No abstract

Machine learning methods are applied to finding the Green function of the Anderson impurity model, a basic model system of quantum many-body condensed matter physics. Different methods of parametrizing the Green function are investigated; a representation in terms of Legendre polynomials is found to be superior due to its limited number of coefficients and its applicability to state of the art methods of solution. The dependence of the errors on the size of the training set is determined. The results indicate that a machine-learning approach to dynamical mean field theory may be feasible.

Standard spin-polarized density functional theory calculations have been conducted to study the electronic structures and magnetic properties of O and S functionalized zigzag boron nitride nanoribbons (zBNNRs). Unlike the semiconducting and nonmagnetic H edge-terminated zBNNRs, the O edge-terminated zBNNRs have two energetically degenerate magnetic ground states with a ferrimagnetic character on the B edge, both of which are metallic. In contrast, the S edge-terminated zBNNRs are nonmagnetic albeit still metallic. An intriguing coexistence of two different Peierls-like distortions is observed for S edge-termination that manifests as a strong S dimerization at the B zigzag edge and a weak S trimerization at the N zigzag edge, dictated by the band fillings at the vicinity of the Fermi level. Nevertheless, metallicity is retained along the S wire on the N edge due to the partial filling of the band derived from the p(z) orbital of S. A second type of functionalization with O or S atoms embedded in the center of zBNNRs yields semiconducting features. Detailed examination of both types of functionalized zBNNRs reveals that the p orbitals on O or S play a crucial role in mediating the electronic structures of the ribbons. We suggest that O and S functionalization of zBNNRs may open new routes toward practical electronic devices based on boron nitride materials.

We present first-principles calculations of quantum transport in chemically functionalized metallic carbon nanotubes with lengths reaching the micrometer scale and random distributions of functional groups. Two typical cases are investigated, namely, a sp2-type bonding between carbene groups (CH2) and the nanotube sidewalls and a sp3-type bonding of nanotubes with paired phenyl groups. For similar molecular coverage density, charge transport is found to range from a quasi-ballistic-like to a strongly diffusive regime, with corresponding mean free paths changing by orders of magnitude depending on the nature of the chemical bonding.

International audienceDensity functional calculations are used to perform a systematic study of the effect of edge-functionalization on the structure and electronic properties of graphene nanoribbons (GNRs). −H, −F, −Cl, −Br, −S, −SH, and −OH edge-functionalization of armchair, zigzag, and reconstructed Klein-type GNRs was considered. The most energetically favorable edge structure varies depending on the choice of functional group. It is shown, for the first time, that reconstructed Klein-type GNRs are important stable configurations for several edge-functional groups. Band gaps using three different exchange-correlation functionals are calculated. The band gap for armchair GNRs can be tuned over a range of 1.2 eV by varying the edge-functional groups. In contrast, the band gaps of zigzag and reconstructed Klein edge GNRs are largely insensitive to the choice of edge-functional group, and ribbon width is instead the defining factor. Alternatively, the armchair GNR band gap can be controlled by varying the number of functional groups per opposing edge, altering the GNR "effective" width. Edge-functionalization design is an appropriate mechanism to tune the band gap of armchair GNRs

We present a machine learning approach to solve electronic quantum transport equations of one-dimensional nanostructures. The transmission coefficients of disordered systems were computed to provide training and test data sets to the machine. The system's representation encodes energetic as well as geometrical information to characterize similarities between disordered configurations, while the Euclidean norm is used as a measure of similarity. Errors for out-of-sample predictions systematically decrease with training set size, enabling the accurate and fast prediction of new transmission coefficients. The remarkable performance of our model to capture the complexity of interference phenomena lends further support to its viability in dealing with transport problems of undulatory nature.

We present first-principles transport calculations of graphene nanoribbons with chemically reconstructed edge profiles. Depending on the geometry of the defect and the degree of hydrogenation, spectacularly different transport mechanisms are obtained. In the case of monohydrogenated pentagon (heptagon) defects, an effective acceptor (donor) character results in strong electron-hole conductance asymmetry. In contrast, weak backscattering is obtained for defects that preserve the benzenoid structure of graphene. Based on a tight-binding model derived from ab initio calculations, evidence for large conductance scaling fluctuations are found in disordered ribbons with lengths up to the micrometer scale.

We present a theoretical study of a new type of two-dimensional material exhibiting a pentagonal arrangement of C and Si atoms. Pentagonal SiC 2 is investigated with density functional theory-based calculations to show that the buckled nano-structure is dynamically stable, exhibits an indirect energy band gap, and an enhanced electronic dispersion with respect to the all-carbon counterpart. Computed Born effective charges exhibit a significant anisotropy for C and Si atoms that deviates substantially from their static effective charges. We establish an accurate tunability of the vertical location of the p-p-σ and p-p-π bands and show that under compressive bi-axial strain the density of states decreases, and conversely for tensile biaxial strain. This study establishes that the coupling between the tunability of strain-mediated density of states and semiconducting properties in a monolayered structure may allow for the development of applications in semiconducting stretchable electronics.