Electrically Tunable WSe <sub>2</sub> /α-In <sub>2</sub> Se <sub>3</sub> van der Waals Ferroelectric Heterostructure for Reconfigurable Photodetection and Neuromorphic Computing

The growing demand for compact and energy-efficient hardware in artificial intelligence and edge computing calls for multifunctional electronic systems beyond conventional architectures. van der Waals (vdW) ferroelectric semiconductors, which couple switchable polarization with tunable carrier transport, offer a promising avenue for reconfigurable electronics. Here, we demonstrate a WSe<sub>2</sub>/α-In<sub>2</sub>Se<sub>3</sub> vdW heterostructure that enables dynamic and nonvolatile reconfiguration of electrical functionality within a single device. Through bias-mediated control of ferroelectric polarization and the associated interfacial carrier redistribution, the heterostructure exhibits dual-mode operation: as a high-performance photodetector with a detectivity exceeding 10<sup>12</sup> Jones and as a nonvolatile memory element. Furthermore, the device emulates biological synaptic plasticity, supporting the implementation of artificial neural networks (ANNs) that achieve 96.76% recognition accuracy on the MNIST data set. This work establishes a versatile and electrically reconfigurable platform based on vdW ferroelectric heterojunctions, enabling dual-mode operation for photodetection and neuromorphic computing.

Authors

Institutions

Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2026-02-23
DOI
https://doi.org/10.1021/acsami.5c24824
Primary Topic
2D Materials and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Electrically Tunable WSe 2 /α-In 2 Se 3 van der Waals Ferroelectric Heterostructure for Reconfigurable Photodetection and Neuromorphic Computing

Jie Chen, Yinfeng Long, Mao Chen, Jinjian Yan et al.
ACS Applied Materials & Interfaces
2D Materials and Applications
article

Electrically Tunable WSe 2 /α-In 2 Se 3 van der Waals Ferroelectric Heterostructure for Reconfigurable Photodetection and Neuromorphic Computing

Jie Chen, Yinfeng Long, Mao Chen, Jinjian Yan, Y.B. Chen, Linlin Wang, Xinwei Zhang, Jinxiu Zhao, Siwen Zhang, Mengwei Si, Du Xiang, Yufeng Ning, Kai Liu, Han Chen, Yishu Zhang, Liang Liu
article en

Abstract

The growing demand for compact and energy-efficient hardware in artificial intelligence and edge computing calls for multifunctional electronic systems beyond conventional architectures. van der Waals (vdW) ferroelectric semiconductors, which couple switchable polarization with tunable carrier transport, offer a promising avenue for reconfigurable electronics. Here, we demonstrate a WSe<sub>2</sub>/α-In<sub>2</sub>Se<sub>3</sub> vdW heterostructure that enables dynamic and nonvolatile reconfiguration of electrical functionality within a single device. Through bias-mediated control of ferroelectric polarization and the associated interfacial carrier redistribution, the heterostructure exhibits dual-mode operation: as a high-performance photodetector with a detectivity exceeding 10<sup>12</sup> Jones and as a nonvolatile memory element. Furthermore, the device emulates biological synaptic plasticity, supporting the implementation of artificial neural networks (ANNs) that achieve 96.76% recognition accuracy on the MNIST data set. This work establishes a versatile and electrically reconfigurable platform based on vdW ferroelectric heterojunctions, enabling dual-mode operation for photodetection and neuromorphic computing.

ACS Applied Materials & InterfacesVol. 18(8)
Zhejiang University of Science and Technology (CN), Shanghai Jiao Tong University (CN), Xiamen University (CN), Fudan University (CN), Integrated Optical Circuit Consultants (United States) (US), CHI Systems (United States) (US), Zhejiang University (CN)
Affordable and clean energy
Openalex Percentile: Top 48%
2D Materials and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.