Investigating the Effects of Basis Set on Metal–Metal and Metal–Ligand Bond Distances in Stable Transition Metal Carbonyls: Performance of Correlation Consistent Basis Sets with 35 Density Functionals

Density functional theory (DFT) is a widely used method for predicting equilibrium geometries of organometallic compounds involving transition metals, with a wide choice of functional and basis set combinations. A study of the role of basis set size in predicting the structural parameters can be insightful with respect to the effectiveness of using small basis sets to optimize larger molecular systems. For many organometallic systems, the metal–metal and metal–carbon distances are the most important structural features. In this study, we compare the equilibrium metal–ligand and metal–metal distances of six transition metal carbonyl compounds predicted by the Hood-Pitzer double-ζ polarization (DZP) basis set, against those predicted employing the standard correlation consistent cc-pVXZ (X = D,T,Q) basis sets, for 35 different DFT methods. The effects of systematically increasing the basis set size on the structural parameters are carefully investigated. The Mn–Mn bond distance in Mn2(CO)10 shows a greater dependence on basis set size compared to the other M–M bonds. However, the DZP predictions for re(Mn–Mn) are closer to experiment than those obtained with the much larger cc-pVQZ basis set. Our results show that, in general, DZP basis sets predict structural parameters with an accuracy comparable to the triple and quadruple-ζ basis sets. This finding is very significant, because the quadruple-ζ basis set for Mn2(CO)10 includes 1308 basis functions, while the equally effective double-ζ set (DZP) includes only 366 basis functions. Overall, the DZP M06-L method predicts structures that are very consistent with experiment

Automated theoretical chemical kinetics: Predicting the kinetics for the initial stages of pyrolysis

Large scale implementation of high level computational theoretical chemical kinetics offers the prospect for dramatically improving the fidelity of combustion chemical modeling. To facilitate such efforts, we have developed a suite of codes, collectively referred to as AutoMech, that allow for the automatic prediction of the kinetics for large sets of reactions via ab initio transition-state-theory based master-equation calculations. The primary input is simply the mechanism, a dictionary relating chemically identifiable species descriptors (e.g., SMILES or InChIs) to species labels in the mechanism, and a specification of the electronic structure and transition state theory models to be implemented. Here we illustrate the current utility of AutoMech through a study of the initial stages of pyrolysis for 3 sets of fuels: sequences of alkanes, alcohols, and aldehydes. For simplicity, the analysis focuses on abstractions from the fuel by H, CH3, and OH, and the decomposition of the resulting radicals. Altogether, there are a total of 166 input channels in these sets (more than 363 forward reactions when expanded to the full set of elementary reactions). The code successfully produces high quality rate estimates (with apparent uncertainties less than a factor of two in limited comparisons with experiment) for >95% of these. For the radical decomposition reactions, the analysis includes predictions for the pressure dependence of the kinetics. This wide-ranging exploration illustrates (i) the effect of different levels of prediction on the expected accuracy, (ii) the branching between abstractions at different sites for different abstractors, (iii) the dependence of the rates on the chemical structure, and (iv) the variation in radical stabilities across chemical families. These results, as well as the demonstrated feasibility of the methodology, should find further utility in the development of accurate rate expressions for arbitrary fuels

Investigating the Effects of Basis Set on Metal–Metal and Metal–Ligand Bond Distances in Stable Transition Metal Carbonyls: Performance of Correlation Consistent Basis Sets with 35 Density Functionals

Density functional theory (DFT) is a widely used method for predicting equilibrium geometries of organometallic compounds involving transition metals, with a wide choice of functional and basis set combinations. A study of the role of basis set size in predicting the structural parameters can be insightful with respect to the effectiveness of using small basis sets to optimize larger molecular systems. For many organometallic systems, the metal–metal and metal–carbon distances are the most important structural features. In this study, we compare the equilibrium metal–ligand and metal–metal distances of six transition metal carbonyl compounds predicted by the Hood-Pitzer double-ζ polarization (DZP) basis set, against those predicted employing the standard correlation consistent cc-pVXZ (X = D,T,Q) basis sets, for 35 different DFT methods. The effects of systematically increasing the basis set size on the structural parameters are carefully investigated. The Mn–Mn bond distance in Mn₂(CO)₁₀ shows a greater dependence on basis set size compared to the other M–M bonds. However, the DZP predictions for r_<i>e</i>(Mn–Mn) are closer to experiment than those obtained with the much larger cc-pVQZ basis set. Our results show that, in general, DZP basis sets predict structural parameters with an accuracy comparable to the triple and quadruple-ζ basis sets. This finding is very significant, because the quadruple-ζ basis set for Mn₂(CO)₁₀ includes 1308 basis functions, while the equally effective double-ζ set (DZP) includes only 366 basis functions. Overall, the DZP M06-L method predicts structures that are very consistent with experiment