TY - JOUR
T1 - Open and FAIR data for nanofiltration in organic media
T2 - A unified approach
AU - Van Buggenhout, Simon
AU - Ignacz, Gergo
AU - Caspers, Scout
AU - Dhondt, Robin
AU - Lenaerts, Marie
AU - Lenaerts, Nathalie
AU - Hosseinabadi, Sareh Rezaei
AU - Nulens, Ines
AU - Koeckelberghs, Guy
AU - Ren, Yi
AU - Lively, Ryan P.
AU - Rabiller-Baudry, Murielle
AU - Lim, Ki Min
AU - Ghazali, Nazlee
AU - Coronas, Joaquin
AU - Abel, Milan
AU - Wessling, Matthias
AU - Skiborowski, Mirko
AU - Oxley, Adam
AU - Han, Seok Ju
AU - Livingston, Andrew
AU - Yi, Zhuan
AU - Gao, Congjie
AU - Guan, Kecheng
AU - Gonzales, Ralph Rolly
AU - Matsuyama, Hideto
AU - Bettahalli, Srivatsa NM
AU - McCutcheon, Jeffrey R.
AU - Radmanesh, Farzaneh
AU - Benes, Nieck E.
AU - Tashvigh, Akbar Asadi
AU - Fang, Qing
AU - Zhang, Kaisong
AU - Chen, Guining
AU - Jin, Wanqin
AU - Zhang, Yatao
AU - Zhang, Chun Xu
AU - Liu, Mei Ling
AU - Sun, Shi Peng
AU - Buekenhoudt, Anita
AU - Zhao, Chen
AU - Bruggen, Bart Van der
AU - Kim, Jeong F.
AU - Condes, Lucas C.
AU - Webb, Matthew T.
AU - Alhazmi, Banan
AU - Upadhyaya, Lakshmeesha
AU - Nunes, Suzana P.
AU - Volkov, Alexey
AU - Szekely, Gyorgy
N1 - Publisher Copyright:
© 2024
PY - 2025/1
Y1 - 2025/1
N2 - 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.
AB - 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.
KW - Big data
KW - OMD4SRNF
KW - Open membrane database
KW - Organic solvent nanofiltration
KW - OSN database
KW - Solvent-resistant nanofiltration
UR - http://www.scopus.com/inward/record.url?scp=85205030856&partnerID=8YFLogxK
U2 - 10.1016/j.memsci.2024.123356
DO - 10.1016/j.memsci.2024.123356
M3 - Article
AN - SCOPUS:85205030856
SN - 0376-7388
VL - 713
JO - Journal of Membrane Science
JF - Journal of Membrane Science
M1 - 123356
ER -