MODELING ELECTRON DETACHMENT FROM METAL OXIDE CLUSTERS WITH EFFICIENT ELECTRONIC STRUCTURE METHODS

Photoelectron spectroscopy is a powerful technique for investigating the structure and reactivity of metal oxide clusters, which can serve as models of surface defect sites. Assigning photoelectron spectra typically requires corroborating computational simulations. Motivated by the complicated electronic structure often exhibited by these species that can challenge the quality of computational results using widely available quantum chemistry methods, our group has explored the development of efficient electronic structure models to describe photodetachment. This talk will describe these efforts and our lab’s recent applications of such models in investigations of various metal oxide clusters

Experimental and Theoretical Evidence for Nitrogen-Fluorine Halogen Bonding in Silver-Initiated Radical Fluorinations

We report experimental and computational evidence for nitrogen–fluorine halogen bonding in Ag­(I)-initiated radical C–H fluorinations. Simple pyridines form [N–F–N]+ halogen bonds with Selectfluor to facilitate single-electron reduction by catalytic Ag­(I). Pyridine electronics affect the extent of halogen bonding, leading to significant differences in selectivity between mono- and difluorinated products. Electronic structure calculations show that halogen bonding to various pyridines alters the single-electron reduction potential of Selectfluor, which is consistent with experimental electrochemical analysis. Multinuclear correlation NMR also provides spectroscopic evidence for pyridine halogen bonding to Selectfluor under ambient conditions

EXPLORING TRANSITION METAL CATALYZED REACTIONS VIA AB INITIO REACTION PATHWAYS

Author Institution: Gaussian, Inc., 340 Quinnipiac St., Bldg. 40, Wallingford, CT 06492The study and prediction of chemical reactivity is one of the most influential contributions of quantum chemistry. A central concept in the theoretical treatment of chemical reactions is the reaction pathway, which can be quite difficult to integrate accurately and efficiently. This talk will outline our developments in the integration of these pathways on ab initio potential energy surfaces. We will also describe results from recent studies on the kinetics of transition metal catalyzed reactions, including the importance of vibrational coupling to the reaction coordinate and the role of this coupling in catalytic rate enhancement

NEW METHODS FOR EXPLORING QM:MM POTENTIAL ENERGY LANDSCAPES

Author Institution: Gaussian, Inc., Wallingford, CT 06492, USAIn recent years, the applicability of quantum chemical methods for large system studies has been greatly enhanced by the development of hybrid QM:MM techniques. Despite these advancements, exploring the associated potential energy surfaces continues to present two key challenges. First, the QM energy and derivative evaluations may be too costly for simulations; and second, the system size for many QM:MM cases are too large to effectively store or use second-order information, an approach often used in QM studies to allow for larger integration steps and fewer QM evaluations of the potential energy surface. Our most recent work is focused on overcoming both computational bottlenecks. Using surface fitting models together with direct Hessian-vector and diagonalization algorithms, we are developing models that can accurately and efficiently explore QM:MM potential energy landscapes for very large systems. Our current development status and results from initial applications will be described

Improved Predictor−Corrector Integrators For Evaluating Reaction Path Curvature

ABSTRACT: The reaction path connects a chemical potential energy landscape and the conceptual descriptions of chemical mechanisms and reactivity. In recent years, a class of predictor− corrector integrators has been developed and shown to provide an excellent compromise between computational efficiency and numerical accuracy. Models based on projected frequencies along the reaction path and coupling matrix elements, such as Reaction Path Hamiltonian (RPH) and Unified Reaction Valley Approach (URVA), require highly accurate integration of the reaction path. In this report, the Euler Predictor−Corrector (EulerPC) and Hessian-based Predictor−Corrector (HPC) methods are shown to be inadequate for studying reaction path curvature, which is a central component of the RPH and URVA models. The source of this apparent failure is explored, and a solution is developed. Importantly, the resulting enhanced EulerPC and HPC integrators do not require more intensive CPU or memory requirements than their predecessors

Assessing the performance of ΔSCF and the diagonal second-order self-energy approximation for calculating vertical core excitation energies

Vertical core excitation energies are obtained using a combination of the $\Delta$SCF method and the diagonal second-order (D2) self-energy approximation. These methods are applied to a set of neutral molecules and their anionic forms. An assessment of the results with the inclusion of relativistic effects is presented. For core excitations involving delocalized symmetry orbitals, the applied composite method improves upon the overestimation of $\Delta$SCF by providing approximate values close to experimental K-shell transition energies. The importance of both correlation and relaxation contributions to the vertical core-excited state energies, the concept of local and non-local core orbitals, and the consequences of breaking symmetry are discussed

The Strongest Acid: Protonation of Carbon Dioxide

The strongest carborane acid, H(CHB11F11), protonates CO2 while traditional mixed Lewis/Brønsted superacids do not. The product is deduced from IR spectroscopy and calculation to be the proton disolvate, H(CO2)2(+). The carborane acid H(CHB11F11) is therefore the strongest known acid. The failure of traditional mixed superacids to protonate weak bases such as CO2 can be traced to a competition between the proton and the Lewis acid for the added base. The high protic acidity promised by large absolute values of the Hammett acidity function (H0) is not realized in practice because the basicity of an added base is suppressed by Lewis acid/base adduct formation

Modeling the Photoelectron Spectra of MoNbO₂^– Accounting for Spin Contamination in Density Functional Theory

Spin contamination in density functional studies has been identified as a cause of discrepancies between theoretical and experimental spectra of metal oxide clusters such as MoNbO₂. We perform calculations to simulate the photoelectron spectra of the MoNbO₂ anion using broken-symmetry density functional theory incorporating recently developed approximate projection methods. These calculations are able to account for the presence of contaminating spin states at single-reference computational cost. Results using these new tools demonstrate the significant effect of spin-contamination on geometries and force constants and show that the related errors in simulated spectra may be largely overcome by using an approximate projection model