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Process Optimization of Para-xylene Crystallization Separation Process via Morphology Approach, Multi-dimensional Population Balance Equation, and Equation-Oriented Models.

Zhenxing CaiHui ZhaoPingxin LiXiaobo ChenChaohe Yang
Published in: ACS omega (2023)
An activity coefficient-based model was proposed to predict pertinent saturated concentrations in organic solid-liquid equilibrium, and the binary parameters of xylene mixtures were experimentally obtained. Also, a novel monocular 3D reconstruction technique was developed to measure crystal size and applied to derive the kinetics of nucleation and growth of para-xylene crystals. Subsequently, a multi-dimensional population balance equation was used to predict the particle size distribution in the crystallizer and an algorithm was designed to simulate and optimize the economic benefit of the crystallization separation process. Consequently, it became possible to predict the optimal coolant flowrate and inlet temperature, as well as the feed flowrate for a crystallization process with given operating conditions and device parameters.
Keyphrases
  • ionic liquid
  • machine learning
  • liquid chromatography
  • computed tomography
  • molecular dynamics
  • room temperature