Thinnest Nonvolatile Memory Based on Monolayer h-BN

Xiaohan Wu, Ruijing Ge, Po An Chen, Harry Chou, Zhepeng Zhang, Yanfeng Zhang, Sanjay Banerjee, Meng-Hsueh Chiang, Jack C. Lee, Deji Akinwande

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

2D materials have attracted much interest over the past decade in nanoelectronics. However, it was believed that the atomically thin layered materials are not able to show memristive effect in vertically stacked structure, until the recent discovery of monolayer transition metal dichalcogenide (TMD) atomristors, overcoming the scaling limit to sub-nanometer. Herein, the nonvolatile resistance switching (NVRS) phenomenon in monolayer hexagonal boron nitride (h-BN), a typical 2D insulator, is reported. The h-BN atomristors are studied using different electrodes and structures, featuring forming-free switching in both unipolar and bipolar operations, with large on/off ratio (up to 10 7 ). Moreover, fast switching speed (<15 ns) is demonstrated via pulse operation. Compared with monolayer TMDs, the one-atom-thin h-BN sheet reduces the vertical scaling to ≈0.33 nm, representing a record thickness for memory materials. Simulation results based on ab-initio method reveal that substitution of metal ions into h-BN vacancies during electrical switching is a likely mechanism. The existence of NVRS in monolayer h-BN indicates fruitful interactions between defects, metal ions and interfaces, and can advance emerging applications on ultrathin flexible memory, printed electronics, neuromorphic computing, and radio frequency switches.

Original languageEnglish
Article number1806790
JournalAdvanced Materials
Volume31
Issue number15
DOIs
Publication statusPublished - 2019 Apr 12

Fingerprint

Boron nitride
Monolayers
Data storage equipment
Metal ions
Nanoelectronics
Vacancies
Transition metals
Substitution reactions
Electronic equipment
Switches
boron nitride
Atoms
Defects
Electrodes

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Wu, X., Ge, R., Chen, P. A., Chou, H., Zhang, Z., Zhang, Y., ... Akinwande, D. (2019). Thinnest Nonvolatile Memory Based on Monolayer h-BN. Advanced Materials, 31(15), [1806790]. https://doi.org/10.1002/adma.201806790
Wu, Xiaohan ; Ge, Ruijing ; Chen, Po An ; Chou, Harry ; Zhang, Zhepeng ; Zhang, Yanfeng ; Banerjee, Sanjay ; Chiang, Meng-Hsueh ; Lee, Jack C. ; Akinwande, Deji. / Thinnest Nonvolatile Memory Based on Monolayer h-BN. In: Advanced Materials. 2019 ; Vol. 31, No. 15.
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Wu, X, Ge, R, Chen, PA, Chou, H, Zhang, Z, Zhang, Y, Banerjee, S, Chiang, M-H, Lee, JC & Akinwande, D 2019, 'Thinnest Nonvolatile Memory Based on Monolayer h-BN', Advanced Materials, vol. 31, no. 15, 1806790. https://doi.org/10.1002/adma.201806790

Thinnest Nonvolatile Memory Based on Monolayer h-BN. / Wu, Xiaohan; Ge, Ruijing; Chen, Po An; Chou, Harry; Zhang, Zhepeng; Zhang, Yanfeng; Banerjee, Sanjay; Chiang, Meng-Hsueh; Lee, Jack C.; Akinwande, Deji.

In: Advanced Materials, Vol. 31, No. 15, 1806790, 12.04.2019.

Research output: Contribution to journalArticle

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Wu X, Ge R, Chen PA, Chou H, Zhang Z, Zhang Y et al. Thinnest Nonvolatile Memory Based on Monolayer h-BN. Advanced Materials. 2019 Apr 12;31(15). 1806790. https://doi.org/10.1002/adma.201806790