A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency
Creators
- 1. Theory and Simulation of Materials (THEOS), and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
- 2. Department of Energy Conversion and Storage, Technical University of Denmark, Fysikvej 309, 2800 Kgs Lyngby, Denmark
* Contact person
Description
Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the provenance of all data and calculations as stored by AiiDA. *** UPDATE April 2020 *** The zipped tarball archives and AiiDA export files had inconsistent internal formats and naming conventions, which made it difficult to work with them programmatically. In this update, the files are standardized according to the conventions that are detailed in the README.md file. Note that the actual content of pseudo potential files and the JSON metadata files has **not** changed, with the exception that the keys "cutoff" and "dual" in the JSON files have been replaced with "cutoff_wfc" and "cutoff_rho". Here the value of "cutoff_wfc" is equal to the old "cutoff", and "cutoff_rho" is equal to the product of the old "cutoff" and "dual". Besides that, the update concerns merely the renaming of certain files and the restructuring of archive formats. *** UPDATE November 2020 *** The AiiDA export files contained in the sssp.tar archive have been modified and migrated to version format 0.9 in order to be imported in AiiDA 1.2.0 and later versions. The modifications are detailed in the README.md file in the sssp.tar archive. The AiiDA export files contained in the sssp_bands.tar archive have been migrated to version format 0.9 as well.
Files
File preview
files_description.md
All files
Files
(10.5 GiB)
Name | Apps | Size | |
---|---|---|---|
md5:98b9abf2990d131b71d579edb0acd048
|
3.3 KiB | Preview Download | |
md5:c0f9df05fb4cd4921f4caa25606815ef
|
3.6 KiB | Preview Download | |
md5:5e75f85896b6f635d43f1bc368c2f7c5
|
2.1 KiB | Preview Download | |
md5:e8d5113d0ce0f4e1648edb3d6843d2d8
|
1.7 GiB | Download | |
md5:5abe0dc4ef87065bbf3a0ea55de7835e
|
|
34.3 MiB | Download |
md5:685c4e04def7259eaabb385e94fa8d6b
|
17.5 KiB | Preview Download | |
md5:0fc1ac970ab91c2b58aedccd3adb9699
|
34.4 MiB | Download | |
md5:121442338b807cfd7ccec5a98d5d51a7
|
|
34.9 MiB | Download |
md5:186eaedb52cff3fc7f619b2cc2cebbfe
|
17.5 KiB | Preview Download | |
md5:bf8df1e60e04e6a6cb8e1934a93009e6
|
35.0 MiB | Download | |
md5:fd8e8395cc3af7dd8409daaad4381c64
|
|
36.0 MiB | Download |
md5:0d5d6c2c840383c7c4fc3a99b5dc3001
|
17.6 KiB | Preview Download | |
md5:4803ce9fd1d84c777f87173cd4a2de33
|
36.1 MiB | Download | |
md5:41dce262f39af078dcfd4023f648f018
|
|
36.7 MiB | Download |
md5:1576d4b452769d5308ff444b2e4aff4e
|
17.6 KiB | Preview Download | |
md5:4d2a12f814ee0f822b8dcb27bced747b
|
36.8 MiB | Download | |
md5:ba17a17a5e60c52c467884f47e1f9c44
|
|
36.9 MiB | Download |
md5:e810948a8cb60b75eb902895fabb6a4b
|
17.7 KiB | Preview Download | |
md5:b3bd9dc478822455a80be7a3202bc644
|
37.0 MiB | Download | |
md5:81995b48f51ab8927be0e7c625ad0d3a
|
|
37.9 MiB | Download |
md5:b8e298ab61eb04de8c503f8e6056fe97
|
17.7 KiB | Preview Download | |
md5:061a73df6fcfc06452194ad15f063b5c
|
38.0 MiB | Download | |
md5:b4cb4f952f79a994aef590fa4ab6d978
|
8.1 GiB | Download | |
md5:3c531dcb0245d53db9c65436c2e24281
|
165.1 MiB | Download |
References
Journal reference G. Prandini, A. Marrazzo, I. E. Castelli, N. Mounet, N. Marzari, npj Computational Materials 4, 72 (2018)., doi: 10.1038/s41524-018-0127-2