Primary Convener:
Jie Deng, Princeton University

Convener:
Bijaya Karki, Louisiana State University
Mainak Mookherjee, Florida State University

Chair:
Jie Deng, Princeton University
Mainak Mookherjee, Florida State University

The physicochemical properties of materials comprising Earth and other planets under varying intensive thermodynamic properties such as pressure, temperature, and redox conditions are fundamental to our understanding of the planetary interiors. Valuable insights are obtained from experimental constraints on such properties of Earth and planetary materials. Computational methods have also become indispensable in this pursuit, providing insight into material behavior across regimes that are often inaccessible or/are complementary to experimental constraints. This session aims to highlight the latest advances in computational planetary materials research, spanning first-principles calculations, multi-scale modeling, and high-throughput simulations. We especially encourage contributions that integrate machine learning techniques—such as the development of machine-learned interatomic potentials, AI-accelerated simulations, and data-driven discovery pipelines—to explore structure, thermodynamic and thermoelastic properties, transport behavior, diffusion, defects, element partitioning, isotope fractionation, and equilibria. We welcome contributions to mineral physics and allied disciplines that elucidate the dynamics and evolution of the planets.

Index Terms
0545 Modeling
0555 Neural networks, fuzzy logic, machine learning
3999 General or miscellaneous
3699 General or miscellaneous

Suggested Itineraries:
Machine Learning and AI

Cross-Listed:
DI - Study of the Earth´s Deep Interior

Neighborhoods:
2. Earth Interior