Probing the Statistical Validity of the Ductile-to-Brittle Transition in Metallic Nanowires Using GPU Computing
WR French and AK Pervaje and AP Santos and CR Iacovella and PT Cummings, JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 9, 5558-5566 (2013).
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. 2012, 12, 910-914. 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 of independent trajectories in order to fully characterize a system's behavior.
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