Tailoring the local interaction between graphene layers in graphite at the atomic scale and above using scanning tunneling microscopy.

With recent developments in carbon-based electronics, it is imperative to understand the interplay between the morphology and electronic structure in graphene and graphite. We demonstrate controlled and repeatable vertical displacement of the top graphene layer from the substrate mediated by the scanning tunneling microscopy (STM) tip-sample interaction, manifested at the atomic level as well as over superlattices spanning several tens of nanometers. Besides the full-displacement, we observed the first half-displacement of the surface graphene layer, confirming that a reduced coupling rather than a change in lateral layer stacking is responsible for the triangular/honeycomb atomic lattice transition phenomenon, clearing the controversy surrounding it. Furthermore, an atomic scale mechanical stress at a grain boundary in graphite, resulting in the localization of states near the Fermi energy, is revealed through voltage-dependent imaging. A method of producing graphene nanoribbons based on the manipulation capabilities of the STM is also implemented.

Angular dependence of domain wall resistivity in artificial magnetic domain structures.

We exploit the ability to precisely control the magnetic domain structure of perpendicularly magnetized Pt/Co/Pt trilayers to fabricate artificial domain wall arrays and study their transport properties. The scaling behavior of this model system confirms the intrinsic domain wall origin of the magnetoresistance, and systematic studies using domains patterned at various angles to the current flow are excellently described by an angular-dependent resistivity tensor containing perpendicular and parallel domain wall resistivities. We find that the latter are fully consistent with Levy-Zhang theory, which allows us to estimate the ratio of minority to majority spin carrier resistivities, rho downward arrow/rho upward arrow approximately 5.5, in good agreement with thin film band structure calculations.

Machine learning for predictive condensed-phase simulation

We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using accurate, correlated quantum chemistry, and predict energies and forces in molecular aggregates ranging from clusters to solid and liquid phases. The widely used electronic-structure methods based on density-functional theory (DFT) give poor accuracy for molecular materials like water, and we show how our techniques can be used to generate systematically improvable corrections to DFT. The resulting corrected DFT scheme gives remarkably accurate predictions for the relative energies of small water clusters and of different ice structures, and greatly improves the description of the structure and dynamics of liquid water.

Theory of defects in amorphous semiconductors

We review the electronic structure of defects in aSi:H, aGaAs and aSi3N4, emphasising in aSi:H the doping mechanism, the evidence that its dangling bond defect has a small electron-lattice coupling and a positive correlation energy, and possible atomic mechanisms for the Staebler-Wronski effect. © 1985.

Calculation of metallic and insulating phases of V2O3 by hybrid density functionals.

The electronic structure of vanadium sesquioxide V2O3 in its different phases has been calculated using the screened exchange hybrid density functional. The hybrid functional accurately reproduces the experimental electronic properties of all three phases, the paramagnetic metal (PM) phase, the anti-ferromagnetic insulating phase, and the Cr-doped paramagnetic insulating (PI) phase. We find that a fully relaxed supercell model of the Cr-doped PI phase based on the corundum structure has a monoclinic-like local strain around the substitutional Cr atoms. This is found to drive the PI-PM transition, consistent with a Peierls-Mott transition. The PI phase has a calculated band gap of 0.15 eV, in good agreement with experiment.