A First-Principles Study on Water Flow Through Single-Walled Carbon Nanotubes Using Artificial Neural Network Method
Ab initio molecular dynamics simulations are done to elucidate the electronic structure and properties of water/single-walled carbon nanotubes (SWCNTs) systems. The artificial neural network (ANN) approach and statistical methods are then used to model and analyze these properties. The ANN method substantially speeds up the ab initio electronic structure calculations and has superior accuracy in mimicking the results of such calculations. We aim to understand the effects of CNT chirality, temperature, and CNT flexibility on the water diffusion inside SWCNTs. In this regard, the CNT is fixed implies that the position of CNT is kept constant during the diffusion process. Statistical analysis of results shows that there is a nonmonotonic variation of diffusion length of water with respect to the CNT chirality. However, an increase in temperature and rigid CNTs accelerate the water diffusion.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
Document Type: Research Article
Publication date: 2011-11-01
More about this publication?
- Journal for Nanoscience and Nanotechnology (JNN) is an international and multidisciplinary peer-reviewed journal with a wide-ranging coverage, consolidating research activities in all areas of nanoscience and nanotechnology into a single and unique reference source. JNN is the first cross-disciplinary journal to publish original full research articles, rapid communications of important new scientific and technological findings, timely state-of-the-art reviews with author's photo and short biography, and current research news encompassing the fundamental and applied research in all disciplines of science, engineering and medicine.
- Editorial Board
- Information for Authors
- Subscribe to this Title
- Terms & Conditions
- Ingenta Connect is not responsible for the content or availability of external websites