceptor systems.
• Intuitive understanding of electron tunneling through through-bond and through-space interactions.

Conclusions:

• The developed Green's function pathway model offers a significant advancement in predicting electron transfer rates.
• The model provides accurate and cost-effective electronic coupling and tunneling pathway predictions.
• The LMO-GFM adaptation enhances the interpretability of electron tunneling mechanisms.