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Adsorption of malachite green dye onto almond peel waste: a study focusing on application of the ANN approach for optimization of the effect of environmental parameters

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Abstract

Almond peel waste was collected, characterized, and then used as an adsorbent for removing malachite green (MG) dye from aqueous solutions. The environmental conditions of MG dye adsorption were pH, 2.5–10.5; almond peel dose, 0.25–1.5 g/L; initial MG concentration, 10–60 mg/L; and adsorption time, 0–180 min. These were optimized by using an artificial neural network (ANN) tool. At pH = 8.5, 96.1% of the MG dye could be removed using almond peels. According to the coefficient of determination results, the Langmuir isotherm proved to be the equation that best fit the data of the isotherm study. Furthermore, the kinetic study showed that the data on MG adsorption of the almond peel waste was consistent with the pseudo-second-order model. The ANN model was developed by using a three-layer, feed-forward network with an optimum architecture of 4:10:1. Sigmoid functions were employed in both inputs and hidden layers, as also those hidden in the output layers. The results indicated a high correlation value (R = 0.976) to predict the entire experimental dataset, which indicated the applicability of the ANN tool, to describe the MG adsorption data in a highly accurate manner. The important conclusion of this study, after comparison with other similar adsorbents used in the adsorption process of dye wastewater, revealed that almond peel waste is a cheap, recyclable, and effective adsorptive agent, thus a good alternative to remove dyes from aqueous solutions.

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Acknowledgements

The authors express their sincere gratitude to the Payame Noor University of Tehran, Birjand University of Medical Sciences and Al-Mustaqbal University college for financing and scientific supporting of the current study.

Funding

Birjand University of Medical Sciences has provided financial support for this research.

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Authors and Affiliations

  1. Building and Construction Techniques Engineering Department, Al-Mustaqbal University College, Al-Mustaqbal University College, Babylon, 51001, Hillah, Iraq

    Tariq J. Al-Musawi

  2. Department of Artificial Intelligence, Faculty of Computer Engineering, Kharazmi University, Tehran, Iran

    Sayyed Mohammad Ali Arghavan

  3. Medical Toxicology and Drug Abuse Research Center (MTDRC), Birjand University of Medical Sciences (BUMS), Birjand, Iran

    Elaheh Allahyari

  4. Department of Chemistry, Faculty of Sciences of Monastir, University of Monastir, Avenue of the Environment, 5019, Monastir, Tunisia

    Fatemeh Sadat Arghavan

  5. Student Research Committee, Department of Environmental Health Engineering, Faculty of Health, Mashhad University of Medical Sciences, Mashhad, Iran

    Amina Othmani

  6. Department of Environmental Health Engineering, Faculty of Health, Social Determinants of Health Research Center, Birjand University of Medical Sciences, Birjand, Iran

    Negin Nasseh

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  1. Tariq J. Al-Musawi
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  2. Sayyed Mohammad Ali Arghavan
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  3. Elaheh Allahyari
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  4. Fatemeh Sadat Arghavan
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  5. Amina Othmani
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  6. Negin Nasseh
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Contributions

N.N., conceptualization, methodology, and project administration; T.A.M., investigation, resources, and data curation; S.F.A., writing—original draft preparation, software, and validation; S.M.A.A and E.A, performed neural network analyzes; T.A.M and A.O., writing—review and editing, resources, and data curation. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Negin Nasseh.

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Al-Musawi, T.J., Arghavan, S.M.A., Allahyari, E. et al. Adsorption of malachite green dye onto almond peel waste: a study focusing on application of the ANN approach for optimization of the effect of environmental parameters. Biomass Conv. Bioref. 13, 12073–12084 (2023). https://doi.org/10.1007/s13399-021-02174-6

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  • DOI: https://doi.org/10.1007/s13399-021-02174-6

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