Bridging Scales in Materials Modeling with Atomistic Simulations, Information Theory, and Generative Models

Learn how to bridge different scales in materials modeling through the integration of atomistic simulations, information theory, and generative models in this 46-minute conference talk. Explore advanced computational approaches for connecting atomic-level phenomena to continuum-scale behavior in electrochemical systems. Discover how information theory principles can be applied to extract meaningful patterns from atomistic data and understand how generative models can predict material properties across multiple length and time scales. Examine practical applications of these methodologies in electrochemical system modeling, including techniques for transferring information between different modeling scales and reducing computational complexity while maintaining accuracy. Gain insights into cutting-edge research methodologies that combine theoretical frameworks with computational tools to address complex materials science challenges, particularly in the context of electrochemical applications where multi-scale phenomena play crucial roles.