Nano Express

Nanoscale Research Letters

, Volume 4, Issue 9, pp 1054-1058

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube

  • Samad AhadianAffiliated withInstitute for Materials Research (IMR), Tohoku University Email author 
  • , Yoshiyuki KawazoeAffiliated withInstitute for Materials Research (IMR), Tohoku University


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 input–output 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.


Carbon nanotube Water diffusion Artificial intelligence Modeling and prediction