Unveiling the Molecular Driving Forces of Pollutant Extraction by Hydrophobic Eutectic Solvents

TL;DR

This study develops a multiscale computational approach to understand and predict how hydrophobic eutectic solvents selectively extract pollutants like BPA, aiding sustainable solvent design.

Contribution

It introduces a combined molecular dynamics and quantum energy decomposition method to rationalize and predict solute partitioning in hydrophobic eutectic solvents.

Findings

Successfully predicts BPA migration and stabilization in HES.

Identifies hydrogen bonding, dispersion, and polarization as key to selectivity.

Provides a workflow for in-silico screening of HES formulations.

Abstract

Hydrophobic eutectic solvents (HES) are emerging as sustainable alternatives to conventional organic solvents for the extraction of molecular pollutants from water. Yet, their selectivity remains poorly understood, hindering the predictive design of eutectic solvents beyond empirical success. Here, we present a multiscale strategy to rationalize and predict solute partitioning in HES. Focusing on bisphenol A (BPA) in trioctylphosphine oxide (TOPO):menthol as a prototypical system, we combine monophasic and biphasic molecular dynamics with quantum energy decomposition of dominant solvation motifs. Our methodology captures the experimentally measured BPA spontaneous migration and thermodynamic stabilization in the HES phase but also identifies the microscopic origin of selectivity: cooperative hydrogen bonding couples to strong dispersion and polarization in the hydrophobic eutectic microenvironment. The robustness of our workflow paves the way for the predictive in-silico screening and design of HES formulations for green and sustainable applications.