关键词: 三元多共沸混合物, 分离, 预浓缩, 多目标, 遗传算法

Abstract: In the industrial wastewater treatment sector of chemical engineering, the separation of multicomponent azeotropic mixtures remains a persistent challenge. This complexity arises from the intricate phase equilibrium behavior of these systems, which involves minimum/maximum boiling azeotropes and liquid-liquid phase separation. Pharmaceutical wastewater, often contains a ternary mixture of acetonitrile, n-propanol, and water. This mixture exhibits significant non-ideality and multiple azeotropic points, including binary azeotropes for acetonitrile-water, n-propanol-water, and acetonitrile-n-propanol pairs, as well as a ternary azeotrope. Thus, developing an energy-efficient separation process is essential. To address this issue, this study conducted a comprehensive investigation encompassing thermodynamic modeling, solvent screening, process design, and multi-objective optimization. A reliable thermodynamic framework was established using an activity coefficient model, and its validity was confirmed through experimental data verification, thereby ensuring the reliability of subsequent process simulations. Based on systematic analysis of vapor-liquid equilibrium diagrams, ethylene glycol was finally identified as the optimal extractant due to its optimal selectivity. Three distinct separation processes were developed: a conventional three-column distillation sequence, a four-column pre-concentration extractive distillation configuration, and an innovative three-column integrated pre-concentration extractive distillation system incorporating a thermally coupled column. Quantitative process evaluation was performed through multi-objective optimization using the improved nondominated sorting genetic algorithm (NSGA-II), with optimization targets comprising total annualized cost (TAC), CO2 emissions (E_(CO_2 )), and thermodynamic efficiency (η), subject to stringent purity constraints (≥99.9wt% for product components and ≥99.99wt% for extractant recycle). Optimization results showed the superior performance of the integrated three-column configuration, achieving 41.2% lower in TAC, 50.4% fewer CO2 emissions, and 102% higher thermodynamic efficiency than conventional approaches. This integrated preconcentration-extractive distillation process is established as an industrially viable, energy-efficient solution for acetonitrile-n-propanol-water separation that aligns with green chemistry principles.

Key words: ternary multi-azeotropic mixtures, separation, pre-concentration, multi-objective, genetic algorithm