Difference between revisions of "Methods"

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provides list of matching terminations of other materials  
 
provides list of matching terminations of other materials  
  
Special grain boundaries in perovskites <ref> B. M. Darinskiy, N. D. Efanova & D. S. Saiko (2020) Special grain boundaries in perovskite crystals, Ferroelectrics, 567:1, 13-19, DOI: 10.1080/00150193.2020.1791582 </ref>
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Special grain boundaries in perovskites <ref> B. M. Darinskiy, N. D. Efanova & D. S. Saiko (2020) Special grain boundaries in perovskite crystals, Ferroelectrics, 567:1, 13-19, https://doi.org/10.1080/00150193.2020.1791582 </ref>
  
 
Tarjei Bondevik, Akihide Kuwabara, Ole Martin Løvvik, Machine learning sampling to determine rigid body translation <ref> Application of machine learning-based selective sampling to determine BaZrO3 grain boundary structures, Computational Materials Science, 164 (2019) 57-65. https://doi.org/10.1016/j.commatsci.2019.03.054 </ref>
 
Tarjei Bondevik, Akihide Kuwabara, Ole Martin Løvvik, Machine learning sampling to determine rigid body translation <ref> Application of machine learning-based selective sampling to determine BaZrO3 grain boundary structures, Computational Materials Science, 164 (2019) 57-65. https://doi.org/10.1016/j.commatsci.2019.03.054 </ref>

Revision as of 13:34, 22 October 2021

Methods

VASP Wiki and Support Forum

The VASP manual contains information on all INCAR tags and tutorials and guides to several types of calculations (www.vasp.at/wiki/).

The VASP Support Forum (www.vasp.at/forum/) allows users to troubleshoot and discuss technical and scientific topics. The VASP developers are also active in answering questions.

Convergence and Efficiency

Convergence tests

How to and relevant examples.

Benchmark

VASP efficiency on Saga (number of nodes/cores)

Computational cost: atoms vs kpoints vs functional etc.

General calculations and relaxation

NELM, NSW

Systems

Supercells

Surfaces and slabs

Grain boundaries and interfaces

Typically modeled as Coincident Site Lattice (CSL) structures that are optimized by rigid body translation.

provides list of matching terminations of other materials

Special grain boundaries in perovskites [1]

Tarjei Bondevik, Akihide Kuwabara, Ole Martin Løvvik, Machine learning sampling to determine rigid body translation [2]

Disordered structures

Defect calculations

Defect configurations

Machine learning approach [3]

Phonon calculations

Nudged Elastic Band (NEB)

Polaron localization

Visualization of defect states

Bader charge analysis

FFT grid convergence?

Error messages

References

  1. B. M. Darinskiy, N. D. Efanova & D. S. Saiko (2020) Special grain boundaries in perovskite crystals, Ferroelectrics, 567:1, 13-19, https://doi.org/10.1080/00150193.2020.1791582
  2. Application of machine learning-based selective sampling to determine BaZrO3 grain boundary structures, Computational Materials Science, 164 (2019) 57-65. https://doi.org/10.1016/j.commatsci.2019.03.054
  3. Arrigoni, M., Madsen, G.K.H. Evolutionary computing and machine learning for discovering of low-energy defect configurations. npj Comput Mater 7, 71 (2021). https://doi.org/10.1038/s41524-021-00537-1