NERSC Initiative for Scientific Exploration (NISE) 2011 Awards

Semiclassical Approaches for Clean Energy Resources

Puru Jena, University of California Berkeley

Associated NERSC Project: Cluster and Nanostructure for Energy and Bio Applications (m847)

Since the discovery of the fullerene C60 by Kroto et al. in 1985, followed by the production of larger fullerenes and carbon nanotubes by Iijima2 in 1991, it started a different field of investigation devoted to the study of the many electronic and structural properties of this class of nanoobjects. These experimental findings have also led to an intense effort towards finding analogs of the carbon nanotubes and fullerenes involving carbon, boron, and nitrogen. Fullerenes have been extensively investigated as promising buiding blocks for nanoelectronic devices, which implies the search for fullerenelike structures based on other elements rather than carbon and the interaction of carbon fullerenes with other chemical groups or atoms. Due to graphene’s unique dispersion relation, electrons and holes behave like a two-dimensional 2D gas of massless Dirac fermions, which allows to probe quantum electrodynamics phenomena in condensed matter. On the other hand, a new class of highly electronegative species can be synthesized if the peripheral halogen atoms are replaced by superhalogen moieties, which are named “hyperhalogens”, because their electron affinities can even be larger than those of their superhalogen building blocks and thus can serve as ingredients in the synthesis of new superoxidizing agents. A superhalogen consists of a central metal atom surrounded by halogen atoms. When the number of these halogen atoms exceeds the maximal valence of the metal atom, the molecule possesses electron affinities that are much larger than that of the halogen atoms. Our goal is to also investigate electronic properties of magnetic superhalogens. Our first-principles methodology is based on the density functional theory DFT implemented in the VASP program. We make use of the generalized gradient approximation GGA for the exchange-correlation functional.