2026-10-29T14:25:29Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/119952026-09-04T00:05:30Zcom_10259_4323com_10259_5086com_10259_2604col_10259_4330

Pérez Cortés, Alba Huerta Sainz, Sergio de la Santamaría Herrera, Sara Aparicio Martínez, Santiago Gutiérrez Vega, Alberto 2026-09-03T11:46:32Z 2026-09-03T11:46:32Z 2026-07 2211-7156 https://hdl.handle.net/10259/11995 10.1016/J.RECHEM.2026.103473 Per- and polyfluoroalkyl substances (PFAS) are persistent, toxic pollutants that pose serious challenges for water remediation due to their resistance to degradation and the limitations of existing treatment technologies. In this study, we explore a nature-inspired strategy for PFAS extraction from water using hydrophobic natural deep eutectic solvents (HNADES), applying a multiscale in silico approach. Through quantum-chemical methods rooted in Density Functional Theory (DFT), COnductor-like Screening MOdel for Real Solvents (COSMO-RS) thermodynamic modeling and classical molecular dynamics (MD) simulations, we demonstrate that the selected HNADES exhibits strong affinity for three representative PFAS (PFOA, PFOS and HFPO-DA). This affinity arises from robust hydrogen bonding between PFAS acidic proton of the terminal functional group and the carbonyl group of decanoic acid, supported by favorable van der Waals interactions. The extraction process is further stabilized by internal hydrogen bonding within the HNADES, preserving its structural integrity. These molecular-level interactions translate into high PFAS solubilities and activity coefficients approaching zero, effectively enabling the disruption of PFAS hydration shells and facilitating their migration across the (HNADES)-(PFAS + water) interface into the organic phase. A strong correlation was observed between molecular descriptors and mixture behavior, laying the groundwork for predictive models of extraction efficiency. Building on these insights, we conducted an extended virtual screening of 1746 PFAS against 2589 HNADES combinations, identifying promising candidates for selective, scalable and environmentally friendly remediation technologies, with the most hydrophobic HNADES—primarily those containing linalool, verbenone and cineole—solubilizing the widest range of PFAS. This work was funded by European Union (Horizon 2020 program, project WORLD: H2020-MSCA-RISE-2019-WORLD-GA-873005), and Agencia Estatal de Investigación (Project NADESforPFAS: PID2022-142405OB-I00). Author Alberto Gutiérrez received grant BG22/00089 funded by Spanish Ministerio de Universidades. We also acknowledge SCAYLE (Supercomputación Castilla y León, Spain) for providing supercomputing facilities. The statements made herein are solely the responsibility of the authors. application/pdf eng Elsevier Results in Chemistry. 2026, V.27, art. 103473 https://doi.org/10.1016/j.rechem.2026.103473 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Per and polyfluoroalkyl substances (PFAS) in water Hydrophobic natural deep eutectic solvents (HNADES) Density functional theory (DFT) COnductor like screening MOdel for real solvents (COSMO-RS) Classical molecular dynamics (MD) simulations Machine learning Química cuántica Quantum chemistry Multiscale mechanistic design of hydrophobic natural DES for PFAS extraction: from quantum chemistry to high-throughput screening info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Results in Chemistry 27 103473