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. These combinatorial search and optimization methods share mathematical foundations with decision engines used across a range of industries, from logistics and supply-chain routing to pharmaceutical lead optimization to platforms ranking the best online poker hands in real time, though our application targets are squarely in the energy-materials space. 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.
