The active sites for propane dehydrogenation in Ga/H-ZSM-5 with moderate concentrations of tetrahedral aluminum in the lattice were identified to be Lewis-Brønsted acid pairs. With increasing availability, Ga and Brønsted acid site concentrations changed inversely, as protons of Brønsted acid sites were exchanged with Ga. At a Ga/Al ratio of 1/2, the rate of propane dehydrogenation was 2 orders of magnitude higher than with the parent H-ZSM-5, highlighting the extraordinary activity of the Lewis-Brønsted acid pairs. Density functional theory calculations relate the high activity to a bifunctional mechanism that proceeds via heterolytic activation of the propane C-H bond followed by a monomolecular elimination of H and desorption of propene.

Quantum chemical calculations and simulated kinetics were used to examine the structure sensitivity of the oxygen evolution reaction on several surface terminations of Co3O4. Active sites consisting of two adjacent Co(IV) cations connected by bridging oxos were identified on both the (001) and (311) surfaces. Formation of the O-O bond proceeds on these sites by nucleophilic attack of water on a bridging oxo. It was found that the relative turnover frequencies for the different sites are highly dependent on the overpotential, with the dual-Co site on the (311) surface being most active at medium overpotentials (0.46-0.77 V), where O-O bond formation by water addition is rate limiting. A similar dual-Co site on the (001) surface is most active at low overpotentials (<0.46 V), where O2 release is rate limiting, and a single-Co site on the (110) surface is most active at overpotentials that are high enough (>0.77 V) to form a significant concentration of highly reactive terminal Co(V)═O species. Two overpotential-dependent Sabatier relationships were identified based on the Brønsted basicity and redox potential of the active site, explaining the change in the active site with overpotential. The (311) dual-Co site that is most active in the medium overpotential range is consistent with recent experimental observations suggesting that a defect site is responsible for the observed oxygen evolution activity and that a modest concentration of superoxo intermediates is present on the surface. Importantly, we find that it is essential to consider the kinetics of the water addition and O2 release steps rather than only the thermodynamics.

First-principles screening studies aimed at predicting the catalytic activity of transition metal (TM) catalysts have traditionally been based on mean-field (MF) microkinetic models, which neglect the effect of spatial correlations in the adsorbate layer. Here we critically assess the accuracy of such models for the specific case of CO methanation over stepped metals by comparing to spatially resolved kinetic Monte Carlo (kMC) simulations. We find that the typical low diffusion barriers offered by metal surfaces can be significantly increased at step sites, which results in persisting correlations in the adsorbate layer. As a consequence, MF models may overestimate the catalytic activity of TM catalysts by several orders of magnitude. The potential higher accuracy of kMC models comes at a higher computational cost, which can be especially challenging for surface reactions on metals due to a large disparity in the time scales of different processes. In order to overcome this issue, we implement and test a recently developed algorithm for achieving temporal acceleration of kMC simulations. While the algorithm overall performs quite well, we identify some challenging cases which may lead to a breakdown of acceleration algorithms and discuss possible directions for future algorithm development.

A novel algorithm is presented that achieves temporal acceleration during kinetic Monte Carlo (KMC) simulations of surface catalytic processes. This algorithm allows for the direct simulation of reaction networks containing kinetic processes occurring on vastly disparate time scales which computationally overburden standard KMC methods. Previously developed methods for temporal acceleration in KMC were designed for specific systems and often require a priori information from the user such as identifying the fast and slow processes. In the approach presented herein, quasi-equilibrated processes are identified automatically based on previous executions of the forward and reverse reactions. Temporal acceleration is achieved by automatically scaling the intrinsic rate constants of the quasi-equilibrated processes, bringing their rates closer to the time scales of the slow kinetically relevant nonequilibrated processes. All reactions are still simulated directly, although with modified rate constants. Abrupt changes in the underlying dynamics of the reaction network are identified during the simulation, and the reaction rate constants are rescaled accordingly. The algorithm was utilized here to model the Fischer-Tropsch synthesis reaction over ruthenium nanoparticles. This reaction network has multiple time-scale-disparate processes which would be intractable to simulate without the aid of temporal acceleration. The accelerated simulations are found to give reaction rates and selectivities indistinguishable from those calculated by an equivalent mean-field kinetic model. The computational savings of the algorithm can span many orders of magnitude in realistic systems, and the computational cost is not limited by the magnitude of the time scale disparity in the system processes. Furthermore, the algorithm has been designed in a generic fashion and can easily be applied to other surface catalytic processes of interest.

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We present a computational screening study of ternary metal borohydrides for reversible hydrogen storage based on density functional theory. We investigate the stability and decomposition of alloys containing 1 alkali metal atom, Li, Na, or K ͑M 1 ͒; and 1 alkali, alkaline earth or 3d / 4d transition metal atom ͑M 2 ͒ plus two to five ͑BH 4 ͒ − groups, i.e., M 1 M 2 ͑BH 4 ͒ 2-5 , using a number of model structures with trigonal, tetrahedral, octahedral, and free coordination of the metal borohydride complexes. Of the over 700 investigated structures, about 20 were predicted to form potentially stable alloys with promising decomposition energies. The M 1 ͑Al/ Mn/ Fe͒͑BH 4 ͒ 4 , ͑Li/ Na͒Zn͑BH 4 ͒ 3 , and ͑Na/ K͒͑Ni/ Co͒͑BH 4 ͒ 3 alloys are found to be the most promising, followed by selected M 1 ͑Nb/ Rh͒͑BH 4 ͒ 4 alloys.

First-principles screening approaches exploiting energy trends in surface adsorption represent an unparalleled success story in recent computational catalysis research. Here we argue that our still limited understanding of the structure of active sites is one of the major bottlenecks towards an ever extended and reliable use of such computational screening for catalyst discovery. For low-index transition metal surfaces, the prevalently chosen high-symmetry (terrace and step) sites offered by the nominal bulk-truncated crystal lattice might be justified. For more complex surfaces and composite catalyst materials, computational screening studies will need to actively embrace a considerable uncertainty with respect to what truly are the active sites. By systematically exploring the space of possible active site motifs, such studies might eventually contribute towards a targeted design of optimized sites in future catalysts.

In the last decade, first-principles-based microkinetic modeling has been developed into an important tool for a mechanistic understanding of heterogeneous catalysis. A commonly known, but hitherto barely analyzed issue in this kind of modeling is the presence of sizable errors from the use of approximate Density Functional Theory (DFT). We here address the propagation of these errors to the catalytic turnover frequency (TOF) by global sensitivity and uncertainty analysis. Both analyses require the numerical quadrature of high-dimensional integrals. To achieve this efficiently, we utilize and extend an adaptive sparse grid approach and exploit the confinement of the strongly non-linear behavior of the TOF to local regions of the parameter space. We demonstrate the methodology on a model of the oxygen evolution reaction at the CoO (110)-A surface, using a maximum entropy error model that imposes nothing but reasonable bounds on the errors. For this setting, the DFT errors lead to an absolute uncertainty of several orders of magnitude in the TOF. We nevertheless find that it is still possible to draw conclusions from such uncertain models about the atomistic aspects controlling the reactivity. A comparison with derivative-based local sensitivity analysis instead reveals that this more established approach provides incomplete information. Since the adaptive sparse grids allow for the evaluation of the integrals with only a modest number of function evaluations, this approach opens the way for a global sensitivity analysis of more complex models, for instance, models based on kinetic Monte Carlo simulations.