Computationally guided design of novel metal-organic frameworks for enhanced protonconductivity and photocatalytic water splitting

This project seeks to establish practical design rules for synthesizing MOFs with enhanced performance in hydrogen-related processes, specifically proton conductivity and photocatalytic water splitting. Building on recent discoveries at the University of Manchester, including MOFs that exceed the proton conductivity of benchmark materials and demonstrate efficient hydrogen evolution under visible light, the research will combine molecular simulation, ab initio modeling, and experimental synthesis and characterization. The team will investigate key molecular phenomena such as water adsorption, proton transport, and the effects of structural flexibility and sulfonation on conductivity and catalytic activity. Fundamental questions, such as how framework topology, hydration states, and functional group distribution influence transport behaviour, will be addressed through a series of work packages focused on modeling water cluster networks, tuning chemical functionality, and simulating deformation-driven transport effects. These insights will be translated into computational screening and machine learning-guided discovery of new MOF candidates, followed by targeted synthesis and performance testing. The outcomes of this research will push the boundaries of materials design for hydrogen technologies and provide a deeper understanding of the structure–function relationships that govern MOF behavior under a broad range conditions. The project brings together a multidisciplinary, international team from the University of Manchester (UK), Rutgers University (USA), Oak Ridge National Laboratory (USA), and IBM (Brazil).