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Hydrogen desorption study of as-synthesized carbon nanotubes using artificial neural network

Abdul Rahman, Ali and Arshad, Khairil Anuar and Abd. Razak, Norhuda and M. Sanip, Suhaila and Ismail, Ahmad Fauzi (2005) Hydrogen desorption study of as-synthesized carbon nanotubes using artificial neural network. In: 3rd International Conference on Materials for Advanced Technologies (ICMAT 2005) and 9th International Conference On Advanced Materials (ICAM 2005), 3-8 July 2005, Singapore.

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Abstract

Carbon nanotubes are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Reports suggest that the total surface area of carbon affects the hydrogen storage capacities in carbon nanotubes. Based on the experimental data of as-synthesized carbon nanotubes, an artificial neural network (ANN) model was developed to study the relationship between the surface area of carbon and the hydrogen desorption. The model was also used to study the effect of carbon and alumina content to the hydrogen desorption. A feedforward ANN was used for the prediction. The ANN was trained using the Levenberg-Marquardt training algorithm.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Carbon nanotubes, modeling, neural network, surface area
Subjects:T Technology > T Technology (General)
Divisions:Chemical and Natural Resources Engineering (Formerly known)
ID Code:5423
Deposited By: Norhani Jusoh
Deposited On:22 Apr 2008 10:17
Last Modified:01 Jun 2010 15:30

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