Théorique, numérique
Gas hydrates, particularly hydrogen hydrates, are emerging as significant in sustainable energy storage. The behavior of hydrogen within certain ice structures remains an enigma. Research indicates hydrogen undergoes both classical and quantum rotations in these structures, and specific conditions prompt nematic ordering. This internship aims to delve deeper into these quantum rotations, connect the quantum reasons behind nematic ordering with experimental findings, and employ machine learning to enhance hydrate system simulations. Understanding this is crucial for optimizing gas hydrate applications in energy storage.