################################ ### INTRODUCTION AND CONTENT ### ################################ This entry contains data and workflows to fully reproduce the results published in the corresponding scientific paper about the automatic robust Wannierisation and band-structure interpolation of materials using the SCDM method and our automation protocol: Valerio Vitale, Giovanni Pizzi, Antimo Marrazzo, Jonathan R. Yates, Nicola Marzari, Arash A. Mostofi, npj Computational Materials 6, 66 (2020) doi:10.1038/s41524-020-0312-y In particular, this entry contains the AiiDA database with the full provenance of the simulations performed in the paper, as well as a Virtual Machine ("The Wannierising Machine", version 19.07) that contains AiiDA, Quantum ESPRESSO, Wannier90 and the respective workflows and software needed to re-run the same simulations of the paper or even run new simulations with the same protocol. ################################################################## ### FURTHER INSTRUCTIONS AND READMES FOR THE DIFFERENT CONTENT ### ################################################################## Various README files and data are provided: - **AiiDA provenance**: In order to inspect the data generated during the simulations and inspect their full provenance as stored by AiiDA, follow the instructions in the README-AiiDA.txt" file. The AiiDA database, ready to be imported, with the provenance of all calculations run in the project, is in the export file "automatic_wannier_provenance.aiida" (it requires AiiDA 1.0 or later). - **Run new simulations with AiiDA in a Virtual Machine**: In order to install the virtual machine and run a Wannierisation, use the Virtual Machine image "wannierising_machine_19.07.ova", following the instructions in the "README-virtual-machine.txt" file for the installation and in "tutorial-with-screenshots-VM.pdf" to run the Wannierisation. - **Recreate automatically the Virtual Machine from scratch**: In order to recreate the virtual machine from scratch, use the ansible scripts that are provided in the file "wannierising_machine_19.07_ansible_scripts.tar.gz" - **Input crystal structures**: You can find the data of the crystal structures used in this work in the two files "xsf.tar.gz" (200 metals and insulators when considering also conduction bands) and "xsf_insulators.tar.gz" (81 insultators when considering only valence bands). This data is also stored inside the virtual machine. The crystal structures are stored in XSF format (whose specifications can be found here: http://www.xcrysden.org/doc/XSF.html) - **Data on spreads and bands distance**: the JSON file `automated_wannier_discover_data.json` contains information on all the systems simulated in the project, including in particular the UUID of the relevant crystal-structure and band-structure nodes, as well as the spread of the Wannier functions and the bands distance. More specifically, the schema of the JSON is the following: - Top level dictionary: keys are chemical formulas, values are dictionaries with the following schema: - "structure_uuid": UUID of the input crystal structure - "bands": dictionary with the following schema: - "DFT_uuid": UUID of the DFT bands calculation - "Wannier": dictionary where the key indicates the dataset (either "with_conduction" or "valence_only"; often there is only one of these two keys) and the value is dictionary with the following schema: - the key indicates the method ("SCDM_only", "SCDM+MLWF" or "random+MLWF", the latter existing only in the "valence_only" dataset), and the value is a dictionary with the following schema: - the key is the k-points mesh target linear density in angstrom^-1, as described in the paper, as a string (valid values: "0.15", "0.2", "0.3", "0.4"), and the value is a dictionary with the following schema: - "bands_node_uuid": UUID of the Wannier bands calculation - "total_spread": total spread computed by Wannier90 in angstrom^2 - "gauge_invariant_spread": gauge-invariant component of the spread computed by Wannier90 in angstrom^2 - "eta": average bands distance (see definition in the paper) in eV - "eta_max": max bands distance (see definition in the paper) in eV - **Band structures**: You can find a PDF with all band structures studied in the paper in the PDF file `Vitale-2020-all-bands.pdf`, for easy inspection. The first page of the PDF describes in more detail the content of the file. - **Fermi energies**: The file `fermi_energies.json` contains the Fermi energy for each material, as returned by Quantum ESPRESSO. The JSON contains a dictionary. Each key of the dictionary is the chemical formula of the material, and the value is the Fermi energy of the material in eV. ######################################## ### HOW TO CITE AND ACKNOWLEDGEMENTS ### ######################################## When using the data or the virtual machine, we kindly ask you to please cite also the corresponding scientific paper: Valerio Vitale, Giovanni Pizzi, Antimo Marrazzo, Jonathan R. Yates, Nicola Marzari, Arash A. Mostofi, npj Computational Materials 6, 66 (2020) doi:10.1038/s41524-020-0312-y