Investigation and Application of Two-Level Random Telegraph Noise in Ti/HfO <i> <sub>x</sub> </i> /TiN RRAM Using 3-D Multiphysics Modeling
Random telegraph noise (RTN) in the read current of a HfO<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>-based resistive random access memory (RRAM) exhibits complex dynamic characteristics of oxygen vacancies (Vos), ions, and charge carriers. In this work, a simulation framework for RTN is proposed. This framework is based on the multiphonon trap-assisted tunneling (MPTAT) model, and is supplemented by first-principle simulations. It is employed to investigate the underlying physical properties of RRAM through the cautious verification by comprehensive measurements. It confirms that the polaron band of Vo is the main reason to produce the RTN of RRAM, and the observed two-level RTN is attributed to the transition of Vo between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V} ^{{0}}$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V} ^{{1}-}$</tex-math> </inline-formula>. By leveraging the RTN, the location of the conductive filament (CF) rupture can be identified without compromising the device integrity. This work opens a new avenue for exploring the reset state and the Vo-based CFs in the oxide RRAM.
Authors
- Y. P. Zhong (ORCID: https://orcid.org/0009-0007-0676-8378)
- Ming Xu (ORCID: https://orcid.org/0000-0002-2730-283X)
- Kan‐Hao Xue (ORCID: https://orcid.org/0000-0002-2894-7912)
- Xingsheng Wang (ORCID: https://orcid.org/0000-0001-8335-2033)
- Xiangshui Miao (ORCID: https://orcid.org/0000-0002-5621-5495)
- Zijian Zhou (ORCID: https://orcid.org/0000-0001-7401-7612)
- Pan Liu
- Qundao Xu
- Zifei Cai (ORCID: https://orcid.org/0009-0007-1606-7428)
- Dejiang Mu (ORCID: https://orcid.org/0009-0009-3400-4839)
Institutions
- Wuhan National Laboratory for Optoelectronics (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Electron Devices
- Published
- 2025-10-13
- DOI
- https://doi.org/10.1109/ted.2025.3613477
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00