FisMat2017 - Submission - View

Abstract's title: Graphene-based Nanostructured Models for Energy Storage Applications
Submitting author: Luca Bellucci
Affiliation: NEST, Istituto Nanoscienze (CNR-NANO)
Affiliation Address: Pizza S.Silvestro 12, 56127, Pisa
Country: Italy
Oral presentation/Poster (Author's request): Oral presentation
Other authors and affiliations: Valentina Tozzini (NEST, Istituto Nanoscienze (CNR-NANO), Piazza S. Silvestro 12, 56127, Pisa, Italy)
Abstract

Graphene-based materials have generated considerable interest in the development of new nanostructured materials to be used as efficient solid-state energy storage devices and in particular for the hydrogen storage. Several studies have highlighted the possibility to increase the hydrogen uptake by modulating the porosity and the surface area of these graphene-based materials[1,2]. Recently, Baburin et al[3] provided experimental and theretical evidences that multilayer graphene sheets with hole defects of the order of 1-2 nm, possess promising hydrogen storage capacities. Understanding the interaction mechanism between hydrogen and the irregular network of graphene-based materials are of paramount importance to rationalize the gas sorption process on these new systems. Notably, theoretical modeling techniques provide the most proficient tool to study their the adsorption process and to design/develop new type of nanoporous materials with improved hydrogen storage parameters.

Here, we propose and implement an algorithm to generate graphene scaffold with given porosity and specific density, and realistic structure. The algorithm is based on a stepwise generation of graphene flakes of size, shape and orientation randomly distributed, until the wanted structural features are reached. The structure is subsequently refined by means of molecular dynamics simulations using empirical force fields. Optionally, it can be decorated with adatoms (H, O or others) to mimic the real structures generated from GO flakes or other precursors. Finally, the structure is characterized versus its gas adsorption capability by means of gran canonical monte carlo (GCMC) and/or diffusion molecular dynamics simulations.

[1] S. Gadipelli, Z. X. Guo, Progress in Materials Science, 69, 2015.

[2] A. Klechikov, G. Mercier, T. Sharifi, I.A. Baburin, G. Seifertb, A.V. Talyzin, Chem. Commun., 51, 2015.

[3] I. A. Baburin, A. Klechikovb, G. Mercierb, A. Talyzinb, G.Seiferta, Int. J. Hydrogen Energy, 40, 2015.