Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling
Wastewater pollution from toxic inorganic and organic contaminants poses serious environmental and health threats and must be removed. In response, graphene oxide/zeolitic imidazolate frameworks composites have gained attention for combining useful features of both materials in wastewater treatment....
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Elsevier
2025-09-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025024818 |
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| author | Ahmed I. Ibrahim Sagheer A. Onaizi Muhammad S. Vohra |
| author_facet | Ahmed I. Ibrahim Sagheer A. Onaizi Muhammad S. Vohra |
| author_sort | Ahmed I. Ibrahim |
| collection | DOAJ |
| description | Wastewater pollution from toxic inorganic and organic contaminants poses serious environmental and health threats and must be removed. In response, graphene oxide/zeolitic imidazolate frameworks composites have gained attention for combining useful features of both materials in wastewater treatment. In this study, a novel cetyltrimethylammonium bromide/graphene oxide/zeolitic imidazolate framework-9 (CTAB@GO/ZIF-9) nanocomposite was synthesized and employed for the adsorption of lead (Pb2+) and methyl orange (MO) from aqueous media. The adsorption process was optimized using response surface methodology (RSM), and artificial neural networks (ANN) were applied to improve the prediction accuracy. RSM identified adsorbent mass, pollutant concentration, and temperature as significant parameters affecting adsorption capacity. ANN models outperformed RSM in prediction, achieving R2 values of 0.975 for Pb2+ and 0.991 for MO. The isotherm study showed that Pb2+ adsorption followed the Freundlich (R2 = 0.907) and Redlich–Peterson (R2 = 0.908) models, while MO fitted the Langmuir (R2 = 0.995) and Redlich–Peterson (R2 = 0.997) models, with maximum adsorption capacities of 1139.7 mg/g and 1195 mg/g, respectively. The kinetic findings indicated that the Avrami model best described both adsorption processes, with R2 values of 0.999 for Pb2+ and 0.995 for MO, suggesting a multi-step mechanism. The thermodynamic analysis confirmed the spontaneity of adsorption: Pb2+ removal was endothermic and entropy-driven, while MO adsorption was exothermic with decreased entropy. Possible adsorption mechanisms involved coordination interactions for Pb2+ and electrostatic and π–π interactions for MO. These results demonstrate the high efficiency of CTAB@GO/ZIF-9 as a versatile adsorbent for various pollutants in wastewater treatment. |
| format | Article |
| id | doaj-art-abe97e3eadf244df970e98a24c01095b |
| institution | DOAJ |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-abe97e3eadf244df970e98a24c01095b2025-08-20T03:13:57ZengElsevierResults in Engineering2590-12302025-09-012710641110.1016/j.rineng.2025.106411Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modelingAhmed I. Ibrahim0Sagheer A. Onaizi1Muhammad S. Vohra2Civil and Environmental Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi ArabiaChemical Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia; Interdisciplinary Research Center for Hydrogen and Energy Storage, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi ArabiaCivil and Environmental Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia; Interdisciplinary Research Center for Construction and Building Materials, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia; Corresponding author.Wastewater pollution from toxic inorganic and organic contaminants poses serious environmental and health threats and must be removed. In response, graphene oxide/zeolitic imidazolate frameworks composites have gained attention for combining useful features of both materials in wastewater treatment. In this study, a novel cetyltrimethylammonium bromide/graphene oxide/zeolitic imidazolate framework-9 (CTAB@GO/ZIF-9) nanocomposite was synthesized and employed for the adsorption of lead (Pb2+) and methyl orange (MO) from aqueous media. The adsorption process was optimized using response surface methodology (RSM), and artificial neural networks (ANN) were applied to improve the prediction accuracy. RSM identified adsorbent mass, pollutant concentration, and temperature as significant parameters affecting adsorption capacity. ANN models outperformed RSM in prediction, achieving R2 values of 0.975 for Pb2+ and 0.991 for MO. The isotherm study showed that Pb2+ adsorption followed the Freundlich (R2 = 0.907) and Redlich–Peterson (R2 = 0.908) models, while MO fitted the Langmuir (R2 = 0.995) and Redlich–Peterson (R2 = 0.997) models, with maximum adsorption capacities of 1139.7 mg/g and 1195 mg/g, respectively. The kinetic findings indicated that the Avrami model best described both adsorption processes, with R2 values of 0.999 for Pb2+ and 0.995 for MO, suggesting a multi-step mechanism. The thermodynamic analysis confirmed the spontaneity of adsorption: Pb2+ removal was endothermic and entropy-driven, while MO adsorption was exothermic with decreased entropy. Possible adsorption mechanisms involved coordination interactions for Pb2+ and electrostatic and π–π interactions for MO. These results demonstrate the high efficiency of CTAB@GO/ZIF-9 as a versatile adsorbent for various pollutants in wastewater treatment.http://www.sciencedirect.com/science/article/pii/S2590123025024818Lead removalMethyl orange removalZeolitic imidazolate framework-9CTAB-modified GOResponse surface methodologyArtificial neural network |
| spellingShingle | Ahmed I. Ibrahim Sagheer A. Onaizi Muhammad S. Vohra Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling Results in Engineering Lead removal Methyl orange removal Zeolitic imidazolate framework-9 CTAB-modified GO Response surface methodology Artificial neural network |
| title | Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling |
| title_full | Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling |
| title_fullStr | Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling |
| title_full_unstemmed | Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling |
| title_short | Incorporation of surfactant-intercalated graphene oxide into zeolitic imidazolate framework-9 for effective heavy metal and dye removal from wastewater: RSM optimization and ANN modeling |
| title_sort | incorporation of surfactant intercalated graphene oxide into zeolitic imidazolate framework 9 for effective heavy metal and dye removal from wastewater rsm optimization and ann modeling |
| topic | Lead removal Methyl orange removal Zeolitic imidazolate framework-9 CTAB-modified GO Response surface methodology Artificial neural network |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025024818 |
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