DFT-assisted machine learning for polyester membrane design in textile wastewater recovery applications

Water Research, Journal Year: 2025, Volume and Issue: 279, P. 123438 - 123438

Published: March 5, 2025

Language: Английский

Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 16, 2024

Polymeric membranes have been widely used for liquid and gas separation in various industrial applications over the past few decades because of their exceptional versatility high tunability. Traditional trial-and-error methods material synthesis are inadequate to meet growing demands high-performance membranes. Machine learning (ML) has demonstrated huge potential accelerate design discovery membrane materials. In this review, we cover strengths weaknesses traditional methods, followed by a discussion on emergence ML developing advanced polymeric We describe methodologies data collection, preparation, commonly models, explainable artificial intelligence (XAI) tools implemented research. Furthermore, explain experimental computational validation steps verify results provided these models. Subsequently, showcase successful case studies emphasize inverse methodology within ML-driven structured framework. Finally, conclude highlighting recent progress, challenges, future research directions advance next generation With aim provide comprehensive guideline researchers, scientists, engineers assisting implementation process.

Language: Английский

Rejection of an emerging small neutral organic micropollutant by in-situ nanofiltration membrane modification for water treatment

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 125052 - 125052

Published: March 26, 2025

Language: Английский