Unraveling Hidden Order and Dynamics in a Heterogeneous Ferroelectric System Using Machine Learning

10.13139/OLCF/1773493

We uploaded two batches of datasets: Batch-a) Equilibrium dynamics at a constant temperature at zero electric-field, with one trajectory each for 4-different defect structures (i.e. SETs 1 to 4). Each trajectory has a time-step of 0.25 fs, and is run for 7775000 time-steps, with snapshots written out every 4 time-steps (i.e. every 1fs); and Batch-b) Non-Equilibrium dynamics at a constant temperature with the same 0.25 fs time-step, but data dumped every 500 times-steps (i.e. every 125fs) for each of the SETs. The total trajectory of each defect structure (i.e. each SETs 1 to 4) is 2800000 time-steps (5600 snapshots), with stepping of electric-field by 0.01 V/Ã…, after every 100,000 time-steps (i.e. every 200 snapshots), from E=0 to E=0.05 V/Ã… to E = -0.05 V/Ã… to E=0.05 V/Ã….

Published: 2021-04-05 09:56:10 Download Dataset

Dataset Properties

Field Value
Authors
  • Dhakane, Abhijeet Oak Ridge National Laboratory
  • Ganesh, P. Oak Ridge National Laboratory
  • Sivadas, Nikhil Oak Ridge National Laboratory
Project Identifier CNMS
Dataset Type AS Animations/Simulations
Subjects
  • 36 MATERIALS SCIENCE
Keywords
  • Ferroelectrics
  • Molecular Dynamics
Software Needed Paraview
Originating Organizations Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organizations Office of Science (SC)
DOE Contract KC0403040 ERKCZ01

Acknowledgements

Papers using this dataset are requested to include the following text in their acknowledgements:

*Support for 10.13139/OLCF/1773493 is provided by the U.S. Department of Energy, project CNMS under Contract KC0403040 ERKCZ01. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.