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Thermodynamics and dielectric response of BaTiO_(3)by data-driven modeling

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npj Computational Materials 2022年第1期8卷 1998-2014页

作者： Lorenzo Gigli Max Veit Michele Kotiuga giovanni pizzi Nicola Marzari Michele Ceriotti Laboratory of Computational Science and Modeling(COSMO) Institute of MaterialsÉcole Polytechnique Fédérale de LausanneCH-1015LausanneSwitzerland Theory and Simulation of Materials(THEOS)and National Centre for Computational Design and Discovery of Novel Materials(MARVEL) École Polytechnique Fédérale de LausanneCH-1015LausanneSwitzerland

Modeling ferroelectric materials from first principles is one of the successes of density-functional theory and the driver of much development effort,requiring an accurate description of the electronic processes and the thermodynamic equilibrium that drive the spontaneous symmetry breaking and the emergence of macroscopic *** demonstrate the development and application of an integrated machine learning model that describes on the same footing structural,energetic,and functional properties of barium titanate(BaTiO_(3)),a prototypical *** model uses ab initio calculations as a reference and achieves accurate yet inexpensive predictions of energy and polarization on time and length scales that are not accessible to direct ab initio *** predictions allow us to assess the microscopic mechanism of the ferroelectric *** presence of an order-disorder transition for the Ti off-centered states is the main driver of the ferroelectric transition,even though the coupling between symmetry breaking and cell distortions determines the presence of intermediate,partly-ordered ***,we thoroughly probe the static and dynamical behavior of BaTiO_(3)across its phase diagram without the need to introduce a coarse-grained description of the ferroelectric ***,we apply the polarization model to calculate the dielectric response properties of the material in a full ab initio manner,again reproducing the correct qualitative experimental behavior.

关键词： transition ferroelectric dielectric

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

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npj Computational Materials 2023年第1期9卷 1609-1618页

作者： Miki Bonacci Junfeng Qiao Nicola Spallanzani Antimo Marrazzo giovanni pizzi Elisa Molinari Daniele Varsano Andrea Ferretti Deborah Prezzi FIM Department University of Modena and Reggio EmiliaVia Campi 213/aModenaItaly S3 Center Istituto NanoscienzeCNRVia Campi 213/aModenaItaly Theory and Simulation of Materials(THEOS)and National Centre for Computational Design and Discovery of Novel Materials(MARVEL) École Polytechnique Fédérale de LausanneCH-1015 LausanneSwitzerland Dipartimento di Fisica Universitàdi TriesteI-34151 TriesteItaly Laboratory for Materials Simulations(LMS) Paul Scherrer Institut(PSI)CH-5232 Villigen PSISwitzerland

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 *** 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)***,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 *** 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 *** proposed developments are validated on a set of representative semiconductor and metallic systems.

关键词： properties perturbation theory

Projectability disentanglement for accurate and automated electronic-structure Hamiltonians

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npj Computational Materials 2023年第1期9卷 215-228页

Maximally-localized Wannier functions(MLWFs)are broadly used to characterize the electronic structure of ***,one can construct MLWFs describing isolated bands(*** bands of insulators)or entangled bands(*** and conduction bands of insulators,or metals).Obtaining accurate and compact MLWFs often requires chemical intuition and trial and error,a challenging step even for experienced researchers and a roadblock for high-throughput ***,we present an automated approach,projectability-disentangled Wannier functions(PDWFs),that constructs MLWFs spanning the occupied bands and their complement for the empty states,providing a tight-binding picture of optimized atomic orbitals in *** to the algorithm is a projectability measure for each Bloch state onto atomic orbitals,determining if that state should be kept identically,discarded,or mixed into the *** showcase the accuracy on a test set of 200 materials,and the reliability by constructing 21,737 Wannier Hamiltonians.

关键词： bands Hamiltonian electronic

Automated high-throughput Wannierisation

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npj Computational Materials 2020年第1期6卷 1091-1108页

作者： Valerio Vitale giovanni pizzi Antimo Marrazzo Jonathan R.Yates Nicola Marzari Arash A.Mostofi Cavendish Laboratory Department of PhysicsUniversity of Cambridge19 JJ Thomson AvenueCambridgeUK Departments of Materials and Physics and the Thomas Young Centre for Theory and Simulation of MaterialsImperial College LondonLondon SW72AZUK Theory and Simulation of Materials(THEOS)and National Centre for Computational Design and Discovery of Novel Materials(MARVEL) École Polytechnique Fédérale de LausanneLausanneSwitzerland Department of Materials University of OxfordParks RoadOxford OX13PHUK

Maximally-localised Wannier functions(MLWFs)are routinely used to compute from first-principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging *** the same time,high-throughput(HT)computational materials design is an emergent field that promises to accelerate reliable and cost-effective design and optimisation of new materials with target *** use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is,in general,very *** address this problem directly by proposing a procedure for automatically generating MLWFs for HT *** approach is based on the selected columns of the density matrix method and we present the details of its implementation in an AiiDA *** apply our approach to a dataset of 200 bulk crystalline materials that span a wide structural and chemical *** assess the quality of our MLWFs in terms of the accuracy of the band-structure interpolation that they provide as compared to the band-structure obtained via full first-principles ***,we provide a downloadable virtual machine that can be used to reproduce the results of this paper,including all first-principles and atomistic simulations as well as the computational workflows.

关键词： generating high details

Common workflows for computing material properties using different quantum engines

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npj Computational Materials 2021年第1期7卷 1202-1213页

作者： Sebastiaan P.Huber Emanuele Bosoni Marnik Bercx Jens Bröder Augustin Degomme Vladimir Dikan Kristjan Eimre Espen Flage-Larsen Alberto Garcia Luigi Genovese Dominik Gresch Conrad Johnston Guido Petretto Samuel Poncé Gian-Marco Rignanese Christopher J.Sewell Berend Smit Vasily Tseplyaev Martin Uhrin Daniel Wortmann Aliaksandr V.Yakutovich Austin Zadoks Pezhman Zarabadi-Poor Bonan Zhu Nicola Marzari giovanni pizzi Theory and Simulation of Materials(THEOS)and National Centre for Computational Design and Discovery of Novel Materials(MARVEL) École Polytechnique Fédérale de LausanneLausanneSwitzerland Institut de Ciència de Materials de Barcelona ICMAB-CSICBellaterraSpain Peter Grünberg Institut and Institute for Advanced Simulation Forschungszentrum JülichJülichGermany Department of Physics RWTH Aachen UniversityAachenGermany CEA IRIG-MEM-L_SimUniv.Grenoble-AlpesGrenobleFrance Nanotech@surfaces Laboratory Swiss Federal Laboratories for Materials Science and Technology(Empa)DübendorfSwitzerland SINTEF Industry Materials PhysicsOsloNorway Department of Physics University of OsloOsloNorway Microsoft Station Q University of CaliforniaSanta BarbaraCAUSA Atomistic Simulation Centre School of Mathematics and PhysicsQueen’s University BelfastBelfastUK UCLouvain Institut de la Matière Condensée et des Nanosciences(IMCN)Louvain-la-NeuveBelgium Laboratory of Molecular Simulation(LSMO) Institut des sciences et ingénierie chimiques(ISIC)École Polytechnique Fédérale de Lausanne(EPFL)ValaisSionSwitzerland Department of Chemistry Claverton DownUniversity of BathBathUK The Faraday Institution DidcotUK Department of Chemistry University College LondonLondonUK

The prediction of material properties based on density-functional theory has become routinely common,thanks,in part,to the steady increase in the number and robustness of available simulation *** plurality of codes and methods is both a boon and a *** providing great opportunities for cross-verification,these packages adopt different methods,algorithms,and paradigms,making it challenging to choose,master,and efficiently use *** demonstrate how developing common interfaces for workflows that automatically compute material properties greatly simplifies interoperability and *** introduce design rules for reusable,code-agnostic,workflow interfaces to compute well-defined material properties,which we implement for eleven quantum engines and use to compute various material *** implementation encodes carefully selected simulation parameters and workflow logic,making the implementer’s expertise of the quantum engine directly available to *** workflows are made available as open-source and full reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure.

关键词： quantum routine material