Abinit 2025: New capabilities for the predictive modeling of solids and nanomaterials

Abinit is a widely used scientific software package implementing density functional theory and many related functionalities for excited states and response properties. This paper presents the novel features and capabilities, both technical and scientific, which have been implemented over the past 5 years. This evolution occurred in the context of evolving hardware platforms, high-throughput calculation campaigns, and the growing use of machine learning to predict properties based on databases of first-principle results. We present new methodologies for ground states with constrained charge, spin, or temperature; for density functional perturbation theory extensions to flexoelectricity and polarons; and for excited states in many-body frameworks including GW, dynamical mean field theory, and coupled cluster. Technical advances have extended Abinit high-performance execution to graphical processing units and intensive parallelism. Second-principles methods build effective models on top of first-principle results to scale up in length and time scales. Finally, workflows have been developed in different community frameworks to automate Abinit calculations and enable users to simulate hundreds or thousands of materials in controlled and reproducible conditions.

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Publication Details

Journal
The Journal of Chemical Physics
Published
2025-10-28
DOI
https://doi.org/10.1063/5.0288278
Citations
7
Primary Topic
Nonlocal and gradient elasticity in micro/nano structures
Type
article
Field-Weighted Citation Impact
3.62
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article

Abinit 2025: New capabilities for the predictive modeling of solids and nanomaterials

Julien Bouquiaux, Bogdan Guster, Miquel Royo, Guido Petretto et al.
7 citations
The Journal of Chemical Physics
Nonlocal and gradient elasticity in micro/nano structures
3.62
article

Abinit 2025: New capabilities for the predictive modeling of solids and nanomaterials

Julien Bouquiaux, Bogdan Guster, Miquel Royo, Guido Petretto, Lórien MacEnulty, Asier Zabalo, F. Jollet, Maryam Azizi, Christian Tantardini, Bernard Amadon, Aloïs Castellano, Clément Duval, David D. O’Regan, François Soubiran, Josef W. Zwanziger, François Bottin, Louis Bastogne, Charles Paillard, Maxime Mignolet, D. R. Hamann, Éric Bousquet, J. Bouchet, Marc Torrent, Xu He, Philippe Ghosez, Huazhang Zhang, Pierre Kestener, João Abreu, Austin Zadoks, Samare Rostami, Félix Antoine Goudreault, Gabriel Antonius, Olivier Gingras, Massimiliano Stengel, Jordan Bieder, Mauricio Rodríguez‐Mayorga, Jean Clérouin, James Boust, David Waroquiers, Samuel Poncé, Jean-Baptiste Charraud, Nils Brouwer, N. A. W. Holzwarth, A. Romero, Fabien Bruneval, Robinson Outerovitch, Alireza Sasani, Véronique Brousseau-Couture, Frédéric Gendron, Raveena Gupta, Olle Hellman, Grégory Geneste, Matteo Giantomassi, Xavier Gonze, Michel Côté, Alejandro Gallo, Francesco Ricci, Matthieu Jean Verstraete, Augustin Blanchet, Gian‐Marco Rignanese, Lucas Baguet, Fernando Gómez‐Ortiz, Vasilii Vasilchenko, Fabien Brieuc, Romuald Béjaud, Victor Trinquet, Emmanuel Castiel, Enrico Marazzi, Olivier Nadeau, Andreas Grüneis, Ioanna-Maria Lygatsika, Jean-Michel Beuken, Guillaume E. Allemand, Marc Sarraute, Clémentine Barat
article en
7 citations

Abstract

Abinit is a widely used scientific software package implementing density functional theory and many related functionalities for excited states and response properties. This paper presents the novel features and capabilities, both technical and scientific, which have been implemented over the past 5 years. This evolution occurred in the context of evolving hardware platforms, high-throughput calculation campaigns, and the growing use of machine learning to predict properties based on databases of first-principle results. We present new methodologies for ground states with constrained charge, spin, or temperature; for density functional perturbation theory extensions to flexoelectricity and polarons; and for excited states in many-body frameworks including GW, dynamical mean field theory, and coupled cluster. Technical advances have extended Abinit high-performance execution to graphical processing units and intensive parallelism. Second-principles methods build effective models on top of first-principle results to scale up in length and time scales. Finally, workflows have been developed in different community frameworks to automate Abinit calculations and enable users to simulate hundreds or thousands of materials in controlled and reproducible conditions.

The Journal of Chemical PhysicsVol. 163(16)
Rutgers, The State University of New Jersey (US), Institució Catalana de Recerca i Estudis Avançats (ES), West Virginia University (US), Centre National de la Recherche Scientifique (FR), Dalhousie University (CA), King Fahd University of Petroleum and Minerals (SA), Université Toulouse III - Paul Sabatier (FR), TU Wien (AT), Institut Pasteur (FR), University of Liège (BE), Université du Québec à Montréal (CA), University of Applied Sciences Utrecht (NL), Utrecht University (NL), Wuhan University of Technology (CN), Trinity College (CA), Trinity College Dublin (IE), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), Xerox (France) (FR), American Committee for the Weizmann Institute of Science (US), CEA DAM Île-de-France (FR), CentraleSupélec (FR), CEA Cadarache (FR), Instituto de Física Teórica (ES), CEA Paris-Saclay (FR), European Theoretical Spectroscopy Facility (BE), Institut de Ciència de Materials de Barcelona (ES), Laboratoire Vision Action Cognition (FR), Walloon Excellence in Lifesciences and Biotechnology (BE), Laboratoire de Chimie et Physique Quantiques (FR), Grand Charleroi Hospital (BE), Flatiron Health (United States) (US), Institut de Physique Théorique (FR), Composite Technology Development (United States) (US), Wuhan University of Science and Technology (CN), Wake Forest University (US), École Polytechnique Fédérale de Lausanne (CH), Weizmann Institute of Science (IL), Université du Québec à Trois-Rivières (CA), Université de Montréal (CA), University of Arkansas at Fayetteville (US), European X-Ray Free-Electron Laser (DE), UCLouvain (BE)
Openalex Percentile: Top 6%
Nonlocal and gradient elasticity in micro/nano structures
3.62
DOIOpen Access PDFOpenAlex
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