Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area

The discovery of carbon nanotubes (CNT) by Sumiio Iijima in 1991 has attracted many researchers worldwide to study and explore thc newly found materials. CNT are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Rcccnt reports suggest t...

Full description

Saved in:
Bibliographic Details
Main Authors: Razak, N.A., Arshad, K.A., Rahman , A.A., Ismail , A.F., Sanip, S.M.
Format: Article
Language:English
Published: 2004
Subjects:
Online Access:http://eprints.utm.my/id/eprint/706/1/AhmadFauziIsmail2004_ArtificialNeuralNetworkModelingOf_.pdf
http://eprints.utm.my/id/eprint/706/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
Language: English
id my.utm.706
record_format eprints
spelling my.utm.7062017-09-06T06:39:38Z http://eprints.utm.my/id/eprint/706/ Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area Razak, N.A. Arshad, K.A. Rahman , A.A. Ismail , A.F. Sanip, S.M. TP Chemical technology The discovery of carbon nanotubes (CNT) by Sumiio Iijima in 1991 has attracted many researchers worldwide to study and explore thc newly found materials. CNT are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Rcccnt reports suggest that total surfacc area of carbon affect the hydrogen storage capacities in carbon nanotubes. An Artificial Neural Network model was created to study the relationship between the surface area of carbon and the hydrogen adsorption. 2004 Article NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/706/1/AhmadFauziIsmail2004_ArtificialNeuralNetworkModelingOf_.pdf Razak, N.A. and Arshad, K.A. and Rahman , A.A. and Ismail , A.F. and Sanip, S.M. (2004) Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area. Proceedings of Advances in Fuel Cell Research and Development in Malaysia . pp. 165-169.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Razak, N.A.
Arshad, K.A.
Rahman , A.A.
Ismail , A.F.
Sanip, S.M.
Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area
description The discovery of carbon nanotubes (CNT) by Sumiio Iijima in 1991 has attracted many researchers worldwide to study and explore thc newly found materials. CNT are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Rcccnt reports suggest that total surfacc area of carbon affect the hydrogen storage capacities in carbon nanotubes. An Artificial Neural Network model was created to study the relationship between the surface area of carbon and the hydrogen adsorption.
format Article
author Razak, N.A.
Arshad, K.A.
Rahman , A.A.
Ismail , A.F.
Sanip, S.M.
author_facet Razak, N.A.
Arshad, K.A.
Rahman , A.A.
Ismail , A.F.
Sanip, S.M.
author_sort Razak, N.A.
title Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area
title_short Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area
title_full Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area
title_fullStr Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area
title_full_unstemmed Artificial Neural Network Modeling Of Hydrogen Uptake Based On Carbon Surface Area
title_sort artificial neural network modeling of hydrogen uptake based on carbon surface area
publishDate 2004
url http://eprints.utm.my/id/eprint/706/1/AhmadFauziIsmail2004_ArtificialNeuralNetworkModelingOf_.pdf
http://eprints.utm.my/id/eprint/706/
_version_ 1643643164694675456