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      Sensing Single Molecules with Carbon-Boron-Nitride Nanotubes

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          Abstract

          We investigate the molecular sensing properties of carbon nanotube-boron nitride-carbon nanotube (CNT-BN-CNT) junctions. We demonstrate that the electrical conductance of such a junction changes in response to the binding of an analyte molecule to the region of BN. The change in conductance depends on the length of the BN spacer and the position of the analyte and therefore we propose a method of statistically analysing conductance data. We demonstrate the ability to discriminate between analytes, by computing the conductance changes due to three analytes (benzene, thiol-capped oligoyne and a pyridyl-capped oligoyne) binding to junctions with five different lengths of BN spacer.

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          The SIESTA method for ab initio order-N materials simulation

          Alberto García, Daniel Sánchez-Portal, Pablo Ordejon … (2002)
          We have developed and implemented a self-consistent density functional method using standard norm-conserving pseudopotentials and a flexible, numerical LCAO basis set, which includes multiple-zeta and polarization orbitals. Exchange and correlation are treated with the local spin density or generalized gradient approximations. The basis functions and the electron density are projected on a real-space grid, in order to calculate the Hartree and exchange-correlation potentials and matrix elements, with a number of operations that scales linearly with the size of the system. We use a modified energy functional, whose minimization produces orthogonal wavefunctions and the same energy and density as the Kohn-Sham energy functional, without the need of an explicit orthogonalization. Additionally, using localized Wannier-like electron wavefunctions allows the computation time and memory, required to minimize the energy, to also scale linearly with the size of the system. Forces and stresses are also calculated efficiently and accurately, thus allowing structural relaxation and molecular dynamics simulations.
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            Boron nitride nanotubes.

            N. G. Chopra, R J Luyken, K Cherrey … (1995)
            The successful synthesis of pure boron nitride (BN) nanotubes is reported here. Multi-walled tubes with inner diameters on the order of 1 to 3 nanometers and with lengths up to 200 nanometers were produced in a carbon-free plasma discharge between a BN-packed tungsten rod and a cooled copper electrode. Electron energy-loss spectroscopy on individual tubes yielded B:N ratios of approximately 1, which is consistent with theoretical predictions of stable BN tube structures.
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              Boron nitride nanotubes and nanosheets.

              Dmitri Golberg, Yoshio Bando, Yang Huang … (2010)
              Hexagonal boron nitride (h-BN) is a layered material with a graphite-like structure in which planar networks of BN hexagons are regularly stacked. As the structural analogue of a carbon nanotube (CNT), a BN nanotube (BNNT) was first predicted in 1994; since then, it has become one of the most intriguing non-carbon nanotubes. Compared with metallic or semiconducting CNTs, a BNNT is an electrical insulator with a band gap of ca. 5 eV, basically independent of tube geometry. In addition, BNNTs possess a high chemical stability, excellent mechanical properties, and high thermal conductivity. The same advantages are likely applicable to a graphene analogue-a monatomic layer of a hexagonal BN. Such unique properties make BN nanotubes and nanosheets a promising nanomaterial in a variety of potential fields such as optoelectronic nanodevices, functional composites, hydrogen accumulators, electrically insulating substrates perfectly matching the CNT, and graphene lattices. This review gives an introduction to the rich BN nanotube/nanosheet field, including the latest achievements in the synthesis, structural analyses, and property evaluations, and presents the purpose and significance of this direction in the light of the general nanotube/nanosheet developments.
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                Author and article information

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                ArXiv ID:: 1601.00220

                ScienceOpen disciplines: Nanophysics
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                ScienceOpen disciplines: Nanophysics

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