Artificial neural network modelling for the prediction of carbon surface area
Carbon nanotubes are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Recent reports suggest that total surface area of carbon nanotubes affect the hydrogen storage capacities in carbon nanotubes. An Artificial Neural Network model has...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://eprints.utm.my/6079/1/NorhudaAbd.Razak2004_ArtificialNeuralNetworkModelling.pdf |
| _version_ | 1796854015915458560 |
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| author | Abd. Razak, Norhuda Arshad, Khairil Anuar Abd. Rahman, Ali M. Sanip, Suhaila Ismail, Ahmad Fauzi |
| author_facet | Abd. Razak, Norhuda Arshad, Khairil Anuar Abd. Rahman, Ali M. Sanip, Suhaila Ismail, Ahmad Fauzi |
| author_sort | Abd. Razak, Norhuda |
| collection | ePrints |
| description | Carbon nanotubes are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Recent reports suggest that total surface area of carbon nanotubes affect the hydrogen storage capacities in carbon nanotubes. An Artificial Neural Network model has been created for the prediction of the surface area of carbon. The model is used to study the influence of the different type of carbon on the hydrogen storage properties of carbon nanotubes. |
| first_indexed | 2024-03-05T18:08:05Z |
| format | Conference or Workshop Item |
| id | utm.eprints-6079 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T18:08:05Z |
| publishDate | 2004 |
| record_format | dspace |
| spelling | utm.eprints-60792010-06-01T15:38:39Z http://eprints.utm.my/6079/ Artificial neural network modelling for the prediction of carbon surface area Abd. Razak, Norhuda Arshad, Khairil Anuar Abd. Rahman, Ali M. Sanip, Suhaila Ismail, Ahmad Fauzi T Technology (General) Carbon nanotubes are considered for hydrogen storage due to their low density, high strength, and hydrogen adsorption characteristics. Recent reports suggest that total surface area of carbon nanotubes affect the hydrogen storage capacities in carbon nanotubes. An Artificial Neural Network model has been created for the prediction of the surface area of carbon. The model is used to study the influence of the different type of carbon on the hydrogen storage properties of carbon nanotubes. 2004 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/6079/1/NorhudaAbd.Razak2004_ArtificialNeuralNetworkModelling.pdf Abd. Razak, Norhuda and Arshad, Khairil Anuar and Abd. Rahman, Ali and M. Sanip, Suhaila and Ismail, Ahmad Fauzi (2004) Artificial neural network modelling for the prediction of carbon surface area. In: The XXI Regional Conference on Solid State Science & Technology 2004, 12-13 October 2004, Hyatt Regency Kinabalu, Sabah, Malaysia. |
| spellingShingle | T Technology (General) Abd. Razak, Norhuda Arshad, Khairil Anuar Abd. Rahman, Ali M. Sanip, Suhaila Ismail, Ahmad Fauzi Artificial neural network modelling for the prediction of carbon surface area |
| title | Artificial neural network modelling for the prediction of carbon surface area |
| title_full | Artificial neural network modelling for the prediction of carbon surface area |
| title_fullStr | Artificial neural network modelling for the prediction of carbon surface area |
| title_full_unstemmed | Artificial neural network modelling for the prediction of carbon surface area |
| title_short | Artificial neural network modelling for the prediction of carbon surface area |
| title_sort | artificial neural network modelling for the prediction of carbon surface area |
| topic | T Technology (General) |
| url | http://eprints.utm.my/6079/1/NorhudaAbd.Razak2004_ArtificialNeuralNetworkModelling.pdf |
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