36 citations · 130 across the 28 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
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…
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…
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…
Spectral Operator Representations
Austin Zadoks, Antimo Marrazzo, Nicola Marzari
Machine learning in atomistic materials science has grown to become a powerful tool, with most approaches focusing on atomic arrangements, typically decomposed into local atomic en…
First-Principles Electron-Phonon Interactions and Polarons in the Parent Cuprate LaCuO
Benjamin K. Chang, Iurii Timrov, Jinsoo Park +3
Understanding electronic interactions in high-temperature superconductors is an outstanding challenge. In the widely studied cuprate materials, experimental evidence points to stro…