Predicting Crystal Structures from Molten Phases at Extreme Pressures

ORAL

Abstract

We will present an approach for predicting solid phases under specific pressure and temperature conditions using liquid informed structure searches (LISS). Machine learning potentials and atomistic simulations are employed to study the emergence of finite-temperature crystal structures from molten phases under compression. The method will be illustrated with applications to the phase diagrams of several systems, including Mg and Sn.

* This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract number DEAC52-07NA27344. Authors acknowledge funding support from the Laboratory Directed Research and Development Program at LLNL under the project tracking code 23-ERD-042.

–

Presenters

  • Arpit Agrawal

    Lawrence Livermore National Lab

Authors

  • Arpit Agrawal

    Lawrence Livermore National Lab

  • Stanimir A Bonev

    Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory