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On a comprehensive database with 1,644 datapoints, covering several aspects of main‐group as well as of transition metal chemistry, we assess the performance of 60 density functional approximations (DFA), among them 36 double hybrids (DH). All calculations are performed using a Slater type orbital (STO) basis set of triple‐ζ (TZ) quality and the highly efficient pair atomic resolution of the identity approach for the exchange‐ and Coulomb‐term of the KS matrix (PARI‐K and PARI‐J, respectively) and for the evaluation of the MP2 energy correction (PARI‐MP2). Employing the quadratic scaling SOS‐AO‐PARI‐MP2 algorithm, DHs based on the spin‐opposite‐scaled (SOS) MP2 approximation are benchmarked against a database of large molecules. We evaluate the accuracy of STO/PARI calculations for B3LYP as well as for the DH B2GP‐PLYP and show that the combined basis set and PARI‐error is comparable to the one obtained using the well‐known def2‐TZVPP Gaussian‐type basis set in conjunction with global density fitting. While quadruple‐ζ (QZ) calculations are currently not feasible for PARI‐MP2 due to numerical issues, we show that, on the TZ level, Jacob's ladder for classifying DFAs is reproduced. However, while the best DHs are more accurate than the best hybrids, the improvements are less pronounced than the ones commonly found on the QZ level. For conformers of organic molecules and noncovalent interactions where very high accuracy is required for qualitatively correct results, DHs provide only small improvements over hybrids, while they still excel in thermochemistry, kinetics, transition metal chemistry and the description of strained organic systems. [ABSTRACT FROM AUTHOR]

In this article, we document a new implementation of the fuzzy cells scheme for numerical integration in polyatomic systems [Becke, J. Chem. Phys. 1998, 88, 2547] and compare its efficiency and accuracy with respect to an integration scheme based on the Voronoi space partitioning. We show that the accuracy of both methods is comparable, but that the fuzzy cells scheme is better suited for geometry optimization. For this method, we also introduce the locally dense grid concept and present a proof-of-concept application. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Photocatalytic water oxidation remains the bottleneck in many artificial photosynthesis devices. The efficiency of this challenging process is inherently linked to the thermodynamic and electronic properties of the chromophore and the water oxidation catalyst (WOC). Computational investigations can facilitate the search for favorable chromophore‐catalyst combinations. However, this remains a demanding task due to the requirements on the computational method that should be able to correctly describe different spin and oxidation states of the transition metal, the influence of solvation and the different rates of the charge transfer and water oxidation processes. To determine a suitable method with favorable cost/accuracy ratios, the full catalytic cycle of a molecular ruthenium based WOC is investigated using different computational methods, including density functional theory (DFT) with different functionals (GGA, Hybrid, Double Hybrid) as well as the semi‐empirical tight binding approach GFN‐xTB. A workflow with low computational cost is proposed that combines GFN‐xTB and DFT and provides reliable results. GFN‐xTB geometries and frequencies combined with single‐point DFT energies give free energy changes along the catalytic cycle that closely follow the full DFT results and show satisfactory agreement with experiment, while significantly decreasing the computational cost. This workflow allows for cost efficient determination of energetic, thermodynamic and dynamic properties of WOCs. [ABSTRACT FROM AUTHOR]

A new implementation of frozen-density embedding (FDE) in the Amsterdam Density Functional (ADF) program package is presented. FDE is based on a subsystem formulation of density-functional theory (DFT), in which a large system is assembled from an arbitrary number of subsystems, which are coupled by an effective embedding potential. The new implementation allows both an optimization of all subsystems as a linear-scaling alternative to a conventional DFT treatment, the calculation of one active fragment in the presence of a frozen environment, and intermediate setups, in which individual subsystems are fully optimized, partially optimized, or completely frozen. It is shown how this flexible setup can facilitate the application of FDE in multilevel simulations. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008 [ABSTRACT FROM AUTHOR]

We report a QM augmented QM/MM study on the coordination of the tetrahydroxouranylate ion in aqueous solution. QM/MM geometry optimizations followed by full QM single-point calculations on the optimized structures show that a hexa-coordinated structure is more stable than the hepta-coordinated structure by 43 kJ/mol. Charge transfer of the tetrahydroxouranylate to the solvating water molecules is relatively modest, and can be modeled by including a solvation layer consisting of 12 explicit water molecules. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 1156–1162, 2006 [ABSTRACT FROM AUTHOR]

We present a new implementation of analytical gradients for subsystem density-functional theory (sDFT) and frozen-density embedding (FDE) into the Amsterdam Density Functional program (ADF). The underlying theory and necessary expressions for the implementation are derived and discussed in detail for various FDE and sDFT setups. The parallel implementation is numerically verified and geometry optimizations with different functional combinations (LDA/TF and PW91/PW91K) are conducted and compared to reference data. Our results confirm that sDFT-LDA/TF yields good equilibrium distances for the systems studied here (mean absolute deviation: 0.09 Å) compared to reference wave-function theory results. However, sDFT-PW91/PW91k quite consistently yields smaller equilibrium distances (mean absolute deviation: 0.23 Å). The flexibility of our new implementation is demonstrated for an HCN-trimer test system, for which several different setups are applied. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Applications of quantum chemistry have evolved from single or a few calculations to more complicated workflows, in which a series of interrelated computational tasks is performed. In particular multiscale simulations, which combine different levels of accuracy, typically require a large number of individual calculations that depend on each other. Consequently, there is a need to automate such workflows. For this purpose we have developed P YA DF, a scripting framework for quantum chemistry. P YA DF handles all steps necessary in a typical workflow in quantum chemistry and is easily extensible due to its object-oriented implementation in the Python programming language. We give an overview of the capabilities of P YA DF and illustrate its usefulness in quantum-chemical multiscale simulations with a number of examples taken from recent applications. © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011 [ABSTRACT FROM AUTHOR]