Comparative study of magnetic exchange parameters and magnon dispersions in NiO and MnO from first principles
Abstract
Spin-wave excitations are fundamental to understanding the behavior of magnetic materials and hold promise for future information and communication technologies. Yet, modeling these accurately in transition-metal compounds remains challenging, starting from the self-interaction errors affecting localized and partially filled -orbitals in density-functional theory (DFT) with (semi-)local functionals. In this work, we compare three advanced first-principles approaches for computing magnetic exchange parameters and magnon dispersions in NiO and MnO, all based on a common DFT+ ground state with ab initio Hubbard values obtained from density-functional perturbation theory. Two methods extract exchange parameters directly: one via total-energy differences using the four-state mapping (), and the other via the magnetic force theorem (MFT) using infinitesimal spin rotations. Magnon dispersions are then obtained from a Heisenberg Hamiltonian through linear spin-wave theory (LSWT). The third approach, time-dependent density-functional perturbation theory with (TDDFPT+), yields magnon dispersions directly from the dynamical spin susceptibility, with exchange parameters fitted a posteriori, for comparison, via LSWT. Our results show that TDDFPT+ and the Heisenberg model based on -derived parameters align well with experimental neutron scattering data, whereas the MFT-based approach shows larger discrepancies, possibly due to some inherent approximations and limitations of the particular implementation used. This study benchmarks the accuracy of state-of-the-art first-principles techniques for spin-wave modeling and contributes to advancing reliable computational tools for the study and design of magnetic materials.
Keywords
Cite
@article{arxiv.2508.12153,
title = {Comparative study of magnetic exchange parameters and magnon dispersions in NiO and MnO from first principles},
author = {Flaviano José dos Santos and Luca Binci and Guido Menichetti and Ruchika Mahajan and Nicola Marzari and Iurii Timrov},
journal= {arXiv preprint arXiv:2508.12153},
year = {2026}
}