journal article·2026-04-22

Reliable WSe 2 Memristors Enabled by van der Waals Electrode Integration for Advanced Reservoir Computing and Nociceptive Receptors

Yujie Bai, Yuhao Kong, Siling Liu, Mouyuan Liu, Shiyu Chen, Huifang Ma, Xidong Duan, Weiyou Yang, Jianhong Yang, Xingan Jiang, Xiangdong Yang

ACS Applied Materials & Interfaces· Volume 18· Issue 15
Publisher page

Abstract

Memristors based on two-dimensional (2D) materials are pivotal for next-generation neuromorphic hardware, owing to their high integration density, flexibility, excellent electrical properties, and advantage in neuromorphic computing. However, practical deployment is often thwarted by substantial switching variability and limited endurance, primarily arising from uncontrollable interfacial damage and energetic metal-ion diffusion during conventional electrode deposition. Herein, high-quality monolayer WSe2 single crystals are synthesized via bidirectional-flow physical vapor deposition (PVD). Subsequently, Ag/WSe2/Ag memristors are constructed using a damage-free van der Waals (vdW) metal integration process to preserve the intrinsic lattice integrity. The fabricated vdW devices exhibit remarkable switching consistency with a coefficient of variation (Cv) of only 2.62%, a high memory window exceeding 106, a low High Resistance State (HRS) current below 10 pA, and robust endurance exceeding 105 cycles. Beyond emulating fundamental synaptic behaviors, the devices achieve high-fidelity recognition accuracies of 99.51% for the Modified National Institute of Standards and Technology (MNIST) and 95.39% for the Fashion-MNIST data sets, respectively. Furthermore, biorealistic nociceptive functionalities, such as threshold firing and sensitization, are successfully emulated. This work demonstrates that vdW electrode integration is a robust paradigm for enhancing the reliability of 2D memristors, paving the way for robust high-performance neuromorphic intelligence hardware.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · 2D Materials and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Physical Science and Technology

Lanzhou University

Institute of Micro/Nano Materials and Devices

Ningbo University of Technology

School of Flexible Electronics (Future Technologies) & Institute of Advanced Materials (IAM), Jiangsu National Synergetic Innovation Center for Advanced Materials

Nanjing Tech University

Hunan Provincial Key Laboratory of Two-Dimensional Materials, State Key Laboratory of Chemo and Biosensing, College of Chemistry and Chemical Engineering

Hunan University

College of Integrated Circuit Science and Engineering

Nanjing University of Posts and Telecommunications

State Key Laboratory of Materials for Integrated Circuits, Shanghai Institute of Microsystem and Information Technology

Chinese Academy of Sciences

Funding

Natural Science Foundation of Ningbo Municipality · China Association for Science and Technology · National Natural Science Foundation of China · Ningbo Yongjiang Talent Introduction Programme · State Key Laboratory of Materials for Integrated Circuits

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