David receives funding for the catLEGOS and HYSTRAM projects
The catLEGOS project will focus on the development of machine learning models for the prediction of quantum properties relevant to catalysis with transition metal complexes. The research is planned in three different blocks, including 1) the generation of datasets covering a significant portion of the metal-organic space, 2) the development of molecular representations based on first-principles calculations, and 3) the optimization of predictive models based on neural networks and Gaussian processes. David will be the PI of the project. The HYSTRAM project involves a large consortium of Universities and Industries for the development of a demonstration plant for the synthesis of ammonia from nitrogen and hydrogen, in which the latter will be produced with renewable energy sources. One of the key components of the plant is a hydrogen storage system based on metal-organic frameworks (MOFs). The research led by David will focus on the use of high-throughput virtual screening and machine learning methods for the discovery and design of new MOFs with a high affinity for hydrogen adsorption. The Hylleraas News site also announced the catLEGOS and HYSTRAM grants.
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