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, an 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.

Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Bonacci Miki
;
Spallanzani Nicola;Molinari Elisa;Varsano Daniele;Ferretti Andrea;Prezzi Deborah
2023

Abstract

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, an 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.
2023
Istituto Nanoscienze - NANO
Istituto Nanoscienze - NANO - Sede Secondaria Modena
Inglese
9
1
74-1
74-10
10
https://www.nature.com/articles/s41524-023-01027-2
Sì, ma tipo non specificato
Computation theory; Density functional theory; Perturbation techniques
Ab initio simulations, Algorithm and implementation, Automated workflow, Density-functional-theory, Fully automated, High-throughput, Interpolation schemes, Many body perturbation theory, Novel materials, Theory calculation
Internazionale
9
info:eu-repo/semantics/article
262
Bonacci, Miki; Qiao, Junfeng; Spallanzani, Nicola; Marrazzo, Antimo; Pizzi, Giovanni; Molinari, Elisa; Varsano, Daniele; Ferretti, Andrea; Prezzi, Deb...espandi
01 Contributo su Rivista::01.01 Articolo in rivista
open
   Materials design at the eXascale
   MaX
   European Commission
   Horizon 2020 Framework Programme
   676598

   MAterials design at the eXascale. European Centre of Excellence in materials modelling, simulations, and design
   MaX
   European Commission
   Horizon 2020 Framework Programme
   824143

   MAterials design at the eXascale
   MaX
   European Commission
   Horizon Europe Framework Programme
   101093374

   Battery Interface Genome - Materials Acceleration Platform
   BIG-MAP
   European Commission
   Horizon 2020 Framework Programme
   957189

   Supercomputing Unified Platform - Emilia-Romagna
   SUPER
   Regione Emilia-Romagna PORFESR 2014-2020
   Regione Emilia-Romagna PORFESR 2014-2020
   SUPER (Supercomputing Unified Platform - Emilia-Romagna) from Emilia-Romagna PORFESR 2014-2020 regional funds

   Excitonic insulator in two-dimensional long-range interacting systems
   EXC-INS
   MIUR
   PRIN2017 2017BZPKSZ
   PRIN2017 2017BZPKSZ

   ICSC - Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, funded by European Union - NextGenerationEU - PNRR, Missione 4 Componente 2 Investimento 1.4
   ICSC
   European Union
   European Union - NextGenerationEU - PNRR, Missione 4 Componente 2 Investimento 1.4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/456846
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