36 citations · 130 across the 28 of their papers we have counts for
11 papers · 1 filter
Electronic Structure and Dynamical Correlations in Antiferromagnetic BiFeO
Yihan Wu, Mario Caserta, Tommaso Chiarotti +1
We study the electronic structure and dynamical correlations in antiferromagnetic BiFeO, a prototypical room-temperature multiferroic, using a variety of static and dynamical f…
AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions
Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price +65
Artificial intelligence and machine learning are reshaping how we approach scientific discovery, not by replacing established methods but by extending what researchers can probe, p…
The Interoperability Challenge in DFT Workflows Across Implementations
S. K. Steensen, T. S. Thakur, M. Dillenz +11
Interoperability and cross-validation remains a significant challenge in the computational materials discovery community. In this context, we introduce a common input/output standa…
Self-consistent dynamical Hubbard functional for correlated solids
Tommaso Chiarotti, Matteo Quinzi, Andrea Pintus +3
Many-body functionals of the Green's function can provide fundamental advances in electronic-structure calculations, due to their ability to accurately predict both spectral and th…
Functional theory of the occupied spectral density
Andrea Ferretti, Nicola Marzari
We address the problem of interacting electrons in an external potential by introducing the occupied spectral density as fundamental variable. First, we formulate…
Comparative study of magnetic exchange parameters and magnon dispersions in NiO and MnO from first principles
Flaviano José dos Santos, Luca Binci, Guido Menichetti +3
Spin-wave excitations are fundamental to understanding the behavior of magnetic materials and hold promise for future information and communication technologies. Yet, modeling thes…
Quantum Geometry of Data
Alexander G. Abanov, Luca Candelori, Harold C. Steinacker +9
We demonstrate how Quantum Cognition Machine Learning (QCML) encodes data as quantum geometry. In QCML, features of the data are represented by learned Hermitian matrices, and data…
Ab initio functional-independent calculations of the clamped Pockels tensor of tetragonal barium titanate
Virginie de Mestral, Lorenzo Bastonero, Michele Kotiuga +3
We present an ab initio method to calculate the clamped Pockels tensor of ferroelectric materials from density-functional theory, the modern theory of polarization exploiting the e…
Dynamical Hubbard approach to correlated materials: the case of transition-metal monoxides
Mario Caserta, Tommaso Chiarotti, Marco Vanzini +1
Electronic correlations beyond static mean-field theories are of fundamental importance in describing the properties of complex materials - such as transition-metal oxides - where…
BaZrS Lights Up: The Interplay of Electrons, Photons, and Phonons in Strongly Luminescent Single Crystals
Rasmus Svejstrup Nielsen, Ángel Labordet Álvarez, Yvonne Tomm +8
Chalcogenide perovskites have emerged as a promising class of materials for the next generation of optoelectronic applications, with BaZrS attracting significant attenti…
Charting the landscape of Bardeen-Cooper-Schrieffer superconductors in experimentally known compounds
Marnik Bercx, Samuel Poncé, Yiming Zhang +8
We perform a high-throughput computational search for novel phonon-mediated superconductors, starting from the Materials Cloud 3-dimensional structure database of experimentally kn…