Probing the Statistical Validity of the Ductile-to-Brittle Transition in Metallic Nanowires Using GPU Computing

William R. French, Amulya K. Pervaje, Andrew P. Santos, Christopher R. Iacovella, Peter T. Cummings
Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN
arXiv:1311.3890 [cond-mat.mes-hall], (15 Nov 2013)


   author={French}, W.~R. and {Pervaje}, A.~K. and {Santos}, A.~P. and {Iacovella}, C.~R. and {Cummings}, P.~T.},

   title={"{Probing the Statistical Validity of the Ductile-to-Brittle Transition in Metallic Nanowires Using GPU Computing}"},

   journal={ArXiv e-prints},




   keywords={Condensed Matter – Mesoscale and Nanoscale Physics, Condensed Matter – Materials Science},




   adsnote={Provided by the SAO/NASA Astrophysics Data System}


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We perform a large-scale statistical analysis (> 2000 independent simulations) of the elongation and rupture of gold nanowires, probing the validity and scope of the recently proposed ductile-to-brittle transition that occurs with increasing nanowire length [Wu et. al., Nano Lett., 12, 910-914 (2012)]. To facilitate a high-throughput simulation approach, we implement the second-moment approximation to the tight-binding (TB-SMA) potential within HOOMD-Blue, a molecular dynamics package which runs on massively parallel graphics processing units (GPUs). In a statistical sense, we find that the nanowires obey the ductile-to-brittle model quite well; however, we observe several unexpected features from the simulations that build on our understanding of the ductile-to-brittle transition. First, occasional failure behavior is observed that qualitatively differs from that predicted by the model prediction; this is attributed to stochastic thermal motion of the Au atoms and occurs at temperatures as low as 10 K. In addition, we also find that the ductile-to-brittle model, which was developed using classical dislocation theory, holds for nanowires as small as 3 nm in diameter. Finally, we demonstrate that the nanowire critical length is higher at 298 K relative to 10 K, a result that is not predicted by the ductile-to-brittle model. These results offer practical design strategies for adjusting nanowire failure and structure, and also demonstrate that GPU computing is an excellent tool for studies requiring a large number independent trajectories in order to fully characterize a system’s behavior.
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