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

Van Buggenhout S., Ignacz G., Caspers S., Dhondt R., Lenaerts M., Lenaerts N., ...Daha Fazla

Journal of Membrane Science, cilt.713, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 713
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1016/j.memsci.2024.123356
  • Dergi Adı: Journal of Membrane Science
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aqualine, Biotechnology Research Abstracts, Chemical Abstracts Core, Chimica, Compendex, Food Science & Technology Abstracts, INSPEC, Metadex, Pollution Abstracts, DIALNET
  • Anahtar Kelimeler: Big data, OMD4SRNF, Open membrane database, Organic solvent nanofiltration, OSN database, Solvent-resistant nanofiltration
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.