Vertical valence ionization potential benchmarks from equation-of-motion coupled cluster theory and QTP functionals.

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Materials Science

Background:

• Ionization potential (IP) is key for redox chemistry, charge transfer, and molecular electronics.
• Accurate theoretical IP prediction is vital for virtual materials design.
• Vertical IPs are important for developing many-body Green's function methods, density functionals, and semiempirical methods.

Purpose of the Study:

• To validate the accuracy and robustness of the IP-EOM-CCSD method for predicting vertical valence IPs.
• To generate a large, consistent dataset of theoretical vertical valence IPs for benchmarking.
• To assess the performance of density functional approximations and the extended Koopmans' theorem approach using the generated benchmark set.

Main Methods:

• Calculated over 1468 vertical valence IPs for 155 molecules using IP-EOM-CCSD.
• Compared calculated IPs against experimental data and higher-order coupled cluster theory.
• Utilized Bartlett's IP-eigenvalue theorem and the extended Koopmans' theorem approach for method assessment.

Main Results:

• IP-EOM-CCSD demonstrates high accuracy and robustness for vertical valence IP prediction, with detailed discussion of outliers.
• A comprehensive benchmark set of theoretical vertical valence IPs was generated, addressing a lack of reliable reference data.
• The QTP family of density functionals showed remarkable accuracy and cost-effectiveness compared to IP-EOM-CCSD.

Conclusions:

• IP-EOM-CCSD is a reliable method for calculating vertical valence IPs.
• The generated benchmark dataset serves as a valuable resource for computational chemistry.
• QTP functionals offer a promising, accurate, and efficient alternative for IP calculations.