Monte Carlo simulation of carbon nanotube nucleation and growth using nonlinear dynamic predictions
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The computation time for Monte Carlo (MC) simulation of a nanostructure growth process was shown to be reduced by an order of magnitude compared to conventional atomistic and meso-scale models through the prediction of the structure evolution ahead of every growth step. This approach used to grow of one of the longest (194 nm) reported carbon nanotubes (CNTs) from atomistic simulations. The key to the approach is the finding from simulation experiments that the CNT synthesis process exhibits nonlinear and recurring near-stationary dynamics. 2012 Elsevier B.V. All rights reserved.
