Luca

The Journal of Chemical Physics, Volume 149, Issue 20, November 2018.
A new diabatization method based on artificial neural networks (ANNs) is presented, which is capable of reproducing high-quality ab initio data with excellent accuracy for use in quantum dynamics studies. The diabatic potential matrix is expanded in terms of a set of basic coupling matrices and the expansion coefficients are made geometry-dependent by the output neurons of the ANN. The ANN is trained with respect to ab initio data using a modified Marquardt-Levenberg back-propagation algorithm. Due to its setup, this approach combines the stability and straightforwardness of a standard low-order vibronic coupling model with the accuracy by the ANN, making it particularly advantageous for problems with a complicated electronic structure. This approach combines the stability and straightforwardness of a standard low-order vibronic coupling model with the accuracy by the ANN, making it particularly advantageous for problems with a complicated electronic structure. This novel ANN diabatization approach has been applied to the low-lying electronic states of NO3 as a prototypical and notoriously difficult Jahn-Teller system in which the accurate description of the very strong non-adiabatic coupling is of paramount importance. Thorough tests show that an ANN with a single hidden layer is sufficient to achieve excellent results and the use of a “deeper” layering shows no clear benefit. The newly developed diabatic ANN potential energy surface (PES) model accurately reproduces a set of more than 90 000 Multi-configuration Reference Singles and Doubles Configuration Interaction (MR-SDCI) energies for the five lowest PES sheets.

The Journal of Chemical Physics, Volume 149, Issue 19, November 2018.
Heterogeneous reactions at the surfaces of mineral dusts represent a key process in the formation of atmospheric aerosols. To quantify the rate of aerosol formation in climate modeling as well as combat hazardous aerosols, a deep understanding of the mechanisms of these reactions is essential. In the present work, density functional theory calculations, including a Hubbard-like +U correction, were employed to elucidate the reaction between SO2 and the hematite(0001) surface. Three reaction conditions are considered: dry, wet, and aerobic. In the absence of water and oxygen, adsorption energies of SO2 on the clean Fe–O3–Fe-termination were found to be about −0.8 to −1.0 eV and resulted in the formation of an adsorbed SO3-like species. The addition of water leads to surface hydroxylation and has little effect on promoting the SO2 adsorption. Under such circumstances, an HSO3-like species was formed with a smaller adsorption energy of about −0.5 eV. By contrast, the presence of molecular oxygen enhances the SO2 adsorption significantly as the two species combine to form sulfate SO42−, with adsorption energies of −1.31 to −1.64 eV. The calculated vibrational frequencies of the adsorbate species provide insight into the surface bonding and a useful spectral fingerprinting for experimental measurements. These results elucidate the atomistic mechanism of the reaction between SO2 and hematite and highlight the important role of atmospheric O2 in the formation of sulfates.

Abstract

In this work, we adapt our algorithm for relaxations of periodic systems (Bucko et al. in J Chem Phys 122: 124508, 2005) in delocalized internal coordinates of Baker et al. (J Chem Phys 105: 192, 1996) for the use in transition state geometry optimizations. The abilities of our algorithm are demonstrated on examples of relaxations of atomic positions and cell geometries of systems with and without additional geometric constraints that include transition states for reactions of molecules in the gas phase, reconnection of H atoms in the one-dimensional periodic chain of \(\hbox {H}_2\) molecules, proton transfer in zeolite chabazite, partial desorption of crotonaldehyde from the MgO surface, and a pure affine shear deformation of Al. A simple approximate initial Hessian is suggested, in which only the matrix elements corresponding to atoms actively participating in reaction of interest are determined accurately at a DFT level, while remaining elements, typically related to inactive atoms and lattice vectors components, are defined on a basis of a simple empirical model. The calculations employing the approximate Hessian are shown to be more effective compared to simulations carried out with exact initial Hessian, in which all elements related to atomic positions are computed at the DFT level.

Abstract

We explore the application of the electron position spread tensor, i.e., a quantitative measure of the electron delocalization and mobility, to the conical intersection regions of three relevant compounds showing either photoisomerization or chemiluminescence properties. The electronic structure of the involved states has been solved using the complete active space self-consistent field method, and the position spread tensor has been computed at the same level of theory. In particular, we show that the total position spread tensor is degenerate between the ground and the excited states, because of the inversion of the electronic nature of the states happening at the crossing areas. We also show that the ground-state position spread tensor shows a discontinuity that may be used to locate conical intersections without the need to explicitly compute the excited-state wavefunction. Furthermore, we also report that the spin partition position spread tensor shows a peculiar behavior presenting values close to zero in two of its principal components. We associate those small values to the degeneracy-lifting coordinates and hence to the conical intersection branching space.

Lighting the (reaction) path: Photoredox and photocatalysis have recently provided fresh opportunities to expand the potential of organic synthesis. So far, innovation has mainly been driven by the quest for novel reactivities, often at the expense of a thorough mechanistic understanding. But these fields are now entering a more mature phase where the combination of experimental and mechanistic studies will play a dominant role in sustaining further innovation.

Abstract

The fast‐moving fields of photoredox and photocatalysis have recently provided fresh opportunities to expand the potential of synthetic organic chemistry. Advances in light‐mediated processes have mainly been guided so far by empirical findings and the quest for reaction invention. The general perception, however, is that photocatalysis is entering a more mature phase where the combination of experimental and mechanistic studies will play a dominant role in sustaining further innovation. This Review outlines the key mechanistic studies to consider when developing a photochemical process, and the best techniques available for acquiring relevant information. The discussion will use selected case studies to highlight how mechanistic investigations can be instrumental in guiding the invention and development of synthetically useful photocatalytic transformations.

Abstract

The structures and stability of adsorbed methanol on TiO₂(110) surface have been extensively studied because of its application for direct hydrogen production and promoting hydrogen production in photocatalysis. In this work, combined with ab initio thermodynamics and kinetic Monte Carlo (KMC), a detailed microscopic picture of methanol adsorption structure on TiO₂(110) surface at different conditions is mapped out for the first time. The thermodynamics analysis based on the density functional theory calculations shows that the methanol adsorption at coverage of 2/3 ML is prevailed at a very wide range of temperatures and pressures. The simulated temperature-programmed desorption (TPD) based on KMC indicates that the full monolayer adsorption methanol desorbs at about 150 K and the methanol dimer at a coverage of 2/3 ML is stable up to 250 K. At higher temperature, the methanol dimer becomes unstable and decomposes to the monomer, which desorbs from the surface at 350 K. The present simulated results agree well with the experimental TPD results.