There is an urgent need to develop energy-efficient separations through predictive methodologies that will fast-track the industrial implementation. The performance prediction of solvent-resistant membranes has been a daunting and challenging task, due to the complexity of the multicomponent system comprising of solvents, solutes, and membranes with a high number of possible molecular interactions. Data mining is performed to build a database, which is used to explore artificial intelligence-based predictive models for membrane performance.
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