Miki Bonacci^1,2*, Junfeng Qiao³, Nicola Spallanzani¹, Antimo Marrazzo⁴, Giovanni Pizzi^3,5, Elisa Molinari^2,1, Daniele Varsano¹, Andrea Ferretti¹, Deborah Prezzi¹

1 S3 Center, Istituto Nanoscienze, CNR, Via Campi 213/a, Modena, Italy

2 FIM Department, University of Modena and Reggio Emilia, Via Campi 213/a, Modena, Italy

3 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

4 Dipartimento di Fisica, Università di Trieste, I-34151 Trieste, Italy

5 Laboratory for Materials Simulations (LMS), Paul Scherrer Institut (PSI), CH-5232 Villigen PSI, Switzerland

* Corresponding authors emails: miki.bonacci@nano.cnr.it

DOI10.24435/materialscloud:6w-qh [version v1]

Publication date: Dec 02, 2022

How to cite this record

Miki Bonacci, Junfeng Qiao, Nicola Spallanzani, Antimo Marrazzo, Giovanni Pizzi, Elisa Molinari, Daniele Varsano, Andrea Ferretti, Deborah Prezzi, Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows, Materials Cloud Archive 2022.161 (2022), https://doi.org/10.24435/materialscloud:6w-qh

Description

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, a novel algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally-localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.

Materials Cloud sections using this data

Files

File name	Size	Description
automatedMBPT.aiida MD5md5:46ff4af8b31314eea5785bdcbd80a517 Open this AiiDA archive on renkulab.io (https://renkulab.io/)	475.2 MiB	AiiDA database, ready to be imported, with the provenance of all calculations run in the project
raw_input_output.tar.gz MD5md5:0773a00e5a7e8f2a4594a3ddb396b6d0	5.5 MiB	Raw Yambo and quantumESPRESSO inputs and outputs
gaps.json MD5md5:a0a0c6380c6ee53a598b962bf26dfc58	1.0 KiB	Data on the converged G0W0 band gaps
README.txt MD5md5:77eee39945ff643fe541746832f29573	1.7 KiB	Information on this entry
README-AiiDA.txt MD5md5:b019a0583e2387706de644e74b3fbfef	2.6 KiB	Informations on how to extract and inspect the automatedMBPT.aiida file

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

BIG-MAP high-throughput AiiDA Yambo code Automated many-body perturbation theory GW BSE G0W0 Wannier interpolation aiida-yambo MaX MARVEL first principles