Novel Process Development of Hybrid Reactive–Extractive Distillation System for the Separation of a Cyclohexane/Isopropanol/Water Mixture with Different Feed Compositions

Abstract

A cyclohexane (CY)/isopropanol (IPA)/water mixture has complex thermodynamic properties with three binary azeotropes and one ternary azeotrope. A configuration of doublecolumn reactive−extractive distillation (DCRED) is suitable to be used for the separation of this mixture with ethylene oxide (EO) as the dehydrating agent. Taking advantage of a large liquid−liquid envelope in the ternary map of this mixture, two novel process configurations are proposed in this study to separate the mixture with the percentage of water to total feed ranging from 10 to 90 mol %. A process configuration that includes a pretreatment section followed by a DCRED section (P-DCRED) was proven to be efficient in separating the mixture with the percentage of water ranging from 50 to 90 mol %, while only the DCRED process configuration showed its superiority when dealing with the mixture with the percentage of water ranging from 10 to 40 mol %. Compared to the traditional extractive distillation (ED) and another process of ED coupled with pervaporation (PV) in the recent literature, the novel processes proposed in this study can save a total annual cost (TAC) of 20 to 80%.

Editorial for the Festschrift Honoring the Legacy of Babatunde A. Ogunnaike (1956–2022)

“…4 Wu et al present novel process developments for hybrid reactive-extractive distillation. 5 Stengel et al discuss an interactive tool for designing solvent recovery systems. 6 Correlations between interfacial area and volumetric mass transfer in bubble columns are presented by Hazare et al 7 Special Issue: In Honor of Babatunde A. Ogunnaike Process control and operations are represented by the works of Santander et al, who discuss an integrated stochastic framework for simultaneous short-term scheduling and control for batch processes, 8 Lovelett et al, who review the control of processes with input multiplicity, 9 and Pinnamaraju et al, who employ sparse optimization to construct soft sensors from irregularly and infrequently sampled data.…”

“…Luo et al cover the design of multifeedstock/multiproduct processes using neural network surrogate flexibility constraints . Wu et al present novel process developments for hybrid reactive-extractive distillation . Stengel et al discuss an interactive tool for designing solvent recovery systems .…”