溶液扩散模型"我的死讯被夸大了"

IF 4.9 Q1 ENGINEERING, CHEMICAL Journal of Membrane Science Letters Pub Date : 2024-09-07 DOI:10.1016/j.memlet.2024.100084
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引用次数: 0

摘要

溶液扩散(SD)模型因其简单、透明和在工艺工程中的实用性,在膜科学的发展中起到了重要作用。然而,最近有人对 SD 的基本有效性提出了质疑。这些怀疑主要是基于分子动力学模拟与早期报告中出现的被认为是 SD 固有的几个特征之间的明显差异,即膜内压力和浓度分布的确切性质。在此,我们以复合膜为背景,重新探讨了 SD 的基本物理原理,不做任何先验假设,特别强调了聚合物热力学和由多孔基底支撑的负载膨胀膜力学的作用。分析提供了一个连贯的视角,将薄膜内的溶剂浓度分布和由此产生的流量-压力关系与聚合物的刚性,以及重要的薄膜支撑方式联系起来。分析表明,虽然通量通常会随进料压力非线性变化,并取决于薄膜支撑的几何形状,但对于刚性薄膜(在实际操作中最为常见),SD 预测的是线性行为,几乎与具体的几何形状和压力分布无关。展望未来,我们强调进一步完善 SD 模型的重要性和必要性,这需要从分子动力学、热力学和机械学的角度进行深入研究,同时保持其对工艺设计的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The solution-diffusion model: “Rumors of my death have been exaggerated”

The solution-diffusion (SD) model has been instrumental in the advancement of membrane science, due to its simplicity, transparency, and utility in process engineering. However, some doubts have recently been raised, concerning the fundamental validity of SD. These have largely been based on apparent discrepancies between molecular dynamics simulations and several features, deemed inherent to SD, that appeared in early reports — namely, the exact nature of the pressure and concentration distributions within the membrane. Herein, we re-visit the underlying physics of SD in the context of composite membranes, making no a-priori assumptions and, particularly, highlighting the role of polymer thermodynamics and the mechanics of a loaded, swollen film, supported by a porous substrate. The analysis provides a coherent view, linking the solvent concentration profile within the film and the resultant flux-pressure relations with the polymer rigidity and, importantly, the way in which the film is supported. It is shown that, although the flux may generally vary non-linearly with the feed pressure and depend on the film-support geometry, for rigid films – most common in real operations – SD predicts a linear behavior, virtually independent of specific geometry and pressure distribution. Moving forward, we stress the importance and need for further refinements of the SD model, driven by insight from molecular dynamics, thermodynamics and mechanics, while maintaining its applicability to process design.

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