Abstract To address the energy‐intensive challenge of large‐scale acetonitrile (ACN)‐water separation in industry, this work presents a systematic framework integrating thermodynamic model evaluation, solvent screening‐validation, and hybrid extraction‐distillation process design. The COSMO‐RS model with different parameterizations is first evaluated for its thermodynamic prediction performance for ACN‐related systems, with the better‐performing option implemented into the subsequent solvent screening scheme that comprises (a) COSMO‐RS based thermodynamic screening, (b) deep learning and empirical rule based physicochemical screening, and (c) PubChem‐based environmental, health, and safety (EHS) screening. The top four solvents are subjected to liquid–liquid equilibrium (LLE) experiments to validate their practical extraction performance, among which the most promising candidate is employed in an extraction‐distillation process, reducing the solvent circulation by 44.8% and energy consumption by 32.5% compared with the ethylene glycol‐based reference process. This work provides an energy‐efficient, eco‐friendly separation strategy for the ACN–water mixture, offering a scalable framework for other azeotropic systems.
Chai et al. (Tue,) studied this question.