Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube | Nanoscale Res Lett 2009 4 1054-1058 DOI S11671-009-9361-3 NANO EXPRESS An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube Samad Ahadian Yoshiyuki Kawazoe Received 30 April 2009 Accepted 24 May 2009 Published online 4 June 2009 to the authors 2009 Abstract Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation an adaptive-network-based fuzzy inference system ANFIS is presented to solve this problem. The proposed ANFIS approach can construct an inputoutput mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input-output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down. Keywords Carbon nanotube Water diffusion Artificial intelligence Modeling and prediction Introduction Carbon nanotubes CNTs have drawn much attention not only for their exceptional mechanical and electrical properties but also for their application in the new emerging area of nanofluidics since they can transport fluids at an extraordinarily fast flow rate. This property has diverse applications such as in charge storage devices 1 membrane industry 2 drug-delivery devices 3 and understanding the transport processes in biological channels 4 . In the past few years a significant number of works have been devoted to the study of fluid flow through CNTs S. Ahadian El Y. Kawazoe Institute for Materials Research IMR Tohoku University Sendai 980-8577 Japan e-mail ahadian@ samad_ahadian@ 5-8 . Fast pressure-driven flow of fluids in membranes of CNTs and 7 nm in diameter has been measured by Majumder et al. 5 and Holt et al. 6 respectively. They indicated measured values of 2 to 5 orders of magnitude larger than those calculated by the continuum-based no-slip
