JAVIER CARRASCO RODRIGUEZ
This group aims to develop the concepts, theories, and algorithms to aid the design process of advanced functional materials for batteries and supercapacitors through atomistic modeling, mesoscale modeling, and even macroscopic modeling.
Our contribution typically helps to understand and predict structural transformations, electrochemical behavior, and reactivity of a wide range of components (electrodes, solid and polymer electrolytes, thermochemical materials, heterogeneous catalysts, etc.) used in electrochemical and thermal energy storage systems. Applications include the screening of materials, the formation and coexistence of related phases, and transport of charge carriers across bulk and interfaces, with particular focus on Solid Electrolyte Interphase (SEI) formation and dynamics.
To tackle these challenging problems, our group combines its expertise in a range of complementary Theoretical Chemistry methods, including density functional theory and wave function, molecular mechanics and dynamics, and cheminformatics. By thoroughly combining different elements of such rich theoretical arsenal of modern chemistry, the group tries to link the microscopic behavior of matter to electronic and atomic structure with physics-based tools (mesoscale) and even macro-scale challenges in different chemistries such as lithium (Li), sodium (Na), and solid-state batteries. Machine Learning (ML) and Artificial Intelligence (AI) tools are also used in these studies to accelerate the discovering of new materials and speed up materials characterization and design.