Abstract

The replacement of n-hexane in vegetable oil extraction remains a significant challenge due to environmental and health concerns. This study integrates thermodynamic modeling and kinetic analysis to evaluate green solvents for soybean oil extraction. Solvent–triglyceride interactions were predicted using Conductor-like Screening Model for Real Solvents (COSMO-RS), employing σ-surfaces, σ-profiles, σ-potentials, activity coefficients at infinite dilution (γ∞), and relative solubility descriptors (xRS and wRS). Representative triglycerides were modeled using DFT-optimized structures. Based on these predictions and sustainability criteria, cyclopentyl methyl ether (CPME), 2-methyltetrahydrofuran (2-MeTHF), tert-butyl methyl ether (TBME), and ethyl acetate were experimentally evaluated against n-hexane using accelerated solvent extraction (ASE) at 100 °C. CPME and 2-MeTHF achieved the highest extraction yields, exceeding n-hexane, while TBME showed comparable performance and ethyl acetate underperformed. Kinetic analysis using the hot-ball diffusion model revealed a two-stage mechanism: an initial solvation-controlled stage followed by a diffusion-controlled regime. COSMO-RS predictions correlated strongly with early-stage extraction behavior, whereas diffusion coefficients highlighted the influence of mass transfer properties at later stages. The proposed COSMO-RS, experimental extraction, and kinetic modeling framework, validated here for soybean oil, offers a transferable and resource-efficient platform for designing sustainable solvent-based extraction processes across diverse oilseed and natural product matrices.

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