Anisotropic Optoelectronic Synapses in 2D Nb <sub>2</sub> GeTe <sub>4</sub> for Direction‐Programmable Neuromorphic Perception and Decision‐Making

T Tianle Zeng Z Zishen Zhao K Kun Ye Z Zhipeng Yu J Junxin Yan Y Yuxuan Zeng (Nanofabrication facility, Suzhou Institute of Nano‐Tech and Nano‐Bionics Chinese Academy of Sciences Suzhou China) W Weiming Lv L Lianbo Guo (School of Software Engineering Huazhong University of Science and Technology Wuhan 430074 China) C Chun Zhao A Anmin Nie Z Zhongming Zeng (School of Nano-Tech and Nano-Bionics, University of Science and Technology of China 1 , Hefei 230026,) Z Zhongyuan Liu (Division of Spine Surgery, Department of Orthopaedics, Nanfang Hospital, Southern Medical University)

Abstract

Abstract Neuromorphic computing presents a promising solution for the von Neumann bottleneck, enabling energy‐efficient and intelligent sensing platforms. Although 2D materials are ideal for bioinspired neuromorphic devices, achieving multifunctional synaptic operations with simple configurations and linear weight updates remains challenging. Inspired by biological axons, the in‐plane anisotropy of 2D Nb 2 GeTe 4 is exploited to develop dual electronic‐optical synaptic devices. The device exhibits anisotropic hole mobilities (137.97 cm 2 V −1 s −1 along the a ‐axis and 78.29 cm 2 V −1 s −1 along the b ‐axis) and a wavelength‐dependent photoresponse. This enables directional synaptic plasticity under electrical‐optical co‐stimulation, achieving 98.3% accuracy along the a ‐axis and 88.3% along the b ‐axis in adaptive image processing. A machine vision system with 89.6% object recognition accuracy and an intelligent vehicle navigation platform with 90.2% decision‐making accuracy is also demonstrated. The integration of anisotropic transport and spectrally tunable responses in a single material paves the way for compact neuromorphic hardware with multimodal sensing and parallel processing capabilities. This study advances 2D material‐based neuroelectronics for edge computing, autonomous robotics, and adaptive artificial intelligence systems.

Article Details

Volume / Issue Vol. 38, Issue 1
Published January 01, 2026
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (12)

T

Tianle Zeng

Z

Zishen Zhao

K

Kun Ye

Z

Zhipeng Yu

J

Junxin Yan

Y

Yuxuan Zeng

Nanofabrication facility, Suzhou Institute of Nano‐Tech and Nano‐Bionics Chinese Academy of Sciences Suzhou China

W

Weiming Lv

L

Lianbo Guo

School of Software Engineering Huazhong University of Science and Technology Wuhan 430074 China

C

Chun Zhao

A

Anmin Nie

Z

Zhongming Zeng

School of Nano-Tech and Nano-Bionics, University of Science and Technology of China 1 , Hefei 230026,

Z

Zhongyuan Liu

Division of Spine Surgery, Department of Orthopaedics, Nanfang Hospital, Southern Medical University