Fast Water Desalination with a Graphene-MoS Nanoporous Heterostructure.

Energy-efficient water desalination is the key to tackle the challenges with drought and water scarcity that affect 1.2 billion people. The material and type of membrane in reverse osmosis water desalination are the key factors in their efficiency.

Machine Learning in Membrane Design: From Property Prediction to AI-Guided Optimization.

Porous membranes, either polymeric or two-dimensional materials, have been extensively studied because of their outstanding performance in many applications such as water filtration. Recently, inspired by the significant success of machine learning (ML) in many areas of scientific discovery, researchers have started to tackle the problem in the field of membrane design using data-driven ML tools. In this Mini Review, we summarize research efforts on three types of applications of machine learning in membrane design, including (1) membrane property prediction using ML, (2) gaining physical insight and drawing quantitative relationships between membrane properties and performance using explainable artificial intelligence, and (3) ML-guided design, optimization, or virtual screening of membranes.