MR007
Computational Advances and Applications in Mineral Physics

Session ID#: 76305

Session Description:
Knowledge of physical and chemical properties of component materials over wide pressure-temperature (P-T) conditions relevant to the Earth and planetary interiors is crucial to advance our understanding of their structural and dynamical state. Over the last couple of decades, computational techniques have been proven to be very reliable in unraveling the materials properties at those conditions, even in the experimentally inaccessible P-T regions (complementing experiments). The aim of this session is to bring together the most recent computational advances (first principles to multi-scale modeling, application of Machine Learning techniques and data visualization/analysis) covering elasticity, defects, diffusion and deformation, silicate glasses and melts, multi-component materials, etc. We also welcome abstracts from relevant experimental studies.
Index Terms:

3619 Magma genesis and partial melting [MINERALOGY AND PETROLOGY]
3621 Mantle processes [MINERALOGY AND PETROLOGY]
3904 Defects [MINERAL PHYSICS]
3924 High-pressure behavior [MINERAL PHYSICS]


Primary Convener:  Dipta B Ghosh, Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States
Convener:  Bijaya B Karki, Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States
Primary Liaison:  Bijaya B Karki, Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States
 
Accounting for elastic anisotropy in crystal plasticity within the context of olivine dynamic recrystallization using a level-set framework (487214)
Jean Furstoss1, Carole Petit2, Daniel Pino Muñoz3, Clément Ganino4 and Marc Bernacki3, (1)Geoazur, Valbonne, France, (2)Université Côte d’Azur, CNRS, OCA, IRD, Géoazur, Sophia Antipolis, France, (3)Mines ParisTech, Paris, France, (4)Géoazur - Université Nice Sophia Antipolis, Valbonne, France
 
Some remarks on computational mineral physics from a non-computational mineral physicist/geophysicist (Invited) (487846)
Shun-ichiro Karato, Yale University, Geology and Geophysics, New Haven, CT, United States
 
Inferring Equations of State of the Lower Mantle Minerals Using Artificial Neural Networks (ANNs) (487956)
Ashim Rijal1, Laura J Cobden1, Jeannot Trampert1, Jennifer M Jackson2 and Andrew P Valentine3, (1)Utrecht University, Utrecht, Netherlands, (2)Caltech, Pasadena, CA, United States, (3)Australian National University, Research School of Earth Sciences, Canberra, ACT, Australia
 
Parallel Coordinates-based Visual Analytics for Materials Property: Application to Silicate Melt Viscosity (517657)
Bijaya B Karki1, Diwas Bhattarai2, Jian Zhang2 and Dipta B Ghosh1, (1)Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States, (2)Louisiana State University, Baton Rouge, LA, United States
 
Simulation and Visualization of Mixed-incorporation of Carbon and Hydrogen in Silicate Melts (524271)
Dipendra Banjara1, Dipta B Ghosh2 and Bijaya B Karki2, (1)Louisiana State University, Baton Rouge, LA, United States, (2)Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States
 
Ab Initio Crystal Structure Prediction with Symmetry and Geometric Constraints (Invited) (525894)
Burkhard Militzer, University of California Berkeley, Department of Earth and Planetary Science, Berkeley, CA, United States, Rustin Domingos, Washington, DC, United States, Mark Andrew Olson, University of California, Berkeley, Mathematics, Berkeley, United States and Shefali Bhatia, University of California, Berkeley, Berkeley, United States
 
Direct calculation of vapor-liquid equilibrium from ab initio Gibbs ensemble (538356)
Zhi LI1,2, Razvan Caracas3, Francois Soubiran4 and Christophe Winisdoerffer1,5, (1)Ecole Normale Supérieure Lyon, Lyon, France, (2)LGLTPE Laboratoire de Géologie de Lyon : Terre, Planètes et Environnement, Villeurbanne Cedex, France, (3)CNRS Lyon, Laboratory of Geology of Lyon, Lyon, France, (4)Ecole Normale Supérieure Lyon, LGLTPE, Lyon, France, (5)Centre de Recherche Astrophysique de Lyon UMR 5574, Lyon, France
 
Predicting Halogen Crystal Structures at Megabar Pressures (556515)
Mark Andrew Olson, University of California Berkeley, Berkeley, CA, United States, Shefali Bhatia, University of California, Berkeley, Berkeley, United States and Burkhard Militzer, University of California Berkeley, Department of Earth and Planetary Science, Berkeley, CA, United States
 
Assessing composition space and tunnel size in mineral hollandite by employing Artificial Neural Network (558792)
Dipta B Ghosh1, Bijaya B Karki1 and Jianwei Wang2, (1)Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States, (2)Louisiana State University, Baton Rouge, LA, United States
 
Liquid-vapor coexistence and critical point of Mg2SiO4 from ab-initio simulations (591542)
Joshua P Townsend, Sandia National Laboratories, Albuquerque, NM, United States and Gil Shohet, Stanford University, Aeronautics and Astronautics, Stanford, CA, United States
 
First-Principles Computational Study of Diffusional Mg Isotopes in MgSiO3 melts (605492)
Haiyang Luo1, Bijaya B Karki2, Dipta B Ghosh2 and Huiming Bao1, (1)Louisiana State University, Department of Geology & Geophysics, Baton Rouge, LA, United States, (2)Louisiana State University, Department of Computer Science, Department of Geology & Geophysics, Center for Computation and Technology, Baton Rouge, LA, United States
 
An Internal Energy dependent Grüneisen Parameter Model From Molecular Dynamics Simulations (615319)
Yacong Zhou, California Institute of Technology, Pasadena, CA, United States, Paul D Asimow, California Institute of Technology, Geological and Planetary Sciences, Pasadena, CA, United States and Wiliiam A. Goddard III, California Institute of Technology, Chemistry and Materials Science, Pasadena, CA, United States
 
Effectiveness of Machine Learning Algorithms To Use Unconstrained Data for Lithofacies Prediction in Carbonate Reservoir (635230)
Abhishek Bisui, Ravi Sharma, Kunal Sharma and Sambit Sarkar, Indian Institute of Technology Roorkee, Department of Earth Sciences, Roorkee, India