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Two-Photon Absorption Strengths of Small Molecules: Reference CC3 Values and Benchmarks
Carmelo Naim1, Robert Zaleśny2, Denis Jacquemin1,3
1Nantes Université, CNRS, CEISAM UMR 6230, F-44000 Nantes, France.
We generated accurate two-photon transition strengths for small molecules using advanced quantum chemistry methods. This dataset benchmarks various computational approaches, aiding future molecular property predictions.
Area of Science:
- Computational chemistry
- Molecular spectroscopy
- Quantum mechanics
Background:
- Accurate calculation of molecular properties is crucial for understanding chemical phenomena.
- Two-photon absorption (TPA) is a significant photophysical process with applications in various fields.
- High-accuracy computational methods are needed to reliably predict TPA strengths.
Purpose of the Study:
- To create a comprehensive dataset of highly accurate two-photon transition strengths for standard small molecules.
- To provide a benchmark for evaluating the performance of various computational methods for TPA calculations.
- To assess the impact of system size, transition character, and computational approximations on prediction accuracy.
Main Methods:
- Reference TPA strengths calculated using the quadratic response implementation of the third-order coupled cluster method including iterative triples (Q-CC3).
- Aug-cc-pVTZ and aug-cc-pVDZ atomic basis sets were employed, with basis set effects discussed.
- Evaluated alternative wavefunction methods: quadratic response and equation-of-motion CCSD approximations, Q-CC2, and I-ADC2.
- Assessed time-dependent density functional theory (TD-DFT) using five common exchange-correlation functionals.
Main Results:
- A dataset of 82 singlet transitions (Rydberg, valence, double excitations) was generated.
- Quantitative assessment of benchmarked methods revealed varying performance based on system size, transition intensity, and type.
- Insights into the accuracy and limitations of different computational approaches for predicting TPA strengths were obtained.
Conclusions:
- The Q-CC3 method provides highly accurate reference values for TPA strengths.
- The developed dataset serves as a valuable resource for validating and improving computational methods.
- Understanding method performance is key for selecting appropriate computational strategies for TPA calculations.
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