Advancing Toward 4F² 1T1R RRAM With Local NAND-gate and Isolation Scheme
In this work, we introduce an innovative NAND-gate array structure that optimizes cell density through local series connection. By implementing a p-well isolation in combination with the substrate bias effect, we effectively mitigate the operating voltage constraints on series-connected cells. This design ensures symmetric read operations and maintains uniform read margins among cells in the NAND-gate array, achieving a record cell size of 0.045 μm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><roman>2</roman></sup> at the 40-nm technology node. This design demonstrates robust reliability with an endurance of 100k cycles and a ten-year retention at 150 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∘</sup>C. Moreover, the implementation of deep trench isolation (DTI) technology enables further density enhancements, with a projected cell area of 0.0255 μm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><roman>2</roman></sup> at the 28-nm technology node. This approach offers significant advancements in resistive random access memory (RRAM) density, making it highly suitable for high-density memory and computing applications.
Authors
- Qishen Wang (ORCID: https://orcid.org/0000-0002-4013-6426)
- Yimao Cai (ORCID: https://orcid.org/0000-0002-6854-8211)
- Shengyu Bao (ORCID: https://orcid.org/0000-0001-7848-5958)
- Lin Bao (ORCID: https://orcid.org/0000-0002-3146-6124)
- Zongwei Wang (ORCID: https://orcid.org/0000-0001-6297-2700)
- Linbo Shan
- Yuhang Yang (ORCID: https://orcid.org/0000-0002-5293-9728)
- Ru Huang
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Peking University (CN)
Publication Details
- Journal
- IEEE Transactions on Electron Devices
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1109/ted.2025.3554165
- Citations
- 4
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- National Natural Science Foundation of China
- Higher Education Discipline Innovation Project
- Beijing Nova Program