Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.34295

Controllable charge-spin conversion in sliding multiferroic metal Fe3GaTe2

Tongrui Li·Lidong Zhang·Weiyi Pan
View original source ↗Read source document ↗Export metadata ↓

Abstract

Controlling charge--spin conversion within a single magnetic material is important for compact spintronic devices. Using first-principles calculations, symmetry analysis, and Wannier-based linear response, we study the Edelstein and spin Hall responses of sliding-ferroelectric bilayer \ce{Fe3GaTe2}. Two degenerate ground states with opposite interlayer sliding vectors and out-of-plane dipole moments are separated by a calculated switching barrier of about $16.3$~meV per unit cell. Magnetization orientation determines the allowed current-induced spin components, while ferroelectric switching induces component-selective sign reversals governed by $M_z\mathcal T$ for in-plane magnetization and by $M_z$ for out-of-plane magnetization. The Edelstein response is strongly energy dependent, with spin accumulation approaching $2~\hbar$ for $\mathbf m\parallel+y$ under a reference field of $1$~V/Å. Momentum-resolved analysis links the TR-even and TR-odd Edelstein responses to $Γ$-centered constant-energy contours and localized interband features, respectively. Spin-conductivity contributions show the opposite momentum-space character, with broad sign-competing spin Berry curvature for TR-even and narrow Fermi-surface contours for TR-odd. The transverse spin Hall conductivity reaches $\sim10^{3}\,(\hbar/e)(\mathrm{S/cm})$ and depends strongly on ferroelectric state and magnetization direction. Magnetization rotations in the $xy$ and $xz$ planes reveal symmetry-allowed higher angular harmonics in both spin accumulation and spin-current responses. These results establish sliding-ferroelectric bilayer \ce{Fe3GaTe2} as a tunable platform for reconfigurable spin accumulation and spin-current generation.

Explore related subjects

cond-mat.str-elcond-mat.mtrl-sci

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tongrui Li, Lidong Zhang, Weiyi Pan. 2026-10-25. Controllable charge-spin conversion in sliding multiferroic metal Fe3GaTe2. https://arxiv.org/abs/2610.34295

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Transport and Phase competition in three-dimensional Hubbard-Holstein model at half-filling

We investigate the magnetotransport properties of the one-band Hubbard-Holstein model at half-filling in three dimensions (3D) using exact diagonalization based semi-classical Monte Carlo simulations with phonons treated in the adiabatic limit. The low-temperature electronic correlation $U$ vs electron-phonon coupling $V$ phase diagram reveals two insulating phases--antiferromagnetic (AF-I) and charge-ordered (CO-I)--separated by a first-order transition, with no metallic phase observed at their intersection, indicating robustness of these phases in 3D. For $U \sim bandwidth$, the $V$ vs temperature $T$ phase diagram exhibits multiple phases including AF-I, CO-I, Mott-Hubbard insulator, bipolaronic insulator, and two bipolaronic metallic states. Several first-order transitions occur near $V \sim 3.75$. Above the ordering temperature, the density of states shows universal behavior dominated by electronic contribution, while susceptibility and DOS analyses reveal pseudogap features. Magnetic and transport properties along the phase boundary highlight strong proximity effects between competing phases, suggesting routes for tuning correlated materials and emergent electronic states.

cond-mat.str-el↗
arXiv2026

Open Wilson chain numerical renormalization group approach to steady-state non-equilibrium quantum transport

The numerical renormalization group (NRG) approach was developed to identify and quantify different equilibrium regimes of quantum impurity systems (QISs) with unprecedented accuracy by a tailored finite size representation. Out of equilibrium, the steady-state density operator is not of the Boltzmannian form but one that is determined by the imposed boundary conditions. We extend the NRG to the nonequilibrium setting by augmenting each Wilson site with a reservoir, whose coupling functions are calculated via a continuous fraction expansion in order to recover the continuum limit exactly. The nonequilibrium parameters such as a finite bias as well as a finite temperature gradient enters through the Bloch-Redfield tensor (BRT), whose zero eigenvector gives the steady-state density operator. We used the resulting open chain full density matrix (OC-FDM) approach with an effective single lead description to investigate the charge and spin transport through a quantum dot (QD) under finite bias and temperature gradient. The influence of lead asymmetry and an external magnetic field on the transport properties are also studied. For completeness, we have also investigated local properties of the QD, such as charge fluctuations and find excellent agreement with real-time quantum Monte Carlo (RT-QMC) data. The OC-FDM approach was able to explore Kondo energy scales as low as $T_K/D \approx 10^{-8}$ in the non-equilibrium regime, as well as show convergence with the established equilibrium benchmarks, such as a quantitative agreement with full density matrix numerical renormalization group (FDM-NRG) and Fermi-liquid scaling at small bias and temperature. Owing to the effective single lead description, a single OC-FDM data point takes orders of magnitude less time on a standard laptop, compared to other state-of-the-art numerical methods.

cond-mat.str-el↗
arXiv2026

Designing Strongly Correlated Quantum Phases of Matter with Foundation Neural-Network Quantum States

Materials design is an inverse problem: finding the couplings of a microscopic Hamiltonian whose ground state exhibits a desired property. For strongly correlated quantum systems, this remains largely out of reach, as each candidate Hamiltonian requires its own costly simulation. Here we show that Foundation Neural-Network Quantum States, single wave functions that encode the ground states of an entire family of Hamiltonians, make this search efficient. Because the Hamiltonian couplings enter as neural-network inputs, any ground-state property can be optimized by gradient descent directly in coupling space. We use this approach to search for nonmagnetic phases in two-dimensional spin models in coupling spaces of increasing dimensionality. Specifically, we focus on quantum spin liquids, exotic phases of matter in which quantum fluctuations prevent magnetic order at zero temperature. In the largest search space considered, spanned by eight superexchange couplings and containing many paradigmatic frustrated spin systems, the optimization converges to the $J_1$-$J_2$-$δ$ Heisenberg model when starting from a magnetic phase. We show that the ground state at the optimum set of couplings has neither magnetic nor valence-bond order in the thermodynamic limit, leading to a new quantum spin-liquid candidate. The approach is completely general and can be extended to other models and physical properties to optimize, demonstrating that Neural-Network Quantum States are tools not only for simulating quantum matter but also for designing it.

cond-mat.str-el↗