Publication date: 15th December 2025
Magneto-ionic materials, which enable non-volatile control of magnetism through voltage-driven ion migration, are emerging as promising candidates for neuromorphic computing [1, 2]. Unlike conventional memristors, these systems typically operate through dual-actuation protocols, involving both electric and magnetic fields, thus providing a broader range of functional capabilities. The utilization of voltage rather than electric currents significantly reduces Joule heating effects and enhances energy efficiency. Remarkably, voltage-triggered ion motion can induce the formation of ferromagnetic regions within films that are initially paramagnetic. However, the general need for external magnetic fields to control the orientation of the voltage-induced ferromagnetic phases remains a key limitation, undermining the full energy-saving potential of these systems. In this work, we present a magneto-ionic strategy in CoFeN that fully decouples the electric and magnetic field actuation requirements. First, we apply magnetic field to fix a pre-defined direction of the magnetization in the magneto-ionically generated ferromagnetic phase. Then, once the magnetic field is removed, we demonstrate the modulation of magnetic remanence solely with the applied voltage. Such tuning of the remanent magnetization state is enabled by the voltage-controlled propagation of a planar N³⁻ ion migration [3], along with the ferromagnetic exchange interactions between pre-existing and newly generated CoFe magnetic regions. The system exhibits behaviors reminiscent of neuromorphic-inspired functionalities, such as synaptic potentiation and depression [4], while also showing a cumulative, voltage-driven increase in magnetization in the absence of a magnetic field. Once the magnetic field is switched off, synaptic weight remains influenced by the sample’s magnetic and electric history. By eliminating the need for magnetic fields, our approach contributes to reduce energy consumption, decreasing the amount of energy spent typically using these systems by several orders of magnitude, thereby offering a more efficient pathway for brain-inspired magneto-ionic devices.
Financial support from the European Research Council (2021-ERC-Advanced ‘REMINDS’ no. 101054687, and 2024-ERC-Proof of Concept ‘SECURE-FLEXIMAG’ Grant no. 101204328), the Generalitat de Catalunya (2021-SGR-00651) and the Spanish Agencia Estatal de Investigación (PID2020-116844RB-C21 and TED2021-130453B-C22) is acknoweldged. Authors acknowledge the use of instrumentation financed through Grant IU16-014206 (METCAM-FIB) to ICN2 funded by the European Union through the European Regional Development Fund (ERDF) with the support of the Ministry of Research and Universities, Generalitat de Catalunya. ICN2 is funded by the CERCA program/Generalitat de Catalunya and is also supported by the Severo Ochoa Centres of Excellence program, Grant CEX2021-001214-S, grant funded by MCIU/AEI/10.13039/501100011033. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
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