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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.