4.5 Article

Molecular dynamics, simulations of boron-nitride nanotubes embedded in amorphous Si-B-N

期刊

COMPUTATIONAL MATERIALS SCIENCE
卷 39, 期 3, 页码 502-517

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.commatsci.2006.06.013

关键词

molecular dynamics simulations; boron-nitride nanotubes; Si-B-N ceramics; composites; elastic moduli

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In this article, we examine the elastic properties of boron-nitride nanotubes, which are embedded in amorphous silicon-boron-nitride ceramics. We employ molecular dynamics simulations using the Parrinello-Rahman approach. To this end, all systems are modeled with a reactive many-body bond order potential due to Tersoff, which is able to describe covalent bonding accurately. We apply external stress and derive stress-strain curves for various tensile and compressive load cases at given temperature and pressure. In addition to Young moduli and Poisson ratios, we compare radial distribution functions, average coordination numbers, ring statistics and self-diffusion coefficients to characterize the short-range, medium-range and long-range order Of Si3BN5, Si3B2N6 and Si3B3N7 matrices, respectively. Here, our results show that Si3B3N7 exhibits the highest Young modulus and the largest elastic range. Then, we study the properties of a ceramics composite material made from Si3B3N7 matrix and BN nanotubes. We calculate stress-strain curves for the composite to predict the rates of reinforcement of the matrix due to the BN nanotubes. Here, also the influence of the nanotube/matrix-ratio on the elastic modulus of the composite is examined. Finally, we compare the Young moduli derived from our numerical simulations to predictions given by both, a simple macroscopic rule-of-mixtures, which depends on the volume fraction only, and an extended rule-of-mixtures, which also takes the geometry of the BN nanotube into account. Our numerical results show that the extended rule-of-mixtures predicts the Young modulus of the composite with a relative error of 5% or less. (C) 2006 Elsevier B.V. All rights reserved.

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