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Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models

Metal pollutants such as copper released into the aqueous environment have been increasing as a result of anthropogenic activities. Adsorption-based treatment technologies offer opportunities to remediate metal pollutants from municipal and industrial wastewater effluent. The aim of this work was to...

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Main Authors: Abdul Hamid, Nor Hazren, Harun, H., Sunar, N. M., Ahmad, Faridah Hanim, Jasmani, Latifah, Suleiman, Norhidayah
Format: Article
Language:English
Published: Science Publishing Corporation 2018
Online Access:http://psasir.upm.edu.my/id/eprint/73585/1/Predicting%20the%20capability%20of%20oxidized%20CNW%20adsorbents%20for%20the%20remediation%20of%20copper%20under%20optimal%20operating%20conditions%20using%20RSM%20and%20ANN%20models.pdf
http://psasir.upm.edu.my/id/eprint/73585/
https://www.sciencepubco.com/index.php/ijet/article/view/22279
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spelling my.upm.eprints.735852020-07-07T02:27:50Z http://psasir.upm.edu.my/id/eprint/73585/ Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models Abdul Hamid, Nor Hazren Harun, H. Sunar, N. M. Ahmad, Faridah Hanim Jasmani, Latifah Suleiman, Norhidayah Metal pollutants such as copper released into the aqueous environment have been increasing as a result of anthropogenic activities. Adsorption-based treatment technologies offer opportunities to remediate metal pollutants from municipal and industrial wastewater effluent. The aim of this work was to evaluate the capability of modified cellulose nanowhisker (CNW) adsorbents for the remediation of copper from water matrices under realistic conditions using response surface methodology (RSM) and artificial neural network (ANN) models. Considerations for design and application to remediate Cu(II) from wastewater by developing a continuous flow experiment are described in this study. However, the physical structure of modified CNW adsorbents renders them unsuitable for use in column operation. Therefore, a more detailed study of the mechanical properties of CNW adsorbents would be necessary in order to improve the strength and stability of the adsorbents. This work has demonstrated that modified CNW are promising adsorbents to remediate copper from water matrices under realistic conditions including wastewater complexity and variability. The use of models to predict the test parameter system and account for matrix variability when evaluating CNW adsorbents for remediating Cu from a real-world wastewater matrix may also provide the foundation for assessing other treatment technologies in the future. Science Publishing Corporation 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/73585/1/Predicting%20the%20capability%20of%20oxidized%20CNW%20adsorbents%20for%20the%20remediation%20of%20copper%20under%20optimal%20operating%20conditions%20using%20RSM%20and%20ANN%20models.pdf Abdul Hamid, Nor Hazren and Harun, H. and Sunar, N. M. and Ahmad, Faridah Hanim and Jasmani, Latifah and Suleiman, Norhidayah (2018) Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models. International Journal of Engineering and Technology (UAE), 7 (4.30). 264 - 268. ISSN 2227-524X https://www.sciencepubco.com/index.php/ijet/article/view/22279 10.14419/ijet.v7i4.30.22279
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Metal pollutants such as copper released into the aqueous environment have been increasing as a result of anthropogenic activities. Adsorption-based treatment technologies offer opportunities to remediate metal pollutants from municipal and industrial wastewater effluent. The aim of this work was to evaluate the capability of modified cellulose nanowhisker (CNW) adsorbents for the remediation of copper from water matrices under realistic conditions using response surface methodology (RSM) and artificial neural network (ANN) models. Considerations for design and application to remediate Cu(II) from wastewater by developing a continuous flow experiment are described in this study. However, the physical structure of modified CNW adsorbents renders them unsuitable for use in column operation. Therefore, a more detailed study of the mechanical properties of CNW adsorbents would be necessary in order to improve the strength and stability of the adsorbents. This work has demonstrated that modified CNW are promising adsorbents to remediate copper from water matrices under realistic conditions including wastewater complexity and variability. The use of models to predict the test parameter system and account for matrix variability when evaluating CNW adsorbents for remediating Cu from a real-world wastewater matrix may also provide the foundation for assessing other treatment technologies in the future.
format Article
author Abdul Hamid, Nor Hazren
Harun, H.
Sunar, N. M.
Ahmad, Faridah Hanim
Jasmani, Latifah
Suleiman, Norhidayah
spellingShingle Abdul Hamid, Nor Hazren
Harun, H.
Sunar, N. M.
Ahmad, Faridah Hanim
Jasmani, Latifah
Suleiman, Norhidayah
Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models
author_facet Abdul Hamid, Nor Hazren
Harun, H.
Sunar, N. M.
Ahmad, Faridah Hanim
Jasmani, Latifah
Suleiman, Norhidayah
author_sort Abdul Hamid, Nor Hazren
title Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models
title_short Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models
title_full Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models
title_fullStr Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models
title_full_unstemmed Predicting the capability of oxidized CNW adsorbents for the remediation of copper under optimal operating conditions using RSM and ANN models
title_sort predicting the capability of oxidized cnw adsorbents for the remediation of copper under optimal operating conditions using rsm and ann models
publisher Science Publishing Corporation
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/73585/1/Predicting%20the%20capability%20of%20oxidized%20CNW%20adsorbents%20for%20the%20remediation%20of%20copper%20under%20optimal%20operating%20conditions%20using%20RSM%20and%20ANN%20models.pdf
http://psasir.upm.edu.my/id/eprint/73585/
https://www.sciencepubco.com/index.php/ijet/article/view/22279
_version_ 1672612207519596544
score 13.211869

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