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模拟微型模拟移动床染色学系统的额外列体积:引入相当的辐射流速分布

Juliane Diehm¹, Matthias Franzreb¹

¹Institute of Functional Interfaces, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany.

Journal of chromatography. A

|November 30, 2024

概括

先进的染色学建模准确地预测了微模拟移动床 (μSMB) 系统中的额外列体积 (ECV) 效应. 该研究表明,列性能,而不是ECV,主要决定了μSMB中的峰值形状,简化了模型选择.

科学领域:

染色体学染色体学是一种染色学.
化学工程是化学工程的重要组成部分.
计算流体动力学 (CFD) 是一种计算流体动力学.

背景情况:

额外列体积 (ECV) 建模对于小规模染色学系统至关重要.
传统的1D ECV模型 (DPFR,CSTR) 可能由于辐射不均性而缺乏准确性.
对于精确的ECV度分析,需要更高维度的模型.

研究的目的:

研究微模拟移动床 (μSMB) 染色学扩展的2D层流模型,通过结合分散效应 (例如,Dean) 使用等效辐射流速分布 (eqFRD).
评估高级ECV建模对孤立ECV段的预测准确性和整体μSMB系统性能的影响.

主要方法:

进行了3D CFD模拟,以分析ECV水力动力学.
调整了 2D 层状流量模型的辐射配置,以匹配 3D CFD 停留时间分布,从而创建了 eqFRD 模型.
对比eqFRD模型与传统ECV模型的预测准确度,用于孤立段和完整的μSMB系统.

主要成果:

eqFRD模型显著提高了预测准确度,孤立的ECV段从90%提高到97%.
在完整的μSMB系统中,当精确预测ECV保留时间时,ECV模型选择对结果的影响最小.
该研究表明,在测试的μSMB系统中,对峰值形状的柱子效应比ECV效应更为主导.

结论:

相当的辐射流速分布 (eqFRD) 模型提高了对孤立段的ECV预测准确度.
对于μSMB系统,如果保留时间被准确捕获,更简单的ECV模型可能就足够了,因为柱子效应占主导地位.
未来的研究应该考虑列-ECV过渡和探测器效应,以提高整体模型的准确性.

关键词:

染色学建模的染色学建模死亡体积死亡体积额外的列体积额外的列体积.多列色谱是多列色谱的一种方法.小规模染色体学小规模染色体学

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