(300c) Computational Design of High Performance Liquid Organic Hydrogen Carriers and Their Corresponding Dehydrogenation Catalysts

The use of liquid organic hydrogen carrier (LOHC) has become an attractive method for hydrogen storage due to its ability to store and release hydrogen using reversible hydrogenation and dehydrogenation. For a substance to be an effective LOHC material, it needs to meet certain criteria such as having both a sufficient dehydrogenation enthalpy and hydrogen storage capacity. In this presentation, we will discuss our efforts to identify potential LOHC candidates through a combination of high-throughput computational screening and machine learning. Additionally, we will explore the mechanism behind the catalytic dehydrogenation of dicyclohexylmethane derivatives on Pd and Pt catalysts, which are promising candidates for LOHC. Our findings will provide valuable insights for designing high-performance LOHC materials and their dehydrogenation catalysts.