Amine-functionalized cellulose for the efficient removal of anionic micropollutants from aqueous environments: Development, characterization, and modeling
- Authors
- Jin, Se-Ra; Lee, Kwan-Yong; Park, Si-Hyeon; Cheon, Jeong-Min; Kang, Su Bin; Cho, Chul-Woong
- Issue Date
- Jun-2025
- Publisher
- Elsevier Limited
- Keywords
- Adsorption; Micropollutants; Polyethylenimine cross-linked cellulose; Prediction; Quantitative structure-activity relationship modeling
- Citation
- Journal of Water Process Engineering, v.75
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Water Process Engineering
- Volume
- 75
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/78671
- DOI
- 10.1016/j.jwpe.2025.107940
- ISSN
- 2214-7144
2214-7144
- Abstract
- Cellulose, the most abundant natural biomass, is combined with polyethylenimine (PEI) to develop an efficient adsorbent for the removal of anionic organic micropollutants. In general, cellulose is commonly used as a precursor for developing adsorbents aimed at removing micropollutants from aqueous environments. However, raw cellulose exhibits relatively low efficiency in adsorbing anionic micropollutants. To enhance its adsorptive capacity, the surface of cellulose was chemically modified through cross-linking with PEI, introducing several amine groups capable of attracting anionic species, using ethylene glycol diglycidyl ether (EGDE) as the cross-linker. After preparing the PEI-coated cellulose adsorbent, kinetic experiments were conducted at pH levels of 4.5 and 6.5, using ibuprofen—a common anionic pharmaceutical compound—as the model compound. The results demonstrated that, at pH 4.5, adsorption equilibrium was achieved within 30 min, while at pH 6.5, equilibrium was reached within 1 h. Additionally, isotherm experiments were conducted to evaluate the adsorption capacity of the PEI-cellulose for 29 anionic micropollutants. Furthermore, to extend the application of the experimental results, the adsorption of anionic micropollutants on PEI-cellulose was predicted using quantitative structure-activity relationship (QSAR) modeling, with molecular descriptors calculated using density functional theory and conductor-like screening model. The developed model exhibits reasonable predictive capacity, with an R2 value of 0.841. In conclusion, PEI-cellulose significantly enhances its ability to remove anionic micropollutants, making it a promising adsorbent for water treatment applications. © 2025 Elsevier Ltd
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