five

CMOS-compatible 2D semiconductor-nitride ferroelectric based optoelectronic memristive transistors for neuromorphic sensory computing and optical decoding

收藏
中国科学数据2026-03-31 更新2026-04-25 收录
下载链接:
https://www.sciengine.com/AA/doi/10.1016/j.scib.2025.10.010
下载链接
链接失效反馈
官方服务:
资源简介:
Optoelectronic memristive devices that enable neuromorphic sensory computing with integrated sensing, memory and processing functionalities, have been identified as a promising element for next-generation artificial vision systems. However, the optoelectronic memristive dynamics of these devices are largely based on engineered structures and/or innovative functional nanomaterials, presenting critical challenges for their silicon complementary metal-oxide-semiconductor (CMOS) technology compatibility at a scalable application perspective. Here we demonstrate a CMOS-compatible optoelectronic memristive device based on the aluminium scandium nitride (AlScN) ferroelectric/two-dimensional (2D) semiconductor heterostructure enabled ferroelectric field-effect transistor (FeFET). We show that such FeFETs can be fabricated under the back-end-of-line (BEOL) thermal budget and exhibit non-volatile electronic memory properties. Harnessing the light-induced ferroelectric domain reconfiguration in the AlScN layer, these devices offer light-tunable short- and long-term memristive properties, directly linking light stimulation history to electronic dynamics. Such a working principle enables rich optoelectronic synaptic functions and the implementation of the psychological human visual memory model, offering a critical demonstration for optical neuromorphic sensory computing. Furthermore, a linear and non-volatile dependence of the photoresponse current on the light intensity is exploited for the optical information decoding. Our results mark new opportunities for CMOS-compatible optoelectronic memristive devices as the hardware basis of next-generation neuromorphic vision architectures.
创建时间:
2026-03-31
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作