Lauro Oliver Paz-Borbón
Instituto de Física, Universidad Nacional Autónoma de México, Apdo. Postal 20-364, 01000 México, D.F. México
Transition and noble metal nanoparticles have been the subject of major research efforts with the aim to gain insights on aspects relevant to heterogeneous catalysis. Gaining control at small nm-scale could open new technological possibilities. This has motivated extensive experimental and theoretical studies of mono- and bi- metallic clusters and nanoparticles both in the gas-phase and supported on different type of surfaces, including those of metal oxides. With the constant development of powerful high-performance computing facilities, materials modelling and simulations at the nanoscale has evolved in recent years to a successful field of research, particularly with advances in accurate theoretical approaches based, namely, on Density Functional Theory (DFT) and many-body semi-empirical potentials such as the Gupta potential. In this talk, I will introduce computational methodologies currently used to find minimum energy arrangements of metal clusters - involving a few tens of atoms - as well as of larger nanoparticles. Namely, I will describe a number of global optimization techniques such as Genetic Algorithms, Basin Hopping Monte Carlo, as well as Molecular Dynamics simulations, utilized for an efficient exploration of the particle’s configurational space and to gain understanding of the energetics, thermodynamics and reactivity of gas-phase and supported metal clusters and nanoparticles.
Keywords: Global optimization methods; metal clusters, metal nanoparticles, semi-empirical potentials, Density Functional Theory.