Session information

Symposium

D. Data-Driven and Physics-Informed Materials Discovery and Design

[SY-D4] Symposium D-4

Thu. Nov 1, 2018 4:00 PM - 5:30 PM Room8

Chair: Minoru Otani(AIST, Japan)

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[SY-D4] Exploration of large ab initio data spaces to design structural materials with superior mechanical properties

Invited

^○Joerg Neugebauer, Jan Janssen, Tilmann Hickel, Blazej Gabowski (Max-Planck-Institut fuer Eisenforschung, Germany)

[SY-D4] Toward a machine learning aided interatomic potential for multi-element alloys: Application to binary compounds

^○Doyl Dickel, David Francis, Christopher Barrett (Mississippi State University, United States of America)

[SY-D4] Machine Learning potentials for modeling iradiation defects in iron and tungsten

^○Alexandra Goryaeva¹, Jean-Bernard Maillet², Mihai-Cosmin Marinica¹ (1.DEN-Service de Recherches de Métallurgie Physique, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France, 2.CEA-DAM DIF, 91297 Arpajon Cedex, France)

[SY-D4] Effect of friction and ductility on relaxation dynamics and mechanical memory of crumpled materials

^○Mehdi Habibi, Eric van Bruggen (Wageningen University, Netherlands)

[SY-D4] Big-data insights into solute-GB segregation

^○Liam Huber, Blazej Grabowski, Joerg Neugebauer (MPIE, Germany)

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