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<p>Achieving ultra-high purity in crystallization processes requires precise thermodynamic data, particularly for multicomponent systems. It is common practice to use interaction parameters derived from binary systems; however, this method often falls short in accurately predicting phase behavior in more complex mixtures. This study examines the ternary mixture of acrylic acid, water, and acetic acid as a representative case. We conducted experimental solid–liquid equilibrium (SLE) measurements using the synthetic method, resulting in a dataset that enabled us to optimize the interaction parameters for thermodynamic models. We then compared predictions based on three sets of parameters: (i) those fitted to combined binary and ternary SLE data, (ii) those based exclusively on binary SLE data, and (iii) those derived from binary vapor–liquid equilibrium (VLE) data. Our findings indicate that incorporating ternary SLE data enhances the accuracy of model predictions, as evidenced by reduced deviations in both phase equilibrium calculations and mass balance outcomes. Moreover, a solute-specific regression strategy, which separates parameters depending on the composition range, significantly improves the accuracy of the calculation results. The strategy suggested in this study can be used to produce ultra-high purity products using the crystallization process.</p>

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Solid–Liquid Equilibrium of Acrylic Acid, Water, and Acetic Acid Ternary System for Separation Process Design

  • 期刊论文

  • 发表日期：

    2025年4月10日

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  • Tae Hyun Kim,
  • Yeon Ock Jang,
  • Seon Hwa Baek,
  • Si Yeon Jung,
  • Sung Jin Yoo,
  • Sung Kyu Lee,
  • Jeong Won Kang

摘要

Achieving ultra-high purity in crystallization processes requires precise thermodynamic data, particularly for multicomponent systems. It is common practice to use interaction parameters derived from binary systems; however, this method often falls short in accurately predicting phase behavior in more complex mixtures. This study examines the ternary mixture of acrylic acid, water, and acetic acid as a representative case. We conducted experimental solid–liquid equilibrium (SLE) measurements using the synthetic method, resulting in a dataset that enabled us to optimize the interaction parameters for thermodynamic models. We then compared predictions based on three sets of parameters: (i) those fitted to combined binary and ternary SLE data, (ii) those based exclusively on binary SLE data, and (iii) those derived from binary vapor–liquid equilibrium (VLE) data. Our findings indicate that incorporating ternary SLE data enhances the accuracy of model predictions, as evidenced by reduced deviations in both phase equilibrium calculations and mass balance outcomes. Moreover, a solute-specific regression strategy, which separates parameters depending on the composition range, significantly improves the accuracy of the calculation results. The strategy suggested in this study can be used to produce ultra-high purity products using the crystallization process.