Improved <i>Cupressus sempervirens</i> L. galls for methylene blue removal: adsorption kinetics optimisation using the DA-LS algorithm, characterisation, and machine learning modeling

In this study, an investigation was conducted on the effectiveness of three bioadsorbents – galbuli of Cupressus sempervirens L. almond shells, and Luffa – for removing methylene blue (MB) from water. Various activation techniques and operational conditions were employed to enhance the adsorption capacity. The study focused on adsorption kinetics and equilibrium capacity. The results showed that microwave-dried galbuli of Cupressus sempervirens L. exhibited the highest adsorption capacity of 38.05 mg/g with an adsorption efficiency of 17.4%. To improve this capacity, the Dragonfly Algorithm-integrated least squares (DA-LS) was proposed to optimise the fitting of 32 adsorption isotherm models, which included a proposed modified Langmuir model. After optimisation, the sixth chemical treatment of Cupressus sempervirens L. reached a Langmuir isotherm qmax value of 84.44 mg/g, suggesting the high efficiency of the bioadsorbent compared to previous studies. Characterisation using microscopy and ATR-FTIR techniques revealed that chemical modifications led to rougher, microporous cellulose fibres and significant changes in the chemical structure, potentially enhancing the surface area and adsorption efficiency. To predict the adsorption capacity, the Support Vector Machine for Regression with DA (SVMR-DA) was utilised, achieving a root mean square error (RMSE) of 1.357 and an R2 of 0.9913. This high accuracy indicates a reliable model with a robust error distribution. These results suggest that Cupressus sempervirens L. can be an effective bioadsorbent for water treatment, with significant potential for industrial application.

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Publication Details

Journal
International Journal of Environmental & Analytical Chemistry
Published
2024-08-05
DOI
https://doi.org/10.1080/03067319.2024.2382374
Citations
10
Primary Topic
Water Quality Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
2.93
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article

Improved Cupressus sempervirens L. galls for methylene blue removal: adsorption kinetics optimisation using the DA-LS algorithm, characterisation, and machine learning modeling

Abd-Elmouneïm Belhadj, Mohamed Kouider Amar, Mohamed Hentabli
10 citations
International Journal of Environmental & Analytical Chemistry
Water Quality Monitoring and Analysis
2.93
article

Improved Cupressus sempervirens L. galls for methylene blue removal: adsorption kinetics optimisation using the DA-LS algorithm, characterisation, and machine learning modeling

Abd-Elmouneïm Belhadj, Mohamed Kouider Amar, Mohamed Hentabli
article en
10 citations

Abstract

In this study, an investigation was conducted on the effectiveness of three bioadsorbents – galbuli of Cupressus sempervirens L. almond shells, and Luffa – for removing methylene blue (MB) from water. Various activation techniques and operational conditions were employed to enhance the adsorption capacity. The study focused on adsorption kinetics and equilibrium capacity. The results showed that microwave-dried galbuli of Cupressus sempervirens L. exhibited the highest adsorption capacity of 38.05 mg/g with an adsorption efficiency of 17.4%. To improve this capacity, the Dragonfly Algorithm-integrated least squares (DA-LS) was proposed to optimise the fitting of 32 adsorption isotherm models, which included a proposed modified Langmuir model. After optimisation, the sixth chemical treatment of Cupressus sempervirens L. reached a Langmuir isotherm qmax value of 84.44 mg/g, suggesting the high efficiency of the bioadsorbent compared to previous studies. Characterisation using microscopy and ATR-FTIR techniques revealed that chemical modifications led to rougher, microporous cellulose fibres and significant changes in the chemical structure, potentially enhancing the surface area and adsorption efficiency. To predict the adsorption capacity, the Support Vector Machine for Regression with DA (SVMR-DA) was utilised, achieving a root mean square error (RMSE) of 1.357 and an R2 of 0.9913. This high accuracy indicates a reliable model with a robust error distribution. These results suggest that Cupressus sempervirens L. can be an effective bioadsorbent for water treatment, with significant potential for industrial application.

International Journal of Environmental & Analytical ChemistryVol. 105(17)
University Yahia Fares of Medea (DZ), Medidata (United States) (US)
Openalex Percentile: Top 10%
Water Quality Monitoring and Analysis
2.93
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