Automated Workflow for Accurate High-Throughput GW Calculations
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arXiv
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| Format: | Preprint |
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2024
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| author | Varrassi, Lorenzo Ellinger, Florian Flage-Larsen, Espen Wolloch, Michael Kresse, Georg Marzari, Nicola Franchini, Cesare |
| author_facet | Varrassi, Lorenzo Ellinger, Florian Flage-Larsen, Espen Wolloch, Michael Kresse, Georg Marzari, Nicola Franchini, Cesare |
| contents | The GW approximation represents the state-of-the-art ab-initio method for computing excited-state properties. Its execution requires control over a larger number of (often interdependent) parameters, and therefore its application in high-throughput studies is hindered by the intricate and time-consuming convergence process across a multi-dimensional parameter space. To address these challenges, here we develop a fully-automated open-source workflow for G$_0$W$_0$ calculations within the AiiDA-VASP plugin architecture. The workflow is based on an efficient estimation of the errors on the quasi-particle (QP) energies due to basis-set truncation and the pseudo-potential norm violation, which allows a reduction of the dimensionality of the parameter space and avoids the need for multi-dimensional convergence searches. Protocol validation is conducted through a systematic comparison against established experimental and state-of-the-art GW data. To demonstrate the effectiveness of the approach, we construct a database of QP energies for a diverse dataset of over 320 bulk structures. The openly accessible workflow and resulting dataset can serve as a valuable resource and reference for conducting accurate data-driven research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_15948 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automated Workflow for Accurate High-Throughput GW Calculations Varrassi, Lorenzo Ellinger, Florian Flage-Larsen, Espen Wolloch, Michael Kresse, Georg Marzari, Nicola Franchini, Cesare Materials Science Computational Physics The GW approximation represents the state-of-the-art ab-initio method for computing excited-state properties. Its execution requires control over a larger number of (often interdependent) parameters, and therefore its application in high-throughput studies is hindered by the intricate and time-consuming convergence process across a multi-dimensional parameter space. To address these challenges, here we develop a fully-automated open-source workflow for G$_0$W$_0$ calculations within the AiiDA-VASP plugin architecture. The workflow is based on an efficient estimation of the errors on the quasi-particle (QP) energies due to basis-set truncation and the pseudo-potential norm violation, which allows a reduction of the dimensionality of the parameter space and avoids the need for multi-dimensional convergence searches. Protocol validation is conducted through a systematic comparison against established experimental and state-of-the-art GW data. To demonstrate the effectiveness of the approach, we construct a database of QP energies for a diverse dataset of over 320 bulk structures. The openly accessible workflow and resulting dataset can serve as a valuable resource and reference for conducting accurate data-driven research. |
| title | Automated Workflow for Accurate High-Throughput GW Calculations |
| topic | Materials Science Computational Physics |
| url | https://arxiv.org/abs/2410.15948 |