数据驱动的纳滤未来:逃避线性

IF 4.9 Q1 ENGINEERING, CHEMICAL Journal of Membrane Science Letters Pub Date : 2023-05-01 DOI:10.1016/j.memlet.2023.100040
Gergo Ignacz, Aron K. Beke, Gyorgy Szekely
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引用次数: 3

摘要

与传统的膜分离方法(如蒸馏和色谱)相比,纳滤(NF)减少了废物的产生和能耗。尽管NF和可用于NF膜的材料具有多种优点,但该工艺的工业适用性需要改进。为了应对这些挑战,我们为膜材料和工艺发展的未来提出了四个重要支柱。这四大支柱是数字化、结构-性能分析、小型化和自动化。我们通过培养最有前途的当代技术来填补纳滤膜和工艺开发方面的空白,例如工艺分析技术的集成和并行人工纳滤渗透性测定(PANPA)或大型在线数据库的开发。此外,我们建议广泛使用密度泛函理论辅助的结构-性质关系方法来理解分子水平上的溶质传输过程。实现逆向设计将使研究人员和工业科学家能够利用优化的性能为特定应用开发定制膜。
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Data-driven future for nanofiltration: Escaping linearity

Compared with traditional membrane separation methods such as distillation and chromatography, nanofiltration (NF) affords decreased waste generation and energy consumption. Despite the multiple advantages of NF and materials available for NF membranes, the industrial applicability of this process requires improvement. To address these challenges, we propose four important pillars for the future of membrane materials and process development. These four pillars are digitalization, structure–property analysis, miniaturization, and automation. We fill gaps in the development of NF membranes and processes by fostering the most promising contemporary technologies, e.g., the integration of process analytical technologies and the development of a parallel artificial nanofiltration permeability assay (PANPA) or large online databases. Moreover, we propose the extensive use of density functional theory-aided structure–property relationship methods to understand solute transport process at a molecular level. Realizing an inverse design would allow researchers and industrial scientists to develop custom membranes for specific applications using optimized properties.

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