We present the new quantum chemistry program Serenity. It implements a wide variety of functionalities with a focus on subsystem methodology. The modular code structure in combination with publicly available external tools and particular design concepts ensures extensibility and robustness with a focus on the needs of a subsystem program. Several important features of the program are exemplified with sample calculations with subsystem density-functional theory, potential reconstruction techniques, a projection-based embedding approach and combinations thereof with geometry optimization, semi-numerical frequency calculations and linear-response time-dependent density-functional theory. © 2018 Wiley Periodicals, Inc.
Kohn-Sham density-functional theory (DFT) within the local-density approximation (LDA) or the generalized-gradient approximation (GGA) is known to fail for the correct description of London dispersion interactions. Often, not even bound potential-energy surfaces are obtained for van der Waals complexes, unless special correction schemes are employed. In contrast to that, there has been some evidence for the fact that subsystem-based density functional theory produces interaction energies for weakly bound systems which are superior to Kohn-Sham DFT results without dispersion corrections. This is usually attributed to an error cancellation between the approximate exchange-correlation and non-additive kinetic-energy functionals employed in subsystem DFT. Here, we investigate the accuracy of subsystem DFT for weakly interacting systems in detail, paying special attention to the shape of the potential-energy surfaces (PESs). Our test sets include the extensive S22x5 and S66x8 data sets. Our results indicate that subsystem DFT PESs strongly vary depending on the functional. LDA results are usually quite good, but behave differently from their KS counterparts. GGA results from the popular Perdew-Wang (PW91) set of functionals produce PESs that are often, but not in general overbinding. Results from Becke-Perdew (BP86) GGAs, by contrast, show the typical problems known from the corresponding KS results. We provide some preliminary results for empirical corrections for both PW91 and BP86 in subsystem DFT.
The HOMO–LUMO energy gap of germylenes bearing CNHC ∧Namido chelate ligands has been calculated in order to find suitable candidates for the activation of small molecules. Identified as promising structures, intramolecularly NHC-stabilized three-coordinate germylenes and stannylenes of type [E(CNHC ∧Namido)Cl] (E = Ge and Sn) were synthesized and characterized by NMR spectroscopy and X-ray crystallography. Chlorido substitution at the EII center for tert-butoxido or hexamethyl disilazide ligands was also performed. Chlorido abstraction with NaBArF gave rise to cationic two-coordinate germylenes and stannylenes.
We present a benchmark study on equilibrium structures optimized with subsystem density functional theory (sDFT) employing a new analytical gradient implementation in the program SERENITY. Geometry optimizations are performed on all complexes of the S22 [Jurečka et al. Phys. Chem. Chem. Phys. 2006, 8, 1985–1993] and A24 [Řezáč and Hobza. J. Chem. Theory Comput. 2013, 9, 2151–2155] test sets. While some combinations of approximate exchange-correlation (XC) and nonadditive kinetic-energy functionals (e.g., LDA/Thomas–Fermi or PW91/PW91k) more or less successfully mimic the effect of medium-range dispersion in these complexes, we also include the combination of BP86/LLP91. This functional reproduces the dispersion problem of the corresponding BP86 Kohn–Sham (KS-)DFT calculations and can hence successfully be corrected by empirical dispersion corrections developed for KS-DFT. We propose this as a robust and accurate strategy for sDFT geometry optimizations, which appears to be preferable over the previously used strategy relying on error cancellation between XC and nonadditive kinetic-energy functionals. In fact, the best results in our benchmark are obtained from BP86/LLP91 together with a D3-type dispersion correction. We also discuss the difference between our Gaussian-type orbital implementation in SERENITY and a Slater-type orbital based implementation in the Amsterdam density functional (ADF) program but only find small differences in most cases.
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