Otimização e automatização na caracterização de estruturas nanoporosas por distribuição de energia potencial: armazenamento de hidrogênio

Abstract

Observing the search for new alternative energy sources, with hydrogen being one of the more promising choices being analyzed, the need to evaluate the best way to storage these fuels has grown. Among the various ways researched for hydrogen storage and transportation, the use of nanoporous materials capable of adsorbing hydrogen has gained attention due to its efficiency and economy. Aiming at adsorption as a hydrogen storage methodology, materials science is used, an area capable of evaluating the potential for hydrogen adsorption in nanoporous structures without the need for exhaustive experimental tests, because with use of the physical-chemical properties of the fuel and adsorbent material is possible to execute simulations to analyze the type and intensity of interatomic interactions between adsorbent and adsorbate. In this work has been studied the use of zeolites and Metalic Organic Framework (MOF) as adsorption materials to hydrogen. These materials have a wide diversity of compositions and structures, thus making it possible to find materials with optimal properties for hydrogen adsorption. A python routine was used to obtain the potential energy distribution of the pure interactions, without considering charges, calculated by the Lennard-Jones potential to be used to characterize each structure and evaluate which are the bests to store hydrogen, in addition to seeking to generalize the functionality of the routine for different types of adsorbates. 62 zeolite structures and 194 MOF structures respectively obtained from the Database of Zeolite Structures and MOFX-DB databases were analyzed, and the results obtained will later be used to feed neural networks with the aim of selecting the best structures for hydrogen adsorption. The use of potential energy distribution data in the form of energy histograms proved to be promising as a parameter for characterizing the structures, allowing the verification of the tendency of which structures have the greatest adsorption potential.