Abstract
Time-dependent density functional theory is thoroughly benchmarked for the predictive calculation of UV–vis spectra of porphyrin derivatives. With the aim to provide an approach that is computationally feasible for large-scale applications such as biological systems or molecular framework materials, albeit performing with high accuracy for the Q-bands, the results given by various computational protocols, including basis sets, density-functionals (including gradient corrected local functionals, hybrids, double hybrids and range-separated functionals), and various variants of time-dependent density functional theory, including the simplified Tamm–Dancoff approximation, are compared. An excellent choice for these calculations is the range-separated functional CAM-B3LYP in combination with the simplified Tamm–Dancoff approximation and a basis set of double-ζ quality def2-SVP (mean absolute error [MAE] of ≈0.05 eV). This is not surpassed by more expensive approaches, not even by double hybrid functionals, and solely systematic excitation energy scaling slightly improves the results (MAE ≈0.04 eV).
Original language | English |
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Article number | 1900192 |
Journal | Advanced Theory and Simulations |
Volume | 3 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2020 Jan 1 |
Bibliographical note
Funding Information:This work was supported by the Deutsche Forschungsgemeinschaft (DFG) under the COORNETs Priority Project SPP 1928 (HE 3543/30-1). The computations were performed on a Taurus cluster at the Center of Information Services and ZIH at TU Dresden. T.H. thanks Prof. Carlo Adamo (ParisTech) for fruitful discussions.
Funding Information:
This work was supported by the Deutsche Forschungsgemeinschaft (DFG) under the COORNETs Priority Project SPP 1928 (HE 3543/30‐1). The computations were performed on a Taurus cluster at the Center of Information Services and ZIH at TU Dresden. T.H. thanks Prof. Carlo Adamo (ParisTech) for fruitful discussions.
Publisher Copyright:
© 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Numerical Analysis
- Modelling and Simulation
- General