Difference between revisions of "Methods"

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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>
 
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>
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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>
  
 
===Disordered structures===
 
===Disordered structures===

Revision as of 16:57, 14 January 2022

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

A supercell can be made in VESTA by going into Edit -> Edit data -> Unit Cell...

When the window for the unit cell has opened press Transform, change the numbers in the Transformation matrix to make a supercell of your choice.

Surfaces and slabs

Slabs can be constructed using ASE.

A specific surface can be exposed using VESTA, here is a youtube tutorial for exposing the (110) surface of a TiO2 rutile structure, tutorials for other structures can be found on the same youtube channel.

To make a supercell or a slab from the new unit cell you have just created VESTA you have to export the unit cell in a .vasp format. Open the vasp file in VESTA and then follow the same procedure for the creation of a supercell as has been explained above.

Finite-size correction for slab supercell calculations of materials with spontaneous polarization [1]

Grain boundaries and interfaces

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

Materials project provides a list of matching structures and terminations under the Substrates section for a selected structure.

Special grain boundaries in perovskites [2]

Machine learning sampling to determine rigid body translation [3]

Disordered structures

Defect calculations

Charge correction

Self-Consistent Potential Correction for Charged Periodic Systems [4]

CoFFEE: Corrections For Formation Energy and Eigenvalues for charged defect simulations [5]

Limitations of empirical supercell extrapolation for calculations of point defects in bulk, at surfaces, and in two-dimensional materials [6]

Defect configurations

Evolutionary computing and machine learning for discovering of low-energy defect configurations [7]

Phonon calculations

Phonopy

Nudged Elastic Band (NEB)

Polaron localization

Visualization of defect states

Bader charge analysis

FFT grid convergence?

Error messages

References

  1. Yoo, SH., Todorova, M., Wickramaratne, D. et al. Finite-size correction for slab supercell calculations of materials with spontaneous polarization. npj Comput Mater 7, 58 (2021) http://dx.doi.org/10.1038/s41524-021-00529-1
  2. 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
  3. 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
  4. Mauricio Chagas da Silva, Michael Lorke, Bálint Aradi, Meisam Farzalipour Tabriz, Thomas Frauenheim, Angel Rubio, Dario Rocca, and Peter Deák Phys. Rev. Lett. 126, 076401. https://doi.org/10.1103/PhysRevLett.126.076401
  5. Naik, Mit H., and Manish Jain. CoFFEE: corrections for formation energy and eigenvalues for charged defect simulations. Computer Physics Communications 226 (2018) 114-126. https://doi-org/10.1016/j.cpc.2018.01.011
  6. Christoph Freysoldt, Jörg Neugebauer, Anne Marie Z. Tan, and Richard G. Hennig, Limitations of empirical supercell extrapolation for calculations of point defects in bulk, at surfaces, and in two-dimensional materials, Phys. Rev. B 105, 01410 http://dx.doi.org/10.1103/PhysRevB.105.014103
  7. 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