The combination of machine learning and complex dynamic systems has the potential to lead to new breakthroughs in a variety of fields, ion and hydrogen diffusion in energy materials. For example, ML algorithms can be used to learn from historical data and make predictions about future behavior in complex dynamic systems. Machine learning can also be used to uncover hidden patterns and relationships within complex systems, and to identify the most important factors that contribute to the behavior of these systems.