The physicochemical properties of the materials that compose Earth and planetary interiors—across a wide range of pressure, temperature, composition, and redox conditions—are fundamental to understanding planetary structure, dynamics, and evolution. While experimental studies provide essential constraints, computational approaches have become indispensable for probing regimes that are difficult or inaccessible to experiments and for providing atomistic to planetary-scale insight. This session highlights recent advances in computational planetary materials research, including first-principles calculations, multi-scale modeling, and high-throughput simulations. We particularly encourage contributions that leverage emerging data-driven and machine learning approaches, such as machine-learned interatomic potentials, AI-accelerated simulations, surrogate and reduced-order modeling, uncertainty quantification, and autonomous or high-throughput discovery frameworks. We welcome contributions from mineral physics and allied disciplines—including petrology, geochemistry, geophysics, and planetary science—that demonstrate how computational and data-driven methods are advancing our understanding of planetary materials and their role in geophysical processes and planetary evolution.

• DI - Study of the Earth's Deep Interior