Resistive-Gate RAM: An 1TnR Architecture Feasible for Scaling Beyond 16nm CMOS Generation

We propose a unique Resistive-gate RAM which is scalable to 16nm FinFET generation and beyond. It consists of an 1TnR RRAM array where a 2D prototype is demonstrated and can be readily extended to 3D. Here, vertical RRAMs are integrated directly on FinFET by a backend process to form a memory core. Results demonstrated that this RG-RRAM can operate below 3V. At chip level, read latency as low as 25ns at 1V can be achieved. Reliability tests also showed that the design exhibits excellent immunity to disturbances during SET, RESET, and READ operations, excellent endurance and excellent data retention. With technology scaling, it is expected to be applicable to various generations of FinFET and nanosheet.

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Publication Details

Published
2025-03-30
DOI
https://doi.org/10.1109/irps48204.2025.10982918
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
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article

Resistive-Gate RAM: An 1TnR Architecture Feasible for Scaling Beyond 16nm CMOS Generation

Chih‐Hsuan Sung, Yi‐Ju Li, Steve S. Chung, Y. R. Liu et al.
Advanced Memory and Neural Computing
article

Resistive-Gate RAM: An 1TnR Architecture Feasible for Scaling Beyond 16nm CMOS Generation

Chih‐Hsuan Sung, Yi‐Ju Li, Steve S. Chung, Y. R. Liu, Yongping Yang, Jingjing Guo, M. J. Huang, P. H. Shih
article en

Abstract

We propose a unique Resistive-gate RAM which is scalable to 16nm FinFET generation and beyond. It consists of an 1TnR RRAM array where a 2D prototype is demonstrated and can be readily extended to 3D. Here, vertical RRAMs are integrated directly on FinFET by a backend process to form a memory core. Results demonstrated that this RG-RRAM can operate below 3V. At chip level, read latency as low as 25ns at 1V can be achieved. Reliability tests also showed that the design exhibits excellent immunity to disturbances during SET, RESET, and READ operations, excellent endurance and excellent data retention. With technology scaling, it is expected to be applicable to various generations of FinFET and nanosheet.

National Yang Ming Chiao Tung University (TW)
Affordable and clean energy
Openalex Percentile: Top 91%
Advanced Memory and Neural Computing
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