Andrew P. Santos | Searcharxiv

arXiv2017

From Compact to Open Clusters in Systems with Competing Interactions

Colloidal particles, amphiphiles, and functionalized nanoparticles are examples of systems that frequently exhibit short-range attractions coupled with long-range repulsions. In this work, we observe striking differences in the dynamics of self-assembled clusters that form in a simple isotropic model of such systems when the strength of attraction is varied. We find that while attraction-dominated particles self-assemble into compact clusters with properties similar to micelles formed by amphiphilic molecules, repulsion-dominated particles self-assemble into open clusters which have much shorter life-times. There is also a significantly different dependence of the solution osmotic pressure versus composition: formation of compact clusters causes a decrease in the pressure vs. density slope, while formation of open clusters does not effect the pressure. This thermodynamic quantity turns out to be much more sensitive in picking out different clustering characteristics than the overall aggregation curves or cluster shapes. Our results have significant implications in developing design principles for stable cluster self-assembly and detection in both laboratory settings and in computer simulations.

cond-mat.soft↗

arXiv2013

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

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.

cond-mat.mes-hall↗