Modelling of water flow in carbon nanotubes was still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system was presented to solve this problem. The proposed adaptive-network-based fuzzy inference system approach could construct an input-output mapping based upon both human knowledge in the form of fuzzy if-then rules and stipulated input-output data pairs. Good performance of the designed adaptive-network-based fuzzy inference system ensures its capability as a promising tool for modelling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down.An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion inside a Carbon Nanotube. Ahadian, S., Kawazoe, Y.: Nanoscale Research Letters, 2009, 4[9], 1054-8