Interfacial Conductive Pathway Enabled Self-Rectifying Ferroelectric Memristor for Neuromorphic Applications
Integrating nonvolatile resistive switching (RS) and rectification in a single two-terminal device is critical for suppressing sneak currents in high-density crossbar arrays, yet achieving this dual functionality at low operating voltages (<3 V) remains challenging. Here, we fabricate a self-rectifying memristor by blending the ferroelectric polymer P(VDF-TrFE) with the small-molecule semiconductor C8-BTBT. The high crystallinity and carrier mobility of C8-BTBT enable efficient charge injection, realizing a low SET voltage (<2 V) and high ON/OFF ratio (>105). Conductive atomic force microscopy (CAFM) directly visualizes interfacial conductive pathways localized at C8-BTBT/P(VDF-TrFE) heterojunctions, confirming an interface-dominated RS mechanism governed by ferroelectric polarization-modulated Schottky barriers. Furthermore, self-rectifying memristors have emulated key biological synaptic functions, such as paired-pulse facilitation, spiking rate dependent plasticity, spike number dependent plasticity, and spike timing dependent plasticity. Consequently, this work provides a material-level strategy for energy-efficient neuromorphic hardware.
Authors
- X.C. Li (ORCID: https://orcid.org/0000-0002-5981-2762)
- Hongwei Ge (ORCID: https://orcid.org/0000-0002-9761-6623)
- Qingqing Sun (ORCID: https://orcid.org/0000-0002-6019-9272)
- Xiangyuan Li
- Yu Yan
- Xuying Liu (ORCID: https://orcid.org/0000-0001-9190-4651)
- Takeo Minari (ORCID: https://orcid.org/0000-0001-7690-221X)
- Chuan Liu (ORCID: https://orcid.org/0000-0002-0695-592X)
- Junxin Cheng
- Li Zhang
Institutions
- Sun Yat-sen University (CN)
- National Institute for Materials Science (JP)
- Zhengzhou University (CN)
- Centre de Recherches sur les Macromolécules Végétales (FR)
- Key Laboratory of Guangdong Province (CN)
- National College (US)
- Ingenierie des Materiaux polymeres (FR)
- Laboratoire des Biomolécules (FR)
Publication Details
- Journal
- Nano Letters
- Published
- 2026-05-18
- DOI
- https://doi.org/10.1021/acs.nanolett.6c01429
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Science and Technology Department of Henan Province