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Hauptverfasser: Zhang, Xianxi, Yu, Hongyu, Hong, Liangliang, Xiang, Hongjun
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2605.01781
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author Zhang, Xianxi
Yu, Hongyu
Hong, Liangliang
Xiang, Hongjun
author_facet Zhang, Xianxi
Yu, Hongyu
Hong, Liangliang
Xiang, Hongjun
contents Coupled spin-lattice dynamics (SLD) underlie a wide range of magnetic phenomena, yet a unified first-principles framework that propagates both degrees of freedom without empirical parameterization has remained elusive. We present a fully ab initio SLD approach integrated into VASP, in which interatomic forces and effective magnetic fields are obtained at each time step from self-consistent constrained-moment density-functional calculations. The method is validated on four materials spanning ferromagnetic, non-collinear, and geometrically frustrated orders, recovering the correct magnetic ground state in every case from random initial conditions. SLD trajectories also provide physically correlated training data for magnetic machine-learning potentials, as demonstrated for BiFeO$_3$ by a reduction of up to approximately one order of magnitude in energy MAE over training on randomized spin configurations. This framework opens a practical first-principles route to finite-temperature spin-lattice coupled phenomena in magnetic materials.
format Preprint
id arxiv_https___arxiv_org_abs_2605_01781
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle A Fully Ab-Initio Spin-Lattice Dynamics Framework for Magnetic Materials
Zhang, Xianxi
Yu, Hongyu
Hong, Liangliang
Xiang, Hongjun
Materials Science
Computational Physics
Coupled spin-lattice dynamics (SLD) underlie a wide range of magnetic phenomena, yet a unified first-principles framework that propagates both degrees of freedom without empirical parameterization has remained elusive. We present a fully ab initio SLD approach integrated into VASP, in which interatomic forces and effective magnetic fields are obtained at each time step from self-consistent constrained-moment density-functional calculations. The method is validated on four materials spanning ferromagnetic, non-collinear, and geometrically frustrated orders, recovering the correct magnetic ground state in every case from random initial conditions. SLD trajectories also provide physically correlated training data for magnetic machine-learning potentials, as demonstrated for BiFeO$_3$ by a reduction of up to approximately one order of magnitude in energy MAE over training on randomized spin configurations. This framework opens a practical first-principles route to finite-temperature spin-lattice coupled phenomena in magnetic materials.
title A Fully Ab-Initio Spin-Lattice Dynamics Framework for Magnetic Materials
topic Materials Science
Computational Physics
url https://arxiv.org/abs/2605.01781