Separation of a two binary-azeotrope acetonitrile-cyclohexane-toluene ternary mixture via continuous triple column extractive distillation with heat integration: design, simulation, and multi-objective genetic-algorithm (MOGA) optimization

ABSTRACTUsing a sustainable method for separating azeotropic mixtures, such as extractive distillation, is crucial for environmental and resource sustainability. Cyclohexane, acetonitrile, and toluene are essential solvents in different chemical processes. This ternary mixture has two binary azeotropes between cyclohexane-acetonitrile and acetonitrile-toluene at atmospheric pressures. Using residue curve maps and a uni-volatility line, n-butylbenzene was selected as a viable entrainer for extractive distillation, among other possibilities. Unlike conventional designs, the recycled entrainer was only sent to the first column in this simulation. The wasted energy from the recycled entrainer was used to supply reboilers duty through integration. A 3-D material balance was performed to understand the separation procedures better. High-purity acetonitrile, cyclohexane, and toluene will also be obtained from the first, second, and third columns. Finally, a multi-objective genetic algorithm with 14 key decision variables was utilized to reduce total annual cost (TAC) and CO2 emissions and improve thermodynamic efficiency as objective functions from economic, environmental, and energy efficiency perspectives. Optimized results reveal that a heat-integrated design reduces almost 25% TAC and 46% CO2 emissions compared to conventional extractive distillation and does not significantly affect thermodynamic efficiency. This research could be valuable for separating azeotrope systems from other ternary mixtures.KEYWORDS: Azeotropic separationternary systemextractive distillationsimulationmulti-objective genetic optimization Disclosure statementNo potential conflict of interest was reported by the author(s).NomenclatureTableDisplay TableSupplementary materialSupplemental data for this article can be accessed online at https://doi.org/10.1080/01496395.2023.2259606