By combining materials chemistry and machine learning, researchers in the DM3 department have demonstrated that an algorithm can predict the optimal conditions for synthesizing high-quality metal-organic framework (MOF) membranes. Their method identifies key synthesis parameters with over 90% accuracy and could significantly accelerate the development of new membranes for pollution control, filtration, and separation applications.
Please consult the full reference:
Rational Design of High-Quality ZIF-8 Membranes: Machine Learning-Guided Optimization of ALD ZnO Conversion
Kevin Dedecker, Martin Drobek, Mikhael Bechelany & Anne Julbe
ACS Applied Materials & Interfaces, 2026, 18(7), 12199–12211 – DOI: 10.1021/acsami.5c24910
Artificial Intelligence for Optimizing MOF-Type Membranes
