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DOI 10.1016/j.jhazmat.2025.137742

Медицинская библиотека · Journal of hazardous materials · 2025

Comparative immobilization of 30 PFAS mixtures onto biochar, clay, nanoparticle, and polymer derived engineered adsorbents: Machine learning insights into carbon chain length and removal mechanism.

Hassan Masud, Naidu Ravi, Qi Fangjie, Wang Bing, Wang Liang, Asadi Srinivasulu, Deb Amal Kanti, Du Jianhua, Liu Yanju

СтатьяСравнительное исследованиеПеревод в очереди

Аннотация

Per- and polyfluoroalkyl substances (PFAS) are a group of fluorinated chemicals that cause potential risk in PFAS-impacted soil and water. The adsorption efficiency of 30 PFAS mixtures using different adsorbents in environmentally relevant concentrations was investigated. Different meso/microporous designed adsorbents (n = 7) were used for PFAS adsorption and their interfacial interactions. The adsorbents were tested for their ability to remove PFAS mixtures, including perfluoroalkyl sulfonic acids (PFSAs, n = 7, C4-C10), perfluoroalkyl carboxylic acids (PFCAs, n = 11, C4-C14), fluorotelomer sulfonic acids (FTSs, n = 4), perfluoroalkane sulfonamido acetic acids (FASAAs, n = 3, C8), perfluoroalkane sulfonamides (FASAs, n = 3, C8) and perfluoroalkane sulfonamidoethanols (FASEs, n = 2, C8). The overall removal rate of 30 PFAS was recorded as 86.20-89.29 %, 87.63-90.33 %, and 67.07-93.61 % for microporous biochar/modified biochar, halloysite nanoclays, and mesoporous polymer composites-based adsorbents, respectively. The presence of sugarcane bagasse-derived biochar, iron nanoparticles, and β-cyclodextrin in the composite adsorbents enhances the sorption of PFAS. Higher adsorption efficiency was observed for long-chain PFCAs, PFSAs, FTSs, FASAAs, FASAs, and FASEs, whereas, complete removal of short-chain PFCAs, PFSAs, and FTSs is still challenging by using all the studied adsorbents. The carbon chain length and head groups of PFAS play a vital role in removing PFAS. The correlation coefficient (R2) values between removal rate and carbon chain length, for PFCAs (n = 11), and PFSAs (n = 7) were found as 0.73, and 0.31 respectively. Appropriate machine learning tools including efficient linear least squares, Gaussian process regression, and stepwise linear regression, were applied to fit experimental data and assess model accuracy.

Для цитирования: Hassan Masud, Naidu Ravi, Qi Fangjie, Wang Bing, Wang Liang, Asadi Srinivasulu, Deb Amal Kanti, Du Jianhua, Liu Yanju. Comparative immobilization of 30 PFAS mixtures onto biochar, clay, nanoparticle, and polymer derived engineered adsorbents: Machine learning insights into carbon chain length and removal mechanism.. Journal of hazardous materials. 2025. DOI: 10.1016/j.jhazmat.2025.137742.

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