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Session Proposal: Exploring Planetary Materials through Computational Simulations and Machine Learning (AGU25)

MR003
Exploring Planetary Materials through Computational Simulations and Machine Learning

Session ID#: 247804

Session Description:
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.
Co-Sponsor(s):
  • DI - Study of the Earth's Deep Interior
Index Terms:

0545 Modeling [COMPUTATIONAL GEOPHYSICS]
0555 Neural networks, fuzzy logic, machine learning [COMPUTATIONAL GEOPHYSICS]
3699 General or miscellaneous [MINERALOGY AND PETROLOGY]
3999 General or miscellaneous [MINERAL PHYSICS]
Primary Convener:  Jie Deng, Princeton University, Department of Geosciences, Princeton, United States
Conveners:  Bijaya B Karki, Louisiana State University, School of Electrical Engineering and Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States and Mainak Mookherjee, Florida State University, Earth, Ocean and Atmospheric Science, Tallahassee, FL, United States
 
Vacancies in Mg2SiO4 body-centred-tetragonal phase at 1TPa ultrahigh pressure : a DFT study (1863612)
Philippe Carrez1, Caroline Traisnel1, Taku Tsuchiya2 and Patrick Cordier3, (1)University of Lille, Villeneuve d'Ascq, France, (2)Geodynamics Research Center, Matsuyama, Japan, (3)Université de Lille, UMET, Villeneuve d'Ascq, France
 
Ab initio electrical conductivity of Fe-bearing post-perovskite (1887841)
Yihang Peng1, Yupei Zhang2, Xifan Wu2, Shuai Zhang3, Chenxing Luo1, Donghao Zheng1 and Jie Deng4, (1)Princeton University, Department of Geosciences, Princeton, NJ, United States, (2)Temple University, Department of Physics, Philadelphia, United States, (3)University of Rochester, Laboratory of Laser Energetics, Rochester, United States, (4)Princeton University, Department of Geosciences, Princeton, United States
 
Insights into mobility of magma in the Solid Earth from First Principles Molecular Dynamics Simulations (1896693)
Mainak Mookherjee, Florida State University, Earth, Ocean, and Atmospheric Science, Tallahassee, FL, United States, Aaron Wolfgang Ashley, Université Clermont Auvergne, Clermont-Ferrand, France, Suraj K Bajgain, Louisiana State University and Agricultural & Mechanical College, Baton Rouge, United States and awashley@fsu.edu
 
DFT study on the transport properties of B2 phase Fe-Si-H at Earth’s core-mantle boundary (1902959)
Yuan Yin1,2, Cong Liu3, Shuangmeng Zhai2, Yun Liu2 and Yingwei Fei1, (1)Carnegie Science, Earth and Planets Laboratory, Washington DC, United States, (2)Chinese Academy of Sciences, Institute of Geochemistry, Guiyang, China, (3)Carnegie Institution for Science, Earth and Planets Laboratory, Washington, United States
 
Machine Learning is a Tool that Accurately Breaks the Time and Distance Barriers (Invited) (1910995)
Ronald E Cohen, Xin Deng and Cong Liu, Carnegie Institution for Science, Earth and Planets Laboratory, Washington, United States
 
Thermoelasticity of Geologically Relevant Silica Phases (SiO2) Using Machine Learning Potentials (1930326)
Jessica Santos Rego1,2, Chenxing Luo3, Caetano Rodrigues Miranda2 and Renata Wentzcovitch4, (1)Columbia University of New York, Department of Earth and Environmental Sciences, Palisades, United States, (2)University of São Paulo, Department of Materials Physics and Mechanics, São Paulo, Brazil, (3)Princeton University, Department of Geosciences, Princeton, NJ, United States, (4)Columbia University in the City of New York, New York, United States
 
Behavior of hydrogen and nitrogen in molten bulk Earth system from neural network potentials simulations (1931177)
Bijaya B Karki, Louisiana State University, School of Electrical Engineering and Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States and Abin Shakya, Louisiana State University, Division of Computer Science and Engineering, Baton Rouge, LA, United States
 
Phase transitions, stability, and thermodynamic properties of Mg0.5Fe0.5O under super-Earth conditions (1938518)
Chenxing Luo1, Yihang Peng1, Renata Wentzcovitch2 and Jie Deng3, (1)Princeton University, Department of Geosciences, Princeton, NJ, United States, (2)Columbia University in the City of New York, New York, United States, (3)Princeton University, Department of Geosciences, Princeton, United States
 
Ab initio calculations of equilibrium chromium isotope fractionation during magma evolution (1953718)
Yajie Zhao, University of Science and Technology of China, School of Earth and Space Sciences, Hefei, China
 
Diamond Formation from CH-Hydrocarbons in Ice Giant Mantle Conditions Elucidated from Large-Scale Simulations (1958741)
Maitrayee Ghosh, Stanford University, Stanford, CA, United States, Shuai Zhang, University of Rochester, Laboratory of Laser Energetics, Rochester, United States, Suxing Hu, University of Rochester, Laboratory for Laser Energetics, Rochester, United States, Arianna E Gleason, SLAC, Menlo Park, CA, United States, Armin Bergermann, SLAC National Accelerator Laboratory, Menlo Park, United States and Siegfried Glenzer, SLAC National Accelerator Laboratory, High Energy Density Sciences, Menlo Park, United States
 
Scalable Machine Learning Approach for Phase Segmentation in Molecular Dynamics Simulations of Complex Melts (1960165)
Abin Shakya, Louisiana State University, Division of Computer Science and Engineering, Baton Rouge, LA, United States and Bijaya B Karki, Louisiana State University, School of Electrical Engineering and Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States
 
Thermodynamic Consistent Neural Networks for Constitutive Modeling (1961382)
Kangan Li, Pennsylvania State University Main Campus, Energy and Mineral Engineering, University Park, PA, United States, Tushar Mittal, Penn State, Earth and Planetary Science, University Park, United States, Seth Saltiel, Cornell University, Earth and Atmospheric Sciences, Ithaca, United States and Benjamin K Holtzman, Lamont Doherty Earth Observatory, Columbia Univ., Palisades, NY, United States
 
Hydrogen Superionicity in Dilute Ammonium Hydrides at Ice Giant Interior Conditions (1969169)
Kyla de Villa1, Eva Zurek2, Xiaoyu Wang3 and Burkhard Militzer1, (1)University of California Berkeley, Earth and Planetary Science, Berkeley, CA, United States, (2)University at Buffalo, Buffalo, United States, (3)University at Buffalo, Chemistry, Buffalo, United States
 
Fe–S Phase Diagram at High Pressures: Implications for Core Crystallization in Earth, Mars, and Beyond (1973915)
Felipe Gonzalez Cataldo, University of California Berkeley, Department of Earth and Planetary Science, Berkeley, CA, United States and Burkhard Militzer, University of California Berkeley, Earth and Planetary Science, Berkeley, CA, United States; University of California Berkeley, Department of Astronomy, Berkeley, United States
 
Ferroelastic hysteresis, shear modulus softening, and the tetragonal↔cubic transition in davemaoite (1981422)
Tianqi Wan, Columbia University, Lamont-Doherty Earth Observatory, New York, United States, Chenxing Luo, Princeton University, Department of Geosciences, Princeton, NJ, United States, Zhen Zhang, Iowa State University, Department of Physics, Ames, United States, Yang Sun, Xiamen University, Department of Physics, Xiamen, China and Renata Wentzcovitch, Columbia University in the City of New York, New York, United States
 
Machine Learning Potential for Serpentines (1990893)
Hongjin Wang, Columbia University in the City of New York, Department of Applied Physics and Applied Mathematics, New York, United States, Chenxing Luo, Princeton University, Department of Geosciences, Princeton, NJ, United States and Renata Wentzcovitch, Columbia University in the City of New York, New York, United States
 
Elasticity and Stability of MgO in Giant Planetary Interiors (1994305)
David James, University of California Los Angeles, Los Angeles, CA, United States and Lars P Stixrude, University of California Los Angeles, Department of Earth, Planetary and Space Sciences, Los Angeles, CA, United States
 
The Fe-Si-O system at Terapascal pressures (2000804)
Renata Wentzcovitch1, Yang Sun2, Nan Huang3, Zepeng Wu4, Feng Zhang5 and Shunqing Wu4, (1)Lamont -Doherty Earth Observatory, Palisades, United States, (2)Xiamen University, Department of Physics, Xiamen, China, (3)Xiamen University, Physics, Xiamen, China, (4)Xiamen University, Xiamen, China, (5)Ames Laboratory, US DOE and Iowa State University, Department of Physics, Ames, IA, United States