Low-Leakage Volatile Threshold Switching in Gr/CIPS/h-BN/Au van der Waals Heterostructure via Atomic-Scale Geometric Confinement

Abstract Volatile Threshold Switching (TS) devices are critical selector components for suppressing sneak path currents in high-density crossbar arrays. However, active-metal-based TS devices often face the challenge of stochastic conductive filament overgrowth. In this work, we report a high-performance TS device based on a Graphene/CuInP₂S₆/h-BN/Au van der Waals heterostructure. By utilizing hexagonal Boron Nitride (h-BN) as an atomic-scale ion sieve, we achieve atomic-scale geometric confinement of Cu filament growth. The device exhibits excellent unipolar switching characteristics, featuring a high on/off ratio (>10 5 ), ultra-low off-state leakage current (~pA), and a steep subthreshold swing (<15 mV/dec). Mechanistic investigations reveal that the h-BN layer confines the filaments to the atomic scale, causing the metastable filaments to spontaneously rupture upon bias removal due to Rayleigh instability, thereby enabling rapid self-resetting. This interface engineering strategy effectively addresses the filament overgrowth issue, providing a reliable solution for low-power neuromorphic computing hardware.

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Publication Details

Journal
Nanotechnology
Published
2026-05-28
DOI
https://doi.org/10.1088/1361-6528/ae7427
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Low-Leakage Volatile Threshold Switching in Gr/CIPS/h-BN/Au van der Waals Heterostructure via Atomic-Scale Geometric Confinement

Cong Yan, Xiaoli Yang, Chen ZHONG, Yourui An et al.
Nanotechnology
Advanced Memory and Neural Computing
article

Low-Leakage Volatile Threshold Switching in Gr/CIPS/h-BN/Au van der Waals Heterostructure via Atomic-Scale Geometric Confinement

Cong Yan, Xiaoli Yang, Chen ZHONG, Yourui An, Zhenhao Wen, Shupeng Chen, Shulong Wang, Hongxia Liu
article en

Abstract

Abstract Volatile Threshold Switching (TS) devices are critical selector components for suppressing sneak path currents in high-density crossbar arrays. However, active-metal-based TS devices often face the challenge of stochastic conductive filament overgrowth. In this work, we report a high-performance TS device based on a Graphene/CuInP₂S₆/h-BN/Au van der Waals heterostructure. By utilizing hexagonal Boron Nitride (h-BN) as an atomic-scale ion sieve, we achieve atomic-scale geometric confinement of Cu filament growth. The device exhibits excellent unipolar switching characteristics, featuring a high on/off ratio (>10 5 ), ultra-low off-state leakage current (~pA), and a steep subthreshold swing (<15 mV/dec). Mechanistic investigations reveal that the h-BN layer confines the filaments to the atomic scale, causing the metastable filaments to spontaneously rupture upon bias removal due to Rayleigh instability, thereby enabling rapid self-resetting. This interface engineering strategy effectively addresses the filament overgrowth issue, providing a reliable solution for low-power neuromorphic computing hardware.

Nanotechnology
Chongqing University of Posts and Telecommunications (CN), Xidian University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 9%
Advanced Memory and Neural Computing
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