Voltage-driven fluorine motion for novel organic spintronic memristor
Integrating tunneling magnetoresistance (TMR) effect in memristors is a long-term aspiration because it allows to realize multifunctional devices, such as multi-state memory and tunable plasticity for synaptic function. However, the reported TMR in different multiferroic tunnel junctions is limited to 100%. Here, we demonstrate a giant TMR of -266% in La0.6Sr0.4MnO3(LSMO)/poly(vinylidene fluoride)(PVDF)/Co memristor with thin organic PVDF barrier. Different from the ferroelectricity-based memristors, we discover that the voltage-driven F motion in the junction generates a huge reversible resistivity change up to 106 % with ns timescale. The removing F from PVDF layer suppresses the dipole field in the tunneling barrier, thereby significantly enhances the TMR. Furthermore, the TMR can be tuned by different polarizing voltage due to the strong modification of spin-polarization at the LSMO/PVDF interface upon F doping. The combining of high TMR in the organic memristor paves the way to develop high-performance multifunctional devices for storage and neuromorphic applications.
Authors
- Sylvie Migot (ORCID: https://orcid.org/0000-0003-3803-9931)
- Priyanka Tyagi (ORCID: https://orcid.org/0000-0001-7243-1967)
- Abir Nachawaty
- Kevin Dalla Francesca (ORCID: https://orcid.org/0000-0002-2310-7041)
- Antonio Da Costa (ORCID: https://orcid.org/0000-0002-7420-137X)
- Fatima Ibrahim (ORCID: https://orcid.org/0000-0002-7374-6001)
- Jean‐Christophe Le Breton (ORCID: https://orcid.org/0000-0002-2619-0231)
- Thomas Gries (ORCID: https://orcid.org/0000-0002-2480-8333)
- Rachel Desfeux (ORCID: https://orcid.org/0000-0002-0629-3671)
- Arnaud Le Pottier
- Tongxin Chen (ORCID: https://orcid.org/0000-0001-6333-7856)
- Mairbek Chshiev (ORCID: https://orcid.org/0000-0001-9232-7622)
- Xavier Devaux
- Yuan Lü (ORCID: https://orcid.org/0000-0003-3337-8205)
- Chuanchuan Liu
- Philippe Schieffer (ORCID: https://orcid.org/0000-0001-5902-6553)
- Walaa Jahjah
- Laurent Badie (ORCID: https://orcid.org/0009-0009-9689-5606)
- Xiaoguang Li (ORCID: https://orcid.org/0000-0003-4016-4483)
- Yuchen Wang (ORCID: https://orcid.org/0000-0002-0356-8422)
- Anthony Ferri (ORCID: https://orcid.org/0000-0002-9162-2715)
- Ya-Fei Hao
Institutions
- University of Science and Technology of China (CN)
- Centre National de la Recherche Scientifique (FR)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- CEA Grenoble (FR)
- Institut de Physique de Rennes (FR)
- Spintronique et Technologie des Composants (FR)
- Institut Jean Lamour (FR)
- Université d'Artois (FR)
- Université de Rennes (FR)
- Université Grenoble Alpes (FR)
- Université de Lorraine (FR)
Publication Details
- Published
- 2025-09-18
- DOI
- https://doi.org/10.1117/12.3067387
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00