Issue 9, 2023

Introduction of defects in hexagonal boron nitride for vacancy-based 2D memristors

Abstract

Two-dimensional (2D) materials have become potential resistive switching (RS) layers to prepare emerging non-volatile memristors. The atomically thin thickness and the highly controllable defect density contribute to the construction of ultimately scaled memory cells with stable switching behaviors. Although the conductive bridge random-access memory based on 2D hexagonal boron nitride has been widely studied, the realization of RS completely relying on vacancies in 2D materials has performance superiority. Here, we synthesize carbon-doped h-BN (C-h-BN) with a certain number of defects by controlling the weight percentage of carbon powder in the source. These defects can form a vacancy-based conductive filament under an applied electric field. The memristor displays bipolar non-volatile memory with a low SET voltage of 0.85 V and shows a long retention time of up to 104 s at 120 °C. The response times of the SET and RESET process are less than 80 ns and 240 ns, respectively. The current mapping by conductive atomic force microscopy demonstrates the electric-field-induced current tunneling from defective sites of the C-h-BN flake, revealing the defect-based RS in the C-h-BN memristor. Moreover, C-h-BN with excellent flexibility can be applied to wearable devices, maintaining stable RS performance in a variety of bending environments and after multiple bending cycles. The vacancy-based 2D memristor provides a new strategy for developing ultra-scaled memory units with high controllability.

Graphical abstract: Introduction of defects in hexagonal boron nitride for vacancy-based 2D memristors

Supplementary files

Article information

Article type
Paper
Submitted
26 12 2022
Accepted
21 1 2023
First published
09 2 2023

Nanoscale, 2023,15, 4309-4316

Introduction of defects in hexagonal boron nitride for vacancy-based 2D memristors

H. Chen, Y. Kang, D. Pu, M. Tian, N. Wan, Y. Xu, B. Yu, W. Jie and Y. Zhao, Nanoscale, 2023, 15, 4309 DOI: 10.1039/D2NR07234C

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