activity
20202026
most citedElectronic structure of pristine and Ni-substituted LaFeO from near edge x-ray absorption fine structure experiments and first-principles simulations

36 citations · 130 across the 28 of their papers we have counts for

collaborators

31 papers

cond-mat.str-el2026

Spectral signatures of spin textures and the emergence of a pseudogap

Matteo Quinzi, Andrea Pintus, Tommaso Chiarotti +2

Periodic solids with strongly interacting electrons display phenomena -- from Mott localization to high-temperature superconductivity -- that escape conventional band theory. Effor…

hep-ph2026

A Unified Geometric Framework for Understanding Collider Event Manifolds

Tianji Cai, Hancheng Li

By defining notions of similarity between collider events, metrics give rise to event manifolds with nontrivial geometric structure. Understanding these structures and their relati…

cond-mat.mtrl-sci2026

Assessing the magnetic states and the accuracy of first-principles Hubbard corrections for the battery cathode LiCoO ()

Valentina Sanella, Cristiano Malica, Alberto Carta +4

LiCoO is a prototypical layered cathode material for Li-ion batteries, yet its accurate description from first principles remains challenging because of self-interaction er…

math.NA2026

Randomized Block Davidson Eigensolvers for Plane-Wave Density-Functional Theory

Moritz Gubler, Taejun Park, Augustin Bussy +4

Iterative diagonalization is the dominant cost of plane-wave density-functional theory (DFT), with search-space orthogonalization scaling particularly quickly with problem size and…

cond-mat.mtrl-sci2026

DFT+U+V is equivalent to DFT+U with density-dependent hybridized projectors

Edward Linscott, Alberto Carta, Nicola Marzari

Hubbard-corrected density-functional theory (DFT+) is a popular tool for first-principles modeling of materials with localized or electrons, but its on-site corrections…

cond-mat.mtrl-sci2026

Predicting challenging phase transitions with Bayesian active learning

Lorenzo Bastonero, Gabriel Joalland, Chiara Cignarella +2

Materials underpin modern technologies, from energy harvesting, storage, and conversion to information and communication technologies. Their functionality is often governed by the…

cond-mat.mtrl-sci2026

Phonon collisional broadening and heat transport beyond the Boltzmann equation

Enrico Di Lucente, Nicola Marzari, Michele Simoncelli

In crystals, macroscopic technological properties such as thermal conductivity originate from the microscopic drift and scattering of phonons, commonly described by the Boltzmann T…

cond-mat.str-el2025

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…

physics.soc-ph2025

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…

cond-mat.mtrl-sci2025

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…

cond-mat.str-el2025

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…

cond-mat.mtrl-sci2025

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…

cond-mat.mtrl-sci2025★ 3 cited

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…

cs.LG2025

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…

cond-mat.mtrl-sci2025★ 1 cited

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…

cond-mat.str-el2025

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…

cond-mat.mtrl-sci2025★ 9 cited

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…

cond-mat.supr-con2025★ 10 cited

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…

cond-mat.mtrl-sci2024

Predicting the suitability of photocatalysts for water splitting using Koopmans spectral functionals: The case of TiO polymorphs

Marija Stojkovic, Edward Linscott, Nicola Marzari

Photocatalytic water splitting has attracted considerable attention for renewable energy production. Since the first reported photocatalytic water splitting by titanium dioxide, th…

cond-mat.mtrl-sci2024

The Interplay Between Electron Localization, Magnetic Order, and Jahn-Teller Distortion that Dictates LiMnO Phase Stability

Ronald L. Kam, Luca Binci, Aaron D. Kaplan +3

The development of Mn-rich cathodes for Li-ion batteries promises to alleviate supply chain bottlenecks in battery manufacturing. Challenges in Mn-rich cathodes arise from Jahn-Tel…

cond-mat.mtrl-sci2024★ 6 cited

Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals

Luca Binci, Nicola Marzari, Iurii Timrov

Spin excitations play a fundamental role in understanding magnetic properties of materials, and have significant technological implications for magnonic devices. However, accuratel…

cond-mat.mtrl-sci2024★ 4 cited

Predicting electronic screening for fast Koopmans spectral functional calculations

Yannick Schubert, Sandra Luber, Nicola Marzari +1

Koopmans spectral functionals are a powerful extension of Kohn-Sham density-functional theory (DFT) that enable the prediction of spectral properties with state-of-the-art accuracy…

cond-mat.mtrl-sci2024

Machine learning Hubbard parameters with equivariant neural networks

Martin Uhrin, Austin Zadoks, Luca Binci +2

Density-functional theory with extended Hubbard functionals (DFT++) provides a robust framework to accurately describe complex materials containing transition-metal or rare-e…

cond-mat.str-el2024

Potential energy surfaces from many-body functionals: analytical benchmarks and conserving many-body approximations

Giovanna Lani, Nicola Marzari

We investigate analytically the performance of many-body energy functionals, derived respectively by Klein and Luttinger and Ward, at different levels of diagrammatic approximation…