Rigorous Modeling and Industrial-Scalable Optimization of Hydroquinone–Catechol Vacuum Distillation: Aspen Plus-RSM Integration for Thermally Labile Systems
Abstract
High Resolution Image Download MS PowerPoint Slide To address the critical challenges of high energy consumption and low efficiency in conventional hydroquinone (HQ)–catechol (CAT) purification, this study presents a systematic computational investigation of vacuum distillation via Aspen Plus. Leveraging HQ and CAT’s thermal sensitivity and nonazeotropic behavior (40.0 °C boiling point difference at 101.325 kPa), an accurate thermodynamic framework is built using the NRTL (non-random two-liquid) activity coefficient model, with parameters calibrated via UNIFAC and the Aspen database. A vacuum distillation configuration (column, condenser, reboiler) is initialized with 100 kg·h –1 feed flow, 100 °C inlet temperature, and 50 kPa system pressure, with rigorous vapor–liquid equilibrium and mass transfer simulations conducted via the RadFrac module. Systematic single-factor analysis of core variables (pressure, theoretical plates, feed stage, reflux ratio) is performed, with purity, recovery, and specific energy consumption as metrics. Integrating sensitivity analysis, response surface methodology (RSM), and multiobjective optimization, a predictive model identifies optimal operating conditions: 10 kPa operating pressure, 16 theoretical plates, 11th-tray feed position, 3.143 mass reflux ratio, and an optimized distillate-to-feed (D/F) ratio of 0.092 (reduced from the industrial baseline D/F ratio of 0.121). These optimal conditions yield 99.2% hydroquinone (HQ) purity, 99% catechol (CAT) purity, 98.5% HQ recovery, and 97.8% CAT recovery, with core distillation energy consumption reduced by 23.7% (23.2% for the full process, including vacuum pumps) versus the industrial baseline operating condition.
Fields of Study & Subjects
Process Optimization and Integration
Phase Equilibria and Thermodynamics
Innovative Microfluidic and Catalytic Techniques Innovation
Publication details
- Journal / source
- ACS Omega
- Volume
- 11
- Issue
- 25
- Pages
- 38065–38084
- Publication date
- 19 June 2026
- Language
- EN