Ferroelectric Domain Walls Enable Near-Infrared Visual Synapses in Wide-Bandgap 2D In-Plane Ferroelectric NbOCl <sub>2</sub> -Based Heterojunctions
Ferroelectric domain walls endow ferroelectric materials with sub-bandgap near-infrared (NIR) light absorption properties, holding broad prospects for the development of infrared visual synaptic functions. Their stable behavior in two-dimensional (2D) in-plane ferroelectric materials under external out-of-plane electric fields lays a material foundation for building 2D NIR visual synapses─additionally, the in-plane polarization characteristic further enables optical polarization-sensitive characteristics. Herein, we fabricate a multilayer graphene (Gr)/NbOCl 2 /Gr heterojunction using a wide-bandgap 2D in-plane ferroelectric material and exploit the NIR light absorption properties of ferroelectric domain walls to achieve NIR visual synaptic functions at ultralow voltage. We investigated the heterojunction’s responses to external bias, pulse frequency, and pulse intensity in the 808 nm–2200 nm wavelength range, along with its paired-pulse facilitation/depression (PPF/PPD) and multipulse characteristics. Specifically, the heterojunction can implement synaptic functions at 1 mV, with a single-pulse energy consumption as low as 8.74 fJ, and achieves nearly symmetric PPF/PPD characteristics under positive/negative voltages. Notably, the heterojunction shows excellent optical polarization sensitivity, with a polarization ratio up to 9.12 under 1064 nm light illumination. This work offers key technical and theoretical support for advancing high-performance 2D NIR polarization-sensitive visual synapses and accelerates the application of ferroelectric domain wall materials in next-generation visual neuromorphic computing.
Authors
- Jun Fang (ORCID: https://orcid.org/0000-0003-4357-1869)
- Pengfei Hou (ORCID: https://orcid.org/0000-0003-3005-5953)
- Xianjun Zhang (ORCID: https://orcid.org/0000-0003-3554-780X)
Institutions
- Education Department of Hunan Province (CN)
- Xiangtan University (CN)
Publication Details
- Journal
- ACS Applied Materials & Interfaces
- Published
- 2026-06-26
- DOI
- https://doi.org/10.1021/acsami.6c04118
- 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 Program of Hunan Province