Giant Memory Function Based on the Magnetic Field History of Resistive Switching Under a Constant Bias Voltage
Abstract Memristors, which are characterized by their unique input‐voltage‐history‐dependent resistance, have garnered significant attention for the exploration of next‐generation in‐memory computing, reconfigurable logic circuits, and neural networks. Memristors are controlled by the applied input voltage; however, the latent potential of their magnetic field sensitivity for spintronics applications has rarely been explored. In particular, valuable functionalities are expected to be yielded by combining their history dependence and magnetic field response. Here, for the first time, a giant memory function based on the magnetic field history of memristive switching is revealed with an extremely large magnetoresistance ratio of up to 32,900% under a constant bias voltage, using a two‐terminal Ge‐channel device with Fe/MgO electrodes. This behavior is attributed to colossal magnetoresistive switching induced by the d 0 ferromagnetism of Mg vacancies in the MgO layers and impact ionization breakdown in the Ge substrate. These findings may lead to the development of highly sensitive multi‐field sensors, high‐performance magnetic memory, and advanced neuromorphic devices.
Authors
- Yuriko Tadano
- Akira Masago (ORCID: https://orcid.org/0000-0003-3814-2939)
- Tatsuro Endo (ORCID: https://orcid.org/0000-0001-8649-1338)
- Hikari Shinya (ORCID: https://orcid.org/0000-0002-6257-2114)
- Tetsuya Fukushima (ORCID: https://orcid.org/0000-0001-6301-6104)
- Masaaki Tanaka (ORCID: https://orcid.org/0000-0003-3599-663X)
- Takahito Takeda (ORCID: https://orcid.org/0000-0001-8925-8259)
- Shinobu Ohya (ORCID: https://orcid.org/0000-0003-1417-9403)
- Shun Tsuruoka
- Masaya Kaneda
- Hiroshi Katayama‐Yoshida
Institutions
- Hiroshima University (JP)
- Japan Agency for Marine-Earth Science and Technology (JP)
- Tohoku University (JP)
- Spintronics Research Network of Japan (JP)
- National Institute of Advanced Industrial Science and Technology (JP)
- The University of Tokyo (JP)
- The University of Osaka (JP)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-01-10
- DOI
- https://doi.org/10.1002/adfm.202415648
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Japan Society for the Promotion of Science
- Core Research for Evolutional Science and Technology
- Exploratory Research for Advanced Technology