Estudo computacional do indicador teórico de nanoclusters de metais de transição aplicados em processos de crescimento de nanotubos de carbono

Abstract

In catalytic processes, the knowledge about the properties of the elements plays a very important role in understanding the chemical reactions. Thus, it is necessary to nd indicators to point out the best catalyst components for processes such as the chemical vapour deposition method, which allows the carbon nanotubes (CNTs) growth. In this work, we report a density functional theory study, about the 13-atom transition metal nanoclusters, interacting with zigzag (5,0) and armchair (3,3) carbon nanotube fragments. All transition metals species from the periodic table were considered as possible candidates for catalysts in chemical vapour deposition method. The icosahedral con guration was found to be a good model to simulate the nucleation seed in the case of the short carbon nanotube fragments that are initially formed during the growth process. The energetic and structural properties of all optimized systems showed a strong dependence on the occupation of the bonding and antibonding d-states. In this sense, the center of gravity of the occupied d-states for nanoclusters is found to be a good indicator to reveal the best candidates for the interaction with the carbon nanotubes, namely, Sc-Cu; Y-Nb; Pd, Lu, Hf and Pt. In terms of stability, the interaction with the nanotube is favorable to all studied metals. However, the systems associated with the zigzag nanotubes are more stable than armchair ones. This fact is con rmed in reason of the short distance between the metal and carbon atoms. The predictions regarding the best candidates for catalysis are reinforced by the linear relationship between adhesion energy, a factor that determines the stability, and the center of gravity of the d-states. The adhesion energy values indicate that the intensity of the interaction between nanoclusters and CNT fragments is reduced according to the d-states occupation. As a result, the model proposed in this dissertation, is able to provide a good descriptor for indicating the best 13-atom transition-metal candidates in the chemical vapour deposition process.