Hysteresis Inversion Driven by Polar‐Order Competition in van der Waals Ferrielectric
ABSTRACT Emerging artificial intelligence paradigms increasingly rely on hardware that can dynamically adapt to surging computational workloads, yet present memristive technology remains fundamentally constrained by the fixed polarity of the device, meaning that its directionality for electrical response is unchangeable once integrated into a circuit. Consequently, a single device is locked into a specific operating mode, unable to achieve the flexible reconfiguration required for complex neural networks. Here we introduce a new device concept, a “polarity‐reconfigurable memristor” capable of breaking this constraint by exploiting the complex polar‐order competition in the van der Waals ferrielectric CuCrP 2 S 6 . By dynamically tuning the balance among antiferroelectric (AFE), ferrielectric (FiE), and ferroelectric (FE) states near the phase boundary, the device reversibly inverts its resistive hysteresis, switching between clockwise (CW) and counter‐clockwise (CCW) modes. This reversal allows the same device to alternate between potentiation‐ and depression‐type synaptic plasticity. These results establish polar‐order competition as an effective route to achieve intrinsic polarity reconfigurability for memory and neuromorphic hardware.
Authors
- Man Yang (ORCID: https://orcid.org/0000-0003-0336-374X)
- Shijie Xu (ORCID: https://orcid.org/0000-0003-2882-1065)
- Jingkai Xu (ORCID: https://orcid.org/0000-0002-7545-3608)
- Hanin Algaidi (ORCID: https://orcid.org/0000-0002-5159-8917)
- Xiang Lv (ORCID: https://orcid.org/0000-0001-6101-7568)
- Mohamed Nejib Hedhili (ORCID: https://orcid.org/0000-0002-3624-036X)
- Youyou Yuan (ORCID: https://orcid.org/0009-0002-0875-1215)
- Xixiang Zhang (ORCID: https://orcid.org/0000-0002-3478-6414)
- Hanguang Liao (ORCID: https://orcid.org/0000-0001-6480-1286)
- Yuan Yan (ORCID: https://orcid.org/0000-0002-8987-813X)
- Yinchang Ma (ORCID: https://orcid.org/0000-0002-5201-6448)
- Chuanhui Gong
- Aseel Alslbi (ORCID: https://orcid.org/0009-0002-5374-5025)
- Tao Yang (ORCID: https://orcid.org/0009-0005-1661-6613)
- Bin He (ORCID: https://orcid.org/0009-0009-6557-2492)
- Hao Li (ORCID: https://orcid.org/0009-0009-4193-2449)
Institutions
- The University of Melbourne (AU)
- Sichuan University (CN)
- Islamic University of Madinah (SA)
- King Abdullah University of Science and Technology (SA)
Publication Details
- Journal
- Advanced Materials
- Published
- 2026-07-17
- DOI
- https://doi.org/10.1002/adma.74102
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- King Abdullah University of Science and Technology