Measuring many-body effects in carbon nanotubes with a scanning tunneling microscope

Electron-electron interactions and excitons in carbon nanotubes are locally measured by combining Scanning tunneling spectroscopy and optical absorption in bundles of nanotubes. The largest gap deduced from measurements at the top of the bundle is found to be related to the intrinsic quasi-particle gap. From the difference with optical transitions, we deduced exciton binding energies of 0.4 eV for the gap and 0.7 eV for the second Van Hove singularity. This provides the first experimental evidence of substrate-induced gap renormalization on SWNTs

Symmetry-selected spin-split hybrid states in C60_{60}/ferromagnetic interfaces

The understanding of orbital hybridization and spin-polarization at the organic-ferromagnetic interface is essential in the search for efficient hybrid spintronic devices. Here, using first-principles calculations, we report a systematic study of spin-split hybrid states of C$_{60}$ deposited on various ferromagnetic surfaces: bcc-Cr(001), bcc-Fe(001), bcc-Co(001), fcc-Co(001) and hcp-Co(0001). We show that the adsorption geometry of the molecule with respect to the surface crystallographic orientation of the magnetic substrate as well as the strength of the interaction play an intricate role in the spin-polarization of the hybrid orbitals. We find that a large spin-polarization in vacuum above the buckyball can only be achieved if the molecule is adsorbed upon a bcc-(001) surface by its pentagonal ring. Therefore bcc-Cr(001), bcc-Fe(001) and bcc-Co(001) are the optimal candidates. Spin-polarized scanning tunneling spectroscopy measurements on single C$_{60}$ adsorbed on Cr(001) and Co/Pt(111) also confirm that both the symmetry of the substrate and of the molecular conformation have a strong influence on the induced spin polarization. Our finding may give valuable insights for further engineering of spin filtering devices through single molecular orbitals.Comment: 10 pages, 9 figure

Imaging the symmetry breaking of molecular orbitals in carbon nanotubes

Carbon nanotubes have attracted considerable interest for their unique electronic properties. They are fascinating candidates for fundamental studies of one dimensional materials as well as for future molecular electronics applications. The molecular orbitals of nanotubes are of particular importance as they govern the transport properties and the chemical reactivity of the system. Here we show for the first time a complete experimental investigation of molecular orbitals of single wall carbon nanotubes using atomically resolved scanning tunneling spectroscopy. Local conductance measurements show spectacular carbon-carbon bond asymmetry at the Van Hove singularities for both semiconducting and metallic tubes, demonstrating the symmetry breaking of molecular orbitals in nanotubes. Whatever the tube, only two types of complementary orbitals are alternatively observed. An analytical tight-binding model describing the interference patterns of ? orbitals confirmed by ab initio calculations, perfectly reproduces the experimental results

Assessment of fine scale population genetic diversity and regeneration in Congo basin logged forests

In the Congo Basin most of the light-demanding timber tree species display a deficit of natural regeneration which is a major handicap for sustainable production and certification. Whilst the majority of scientists investigate abiotic and biotic factors explaining that pattern, we hypothesize that tree population density or individual spatial isolation may also affect the tree fitness through inbreeding. In this study, we integrate ecological and genetic approaches to characterize the regeneration potential of a set of priority timber species by (i) estimating pollen dispersal distances at various tree population densities, and (ii) evaluating the impact of increasing spatial isolation on mating characteristics and tree fitness. The ultimate goal is the proposal of minimum population density that prevents inbreeding consequences. Method This ongoing study focuses on 10 timber species (Pericopsis elata, Milicia excelsa, Baillonella toxisperma, Entandrophragma cylindricum, E. utile, E. angolense, E. candollei, Afzelia bipindensis, Erythrophleum suaveloens, Terminalia superba). The data collection was carried out in the logging concession granted to Pallisco in Cameroon. We established two 400-ha plots, where all individuals (DBH > 10 cm) of the target species were inventoried and mapped. A sample of leave or cambium was collected for each of these individuals, as well as for seedlings to characterize patterns of gene flow using genetic tools (nuclear microsatellites). Dispersal agents were identified by direct observations and camera traps. Germination success was characterized in nursery for seeds collected on trees under an increasing isolation gradient. Results Main dispersal agents (wind, bat, rodent) and predators (rodent) were identified for all the species. The gene flow and germination data is still being analyzed and the main results will be presented in the poster. Conclusion Our data will allow characterizing the reproductive biology of a set of important timber species from the Congo basin. These information will strengthen sustainable forest management and the application of certification by adjusting harvesting norms through the use of scientifically-relevant data. In particular, we will tentatively define a maximum distance to be maintained between two adults to allow a qualitative reproduction

Scouting the spectrum for interstellar travellers

Advanced civilizations capable of interstellar travel, if they exist, are likely to have advanced propulsion methods. Spaceships moving at high speeds would leave a particular signature which could be detected from Earth. We propose a search based on the properties of light reflecting from objects travelling at relativistic speeds. Based on the same principles, we also propose a simple interstellar beacon with a solar sail

Localized state and charge transfer in nitrogen-doped graphene

Nitrogen-doped epitaxial graphene grown on SiC(000?1) was prepared by exposing the surface to an atomic nitrogen flux. Using Scanning Tunneling Microscopy (STM) and Spectroscopy (STS), supported by Density Functional Theory (DFT) calculations, the simple substitution of carbon by nitrogen atoms has been identified as the most common doping configuration. High-resolution images reveal a reduction of local charge density on top of the nitrogen atoms, indicating a charge transfer to the neighboring carbon atoms. For the first time, local STS spectra clearly evidenced the energy levels associated with the chemical doping by nitrogen, localized in the conduction band. Various other nitrogen-related defects have been observed. The bias dependence of their topographic signatures demonstrates the presence of structural configurations more complex than substitution as well as hole-doping.Comment: 5 pages, accepted in PR

Gravitational instability of slowly rotating isothermal spheres

We discuss the statistical mechanics of rotating self-gravitating systems by allowing properly for the conservation of angular momentum. We study analytically the case of slowly rotating isothermal spheres by expanding the solutions of the Boltzmann-Poisson equation in a series of Legendre polynomials, adapting the procedure introduced by Chandrasekhar (1933) for distorted polytropes. We show how the classical spiral of Lynden-Bell & Wood (1967) in the temperature-energy plane is deformed by rotation. We find that gravitational instability occurs sooner in the microcanonical ensemble and later in the canonical ensemble. According to standard turning point arguments, the onset of the collapse coincides with the minimum energy or minimum temperature state in the series of equilibria. Interestingly, it happens to be close to the point of maximum flattening. We determine analytically the generalization of the singular isothermal solution to the case of a slowly rotating configuration. We also consider slowly rotating configurations of the self-gravitating Fermi gas at non zero temperature.Comment: Submitted to A&

The construction of non-spherical models of quasi-relaxed stellar systems

Spherical models of collisionless but quasi-relaxed stellar systems have long been studied as a natural framework for the description of globular clusters. Here we consider the construction of self-consistent models under the same physical conditions, but including explicitly the ingredients that lead to departures from spherical symmetry. In particular, we focus on the effects of the tidal field associated with the hosting galaxy. We then take a stellar system on a circular orbit inside a galaxy represented as a "frozen" external field. The equilibrium distribution function is obtained from the one describing the spherical case by replacing the energy integral with the relevant Jacobi integral in the presence of the external tidal field. Then the construction of the model requires the investigation of a singular perturbation problem for an elliptic partial differential equation with a free boundary, for which we provide a method of solution to any desired order, with explicit solutions to two orders. We outline the relevant parameter space, thus opening the way to a systematic study of the properties of a two-parameter family of physically justified non-spherical models of quasi-relaxed stellar systems. The general method developed here can also be used to construct models for which the non-spherical shape is due to internal rotation. Eventually, the models will be a useful tool to investigate whether the shapes of globular clusters are primarily determined by internal rotation, by external tides, or by pressure anisotropy.Comment: AASTeX v5.2, 37 pages with 2 figures, accepted for publication in The Astrophysical Journa

Denoising Scanning Tunneling Microscopy Images of Graphene with Supervised Machine Learning

Machine learning (ML) methods are extraordinarily successful at denoising photographic images. The application of such denoising methods to scientific images is, however, often complicated by the difficulty in experimentally obtaining a suitable expected result as an input to training the ML network. Here, we propose and demonstrate a simulation-based approach to address this challenge for denoising atomic-scale scanning tunneling microscopy (STM) images, which consists of training a convolutional neural network on STM images simulated based on a tight-binding electronic structure model. As model materials, we consider graphite and its mono- and few-layer counterpart, graphene. With the goal of applying it to any experimental STM image obtained on graphitic systems, the network was trained on a set of simulated images with varying characteristics such as tip height, sample bias, atomic-scale defects, and non-linear background. Denoising of both simulated and experimental images with this approach is compared to that of commonly-used filters, revealing a superior outcome of the ML method in the removal of noise as well as scanning artifacts - including on features not simulated in the training set. An extension to larger STM images is further discussed, along with intrinsic limitations arising from training set biases that discourage application to fundamentally unknown surface features. The approach demonstrated here provides an effective way to remove noise and artifacts from typical STM images, yielding the basis for further feature discernment and automated processing.Comment: Includes S