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    Controllable dynamic magnetism in reconfigurable ferroelastic domain-wall networks engineered via nanocavities

    Guangming Lu1,*, Shai Rabkin2,3, Wei Liu1, Suzhi Li4, Guohua Dong5, Hyeok Yoon6,7, Harold Y. Hwang6,7, Beena Kalisky2,3, and Ekhard K. H. Salje8,†

    • *Contact author: luguangming1990@ytu.edu.cn
    • †Deceased.

    Phys. Rev. B 112, 245403 – Published 1 December, 2025

    DOI: https://doi.org/10.1103/9qkp-g4k6

    Abstract

    Ferroelastic domain walls (DWs) offer a unique platform for engineering dynamic magnetism through controlled symmetry breaking. Here, we demonstrate deterministic magnetic field generation in reconfigurable DW networks using nanocavity-patterned ferroelastic matrices. Atomistic simulations reveal that propagating kinks along polar twin walls induce strain-gradient polarization and displacement current vortices, producing localized magnetic fields (∼10−7–10−6 T) via flexoelectric coupling. These fields exhibit scale-free avalanche dynamics with universal power-law exponents, mirroring mechanical energy release events during kink nucleation and depinning transitions. To overcome intrinsic disorder limitations, we mimic lithographically defined nanocavities that guide orthogonal DW propagation with cycle-to-cycle reproducibility, achieving local field enhancement compared to stochastic networks. Scanning superconducting quantum interference device (SQUID) microscopy on SrTiO3 detects out-of-plane magnetic signatures (∼10−7 T) persisting for milliseconds, quantitatively matching simulations and indicating extended lifetimes. Crucially, kink velocity-dependent dynamic magnetism is established through synchronized magnetic and energy jerk profiles, resolving the atomic-scale mechanism linking DW motion to emergent magnetism. This work establishes a multiscale framework for defect-engineered ferroelastic materials, bridging atomic-scale polarization dynamics, mesoscale DW circuit design, and macroscale nonvolatile memory functionality. By decoupling magnetic responses from intrinsic disorder, our approach advances ferroelastic DW networks toward practical applications in strain-programmable spintronics and ultrahigh-density racetrack memories.

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