Open and FAIR data for nanofiltration in organic media: A unified approach

IF 8.4 1区工程技术 Q1 ENGINEERING, CHEMICAL

Journal of Membrane Science Pub Date : 2024-09-21 DOI:10.1016/j.memsci.2024.123356

Simon Van Buggenhout , Gergo Ignacz , Scout Caspers , Robin Dhondt , Marie Lenaerts , Nathalie Lenaerts , Sareh Rezaei Hosseinabadi , Ines Nulens , Guy Koeckelberghs , Yi Ren , Ryan P. Lively , Murielle Rabiller-Baudry , Ki Min Lim , Nazlee Ghazali , Joaquin Coronas , Milan Abel , Matthias Wessling , Mirko Skiborowski , Adam Oxley , Seok Ju Han , Rhea Verbeke

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Abstract

Organic solvent nanofiltration (OSN), also called solvent-resistant nanofiltration (SRNF), has emerged as a promising technology for the removal of impurities, recovery of solutes, and the regeneration of solvents in various industries, such as the pharmaceutical and the (petro)chemical industries. Despite the widespread use of OSN/SRNF, the presence of scattered, non-standardized data, and the absence of openly accessible data pose critical challenges to the development of new membrane materials and processes, their comparison to the state-of-the-art materials, and their fundamental understanding. To overcome these hurdles, data from peer-reviewed research articles and commercial datasheets were curated via a standardized procedure to obtain an extensive dataset on the membrane materials, synthesis parameters, operational conditions, physicochemical properties, and performance of OSN/SRNF membranes. Thanks to a truly impressive joint effort of the OSN/SRNF community, the dataset contains, as per April 2024, 5006 unique membrane filtrations from 294 publications for 42 solvents under several process parameters. This findable, accessible, interoperable, reproducible, and open (FAIR/O) dataset is available on both the OSN Database and the newly inaugurated Open Membrane Database for SRNF (OMD4SRNF). These databases provide multiple visualization and data exploration tools. Here, the standardized procedure applied to curate the data and the functionality of the databases are outlined, as well as the online user interface to deposit new data by external users on the OMD4SRNF. This community-led project has been supported by all the co-authors of this work. Most importantly, they additionally agreed to systematically deposit their future peer-reviewed data on OSN/SRNF into the databases. We thereby pave the road for FAIR/O data in the field of OSN/SRNF to increase transparency, enable more accurate data analysis, and foster collaboration and innovation.

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有机介质纳滤的开放和 FAIR 数据：统一方法

有机溶剂纳滤（OSN），又称耐溶剂纳滤（SRNF），已成为制药和（石油）化学工业等各种工业中去除杂质、回收溶质和溶剂再生的一项很有前途的技术。尽管 OSN/SRNF 的使用非常广泛，但由于数据分散、非标准化，以及缺乏可公开获取的数据，对开发新的膜材料和工艺、将其与最先进的材料进行比较以及对其进行基本了解构成了严峻的挑战。为了克服这些障碍，我们通过标准化程序对同行评审的研究文章和商业数据表中的数据进行了整理，从而获得了关于膜材料、合成参数、操作条件、物理化学特性和 OSN/SRNF 膜性能的大量数据集。在 OSN/SRNF 社区的共同努力下，截至 2024 年 4 月，该数据集包含了来自 294 份出版物的 5006 个独特的膜过滤数据，涉及 42 种溶剂和多个工艺参数。这个可查找、可访问、可互操作、可重现和开放（FAIR/O）的数据集可在 OSN 数据库和新启用的 SRNF 开放式膜数据库（OMD4SRNF）中找到。这些数据库提供多种可视化和数据探索工具。在此，我们将简要介绍整理数据的标准化程序和数据库的功能，以及外部用户在 OMD4SRNF 上存放新数据的在线用户界面。这个由社区主导的项目得到了这项工作所有共同作者的支持。最重要的是，他们还同意今后将其在 OSN/SRNF 上经过同行评审的数据系统地存入数据库。因此，我们为 OSN/SRNF 领域的 FAIR/O 数据铺平了道路，以提高透明度，实现更准确的数据分析，促进合作与创新。

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来源期刊

Journal of Membrane Science 工程技术-高分子科学

CiteScore

17.10

自引率

17.90%

发文量

1031

审稿时长

2.5 months

期刊介绍： The Journal of Membrane Science is a publication that focuses on membrane systems and is aimed at academic and industrial chemists, chemical engineers, materials scientists, and membranologists. It publishes original research and reviews on various aspects of membrane transport, membrane formation/structure, fouling, module/process design, and processes/applications. The journal primarily focuses on the structure, function, and performance of non-biological membranes but also includes papers that relate to biological membranes. The Journal of Membrane Science publishes Full Text Papers, State-of-the-Art Reviews, Letters to the Editor, and Perspectives.