Computational discovery of hydrogen storage materials

IMDEA Materials has know-how and experience in developing computational high-throughput screening workflows for discovery of hydrogen storage materials. Our focus has been mostly directed towards advanced porous materials such as metal organic frameworks and related materials (Fig. 1). Our customizable tools allow to execute material structure prediction from a library of molecular building blocks, performing hydrogen adsorption-desorption simulations and material screening to identify structure with high hydrogen working capacity. Finally, we have the ability to tune these tools to specific material families, application specifics as well as incorporate various machine learning approach to both accelerate the discovery workflows as well as facilitate obtaining various engineering characteristics.

Fig. 1 A representative of information coming from high-throughput screening: H2 adsorption loadings for a set of 500 metal organic framework materials, with the top structures identified together with the structural feature-performance relationships identified, i.e. in this case H2 adsorption at 100 bar correlates strongly with the pore volume.

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