Towards control of carbon nanotube synthesis process using prediction-based fast Monte Carlo simulations
Academic Article
Overview
Research
Identity
Additional Document Info
Other
View All
Overview
abstract
Precise control of the lengths of carbon nanotube (CNT) and other nanostructures is important for various industrial applications. However, time-resolution (1 min) of current in situ measurements does not allow control of lengths to within 20 nm. We present an approach to combine intermittent in situ measurements with length estimates from a fast atomistic Monte Carlo (MC) simulation of CNT synthesis. The MC simulation time was reduced by >70% through prediction of the nonlinear and nonstationary growth increments, and initialization of relaxation process (the most computationally intensive step in MC simulations) with the near-optimum predicted positions, leading to one of the longest (194 nm) CNTs from atomistic simulations. A utility function of growth predictions was defined so that its maximization specified the end-point of the synthesis process. Extensive simulation studies indicate that the approach can be used to control CNT lengths to within 1 nm of specifications. 2012 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
