Benchmarking ionization potentials and electron affinities of potential photovoltaic molecules using DFT/QTP
Hyunsik Kim1, Ajith Perera1, Rodrigo A Mendes1
1Quantum Theory Project, University of Florida, Gainesville, Florida 32611, USA.
Accurate prediction of ionization potentials (IPs) and electron affinities (EAs) is crucial for organic photovoltaic materials. QTP functionals combined with G0W0 corrections offer coupled-cluster accuracy at a fraction of the computational cost.
Area of Science:
- Computational chemistry
- Materials science
- Organic electronics
Background:
- Accurate prediction of ionization potentials (IPs) and electron affinities (EAs) is vital for designing organic photovoltaic (OPV) materials.
- Existing computational methods often face trade-offs between accuracy and computational cost.
Purpose of the Study:
- To evaluate the performance of various Kohn-Sham density functional theory (DFT) functionals, including the QTP family, for predicting IPs and EAs.
- To assess the impact of G0W0 corrections and frozen natural orbital (FNO) truncations on computational efficiency and accuracy.
- To compare DFT-based methods with coupled-cluster (CC) theory for IP and EA calculations.
Main Methods:
- Coupled-cluster (CC) theory, specifically ionization potentials (IPs)/electron affinities (EAs)-equation-of-motion (EOM)/coupled-cluster singles and doubles (CCSD) forms.
- Kohn-Sham density functional theory (DFT) using the QTP family and a range of other exchange-correlation functionals.
- One-shot G0W0 corrections applied to DFT results.
- Standard and tailored frozen natural orbital (FNO) truncations to reduce CC computational cost.
Main Results:
- Local and semi-local DFT functionals show significant errors in IP/EA predictions.
- Global hybrids and range-separated hybrids offer improved accuracy over simpler DFT functionals.
- QTP functionals demonstrate performance matching or exceeding other tested functionals.
- G0W0 corrections applied to DFT starting points bring orbital energies into close agreement with CC results.
- Tailored FNO truncations maintain CC accuracy while significantly reducing computational resources.
- QTP00 and G0W0@QTP00 workflows achieve near-CC quality predictions in under a day, drastically reducing computation time compared to full EA-EOM/CCSD.
Conclusions:
- QTP functionals, especially when combined with G0W0 corrections, provide a highly accurate and computationally efficient approach for predicting IPs and EAs.
- Tailored FNO truncations offer a viable strategy for accelerating CC calculations without sacrificing accuracy.
- These advancements can significantly guide the development of next-generation organic photovoltaic materials.
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