Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/42632
Title: Organic Solvent Nanofiltration and Data-Driven Approaches
Authors: PICCARD, Pieter-Jan 
Borges, Pedro
CLEUREN, Bart 
Buekenhoudt, Anita
HOOYBERGHS, Jef 
Issue Date: 2023
Publisher: 
Source: Data Science Hub Lustrum Symposium, VITO, Mol, Belgium, 10th of November, 2023
Abstract: Membranes are powerful, versatile separation tools, offering an energy lean alternative for traditional thermal separation methods. However, due to the complexity of this membrane process, influenced by all mutual solute-solvent-membrane interactions and properties, the transport mechanism is not well understood. This leads to a slow, trial-and-error based development process. To speed up the development process, and to try and understand the separation mechanism, we resort to data science.
Keywords: organic solvent nanofiltration;data science;mathematical modeling;machine learning;data standardization
Document URI: http://hdl.handle.net/1942/42632
Category: C2
Type: Conference Material
Appears in Collections:Research publications

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