Catalytic Efficiency in Metallic Nanoparticles: A Computational Approach

Abstract

The use of computational methods to characterise and describe different properties in the nanoscale has increased considerably in the recent decades. Catalysis has risen as one of the major focuses in different technological fields since the use of nanostructured materials becomes more common in many industrial processes. Different computational methods have been developed to complement the experimental effort in the design of novel nanocatalysts. To date, density functional (DFT), kinetic Monte Carlo (KMC) and classical molecular dynamics (CMD) simulations allow one to describe catalytic activity for a wide diversity of reactions in different materials. Computational simulations could provide a theoretical guideline for the choice of conditions and nanomaterials to improve a specific catalytic reaction. In this work, we review the most common computational methods used to describe catalytic activity highlighting their applicability and failures. We also examine different cases in which the combination of methods improves the accuracy of the simulations. We also provide a study case in which highly active catalytic nanoparticles can be produced by using CMD simulations.