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

Date

2025-01-01

Author

Van Buggenhout, Simon
Ignacz, Gergo
Caspers, Scout
Dhondt, Robin
Lenaerts, Marie
Lenaerts, Nathalie
Hosseinabadi, Sareh Rezaei
Nulens, Ines
Koeckelberghs, Guy
Ren, Yi
Lively, Ryan P.
Rabiller-Baudry, Murielle
Lim, Ki Min
Ghazali, Nazlee
Coronas, Joaquin
Abel, Milan
Wessling, Matthias
Skiborowski, Mirko
Oxley, Adam
Han, Seok Ju
Livingston, Andrew
Yi, Zhuan
Gao, Congjie
Guan, Kecheng
Gonzales, Ralph Rolly
Matsuyama, Hideto
Bettahalli, Srivatsa NM.
McCutcheon, Jeffrey R.
Radmanesh, Farzaneh
Benes, Nieck E.
Tashvigh, Akbar Asadi
Fang, Qing
Zhang, Kaisong
Chen, Guining
Jin, Wanqin
Zhang, Yatao
Zhang, Chun-Xu
Liu, Mei-Ling
Sun, Shi-Peng
Buekenhoudt, Anita
Zhao, Chen
Bruggen, Bart Van der
Kim, Jeong F.
Condes, Lucas C.
Webb, Matthew T.
Galizia, Michele
Alhazmi, Banan
Upadhyaya, Lakshmeesha
Nunes, Suzana P.
Kim, Dae Woo
Schröter, Henrik
Kragl, Udo
Störtte, Sven
Vorholt, Andreas J.
Çulfaz Emecen, Pınar Zeynep
Pizzoccaro-Zilamy, Marie-Alix
Winnubst, Louis
Yushkin, Alexey
Volkov, Alexey
Chau, John
Sirkar, Kamalesh K.
Lu, Shao
Szekely, Gyorgy
Vankelecom, Ivo
Verbeke, Rhea

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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.

Subject Keywords

Big data, OMD4SRNF, Open membrane database, Organic solvent nanofiltration, OSN database, Solvent-resistant nanofiltration

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85205030856&origin=inward
https://hdl.handle.net/11511/111654

Collections

Department of Chemical Engineering, Article