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Chlorophenol sorption on multi-walled carbon nanotubes: DFT modeling and structure–property relationship analysis

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Abstract

The presence of chlorophenols in drinking water can be hazardous to human health. Understanding the mechanisms of adsorption under specific experimental conditions would be beneficial when developing methods to remove toxic substances from drinking water during water treatment in order to limit human exposure to these contaminants. In this study, we investigated the sorption of chlorophenols on multi-walled carbon nanotubes using a density functional theory (DFT) approach. This was applied to study selected interactions between six solvents, five types of nanotubes, and six chlorophenols. Experimental data were used to construct structure–adsorption relationship (SAR) models that describe the recovery process. Specific interactions between solvents and chlorophenols were taken into account in the calculations by using novel specific mixture descriptors.

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Acknowledgements

The authors thank the National Science Foundation for financial support (NSF EPSCoR # 362492-190200-01\NSFEPS-0903787 and NSF CREST grant HRD # 1547754).

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Authors and Affiliations

  1. Interdisciplinary Center for Nanotoxicity, Jackson State University, 1400 J.R. Lynch Street, Jackson, MS, 39217, USA

    Marquita Watkins, Natalia Sizochenko, Quentarius Moore & Jerzy Leszczynski

  2. Laboratory of Analysis of Natural Compounds, Department of Environmental Analysis, Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, 80-308, Gdańsk, Poland

    Marek Golebiowski

  3. Department of Civil and Environmental Engineering, Jackson State University, Jackson, MS, 39217, USA

    Danuta Leszczynska

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  1. Marquita Watkins
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  2. Natalia Sizochenko
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  5. Danuta Leszczynska
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Correspondence to Jerzy Leszczynski.

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This paper belongs to Topical Collection 7th Conference on Modeling & Design of Molecular Materials in Trzebnica (MDMM 2016)

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Watkins, M., Sizochenko, N., Moore, Q. et al. Chlorophenol sorption on multi-walled carbon nanotubes: DFT modeling and structure–property relationship analysis. J Mol Model 23, 39 (2017). https://doi.org/10.1007/s00894-016-3204-9

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