Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology

In this study, 10% Ni/La2O3single bondMgAl2O4 nano-flake catalyst was synthesized, characterized and tested in a catalytic dielectric barrier discharge (DBD) plasma for dry reforming of methane (DRM). With design of experiment (DoE), the influence of process parameters namely (1) total feed flow rat...

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Main Authors: Khoja, Asif Hussain, Muhammad Tahir, Muhammad Tahir, Saidina Amin, Nor Aishah
Format: Article
Published: Elsevier Ltd. 2019
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Online Access:http://eprints.utm.my/id/eprint/87839/
http://dx.doi.org/10.1016/j.ijhydene.2019.03.059
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spelling my.utm.878392020-11-30T13:28:26Z http://eprints.utm.my/id/eprint/87839/ Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology Khoja, Asif Hussain Muhammad Tahir, Muhammad Tahir Saidina Amin, Nor Aishah TP Chemical technology In this study, 10% Ni/La2O3single bondMgAl2O4 nano-flake catalyst was synthesized, characterized and tested in a catalytic dielectric barrier discharge (DBD) plasma for dry reforming of methane (DRM). With design of experiment (DoE), the influence of process parameters namely (1) total feed flow rate (ml min−1), (2) feed ratio (CO2/CH4), (3) input power (W) and (4) catalyst loading (g) were examined using multiple response surface methodology (RSM) through a four-factor, five-level central composite design (CCD). Second-order regression models were applied for evaluating the interaction between the process parameters and responses. Input power (X3) and total feed flow rate (X1) were the two most influential process parameters followed by catalyst loading (X4) and feed ratio (X2). The experimental and predicted results from the optimum conditions fitted-well with less than ±5% margin of error. The possible dynamic interactions between the process variables were elucidated. The optimum values are feed flow rate = 18.8 ml min−1, feed ratio = 1.05, input power = 125.6 W and catalyst loading = 0.6 g. At these conditions, the predicted CH4 and CO2 conversions are 79.86% and 84.03%, respectively. The H2 and CO yields are predicted as 41.37% and 40.47%, respectively while H2/CO ratio is above unity. The calculated EE from the RSM model is predicted as 0.135 mmol kJ−1. Low carbon deposition observed on the spent catalyst is attributed to the highly basic and oxidative nature of the La2O3 co-supported catalyst. Elsevier Ltd. 2019-05 Article PeerReviewed Khoja, Asif Hussain and Muhammad Tahir, Muhammad Tahir and Saidina Amin, Nor Aishah (2019) Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology. International Journal of Hydrogen Energy, 44 (23). pp. 11774-11787. ISSN 0926-3373 http://dx.doi.org/10.1016/j.ijhydene.2019.03.059
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/
topic TP Chemical technology
spellingShingle TP Chemical technology
Khoja, Asif Hussain
Muhammad Tahir, Muhammad Tahir
Saidina Amin, Nor Aishah
Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology
description In this study, 10% Ni/La2O3single bondMgAl2O4 nano-flake catalyst was synthesized, characterized and tested in a catalytic dielectric barrier discharge (DBD) plasma for dry reforming of methane (DRM). With design of experiment (DoE), the influence of process parameters namely (1) total feed flow rate (ml min−1), (2) feed ratio (CO2/CH4), (3) input power (W) and (4) catalyst loading (g) were examined using multiple response surface methodology (RSM) through a four-factor, five-level central composite design (CCD). Second-order regression models were applied for evaluating the interaction between the process parameters and responses. Input power (X3) and total feed flow rate (X1) were the two most influential process parameters followed by catalyst loading (X4) and feed ratio (X2). The experimental and predicted results from the optimum conditions fitted-well with less than ±5% margin of error. The possible dynamic interactions between the process variables were elucidated. The optimum values are feed flow rate = 18.8 ml min−1, feed ratio = 1.05, input power = 125.6 W and catalyst loading = 0.6 g. At these conditions, the predicted CH4 and CO2 conversions are 79.86% and 84.03%, respectively. The H2 and CO yields are predicted as 41.37% and 40.47%, respectively while H2/CO ratio is above unity. The calculated EE from the RSM model is predicted as 0.135 mmol kJ−1. Low carbon deposition observed on the spent catalyst is attributed to the highly basic and oxidative nature of the La2O3 co-supported catalyst.
format Article
author Khoja, Asif Hussain
Muhammad Tahir, Muhammad Tahir
Saidina Amin, Nor Aishah
author_facet Khoja, Asif Hussain
Muhammad Tahir, Muhammad Tahir
Saidina Amin, Nor Aishah
author_sort Khoja, Asif Hussain
title Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology
title_short Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology
title_full Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology
title_fullStr Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology
title_full_unstemmed Process optimization of DBD plasma dry reforming of methane over Ni/La2O3single bondMgAl2O4 using multiple response surface methodology
title_sort process optimization of dbd plasma dry reforming of methane over ni/la2o3single bondmgal2o4 using multiple response surface methodology
publisher Elsevier Ltd.
publishDate 2019
url http://eprints.utm.my/id/eprint/87839/
http://dx.doi.org/10.1016/j.ijhydene.2019.03.059
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score 13.18916