FeRAM Capacitor with Novel Low-Power, Non-destructive and High Endurance Read operation for High-density Embedded Memory

For the first time, advanced CMOS compatible HZO-based FeRAM trench capacitors, are demonstrated with non-destructive read (R) endurance <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&gt; 10^{4}$</tex> cycles at elevated temperature (85°C) after single write (W). This ensures continuous R between refresh cycles and eliminates rewrite after every R, leading to further reduction in both latency and energy of R operation, over FeRAM with destructive R. Compared to published non-destructive read operation (NDRO) scheme, a higher R bias of 0.8V is used to obtain <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&gt; 28\times$</tex> memory window (MW) boost [1], [2], which originates from high-charge response from domain walls (DWs) due to partial polarization switching. Furthermore, 5yr lifetime at elevated temperature is extrapolated under R/W-intensive NDRO, while low-frequency W access (or refresh) is identified as the worst-case scenario. Finally, a tight distribution of functional bits with NDRO in FeRAM capacitor array across 300mm wafer is demonstrated, showing that integrating low-voltage FE capacitors with proposed novel NDRO scheme has great performance potential for next-generation low-power, high-speed, dense embedded memory.

Authors

Institutions

Publication Details

Published
2025-06-08
DOI
https://doi.org/10.23919/vlsitechnologyandcir65189.2025.11075099
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FeRAM Capacitor with Novel Low-Power, Non-destructive and High Endurance Read operation for High-density Embedded Memory

Uygar E. Avci, B. Krist, Gyu-Yeong Choe, C. Neumann et al.
3 citations
Advanced Memory and Neural Computing
2.19
article

FeRAM Capacitor with Novel Low-Power, Non-destructive and High Endurance Read operation for High-density Embedded Memory

Uygar E. Avci, B. Krist, Gyu-Yeong Choe, C. Neumann, J. Kavalieros, Bernal Granados Alpizar, Shahbaz Ahmed Siddiqui, Sou-Chi Chang, Chih‐Chien Lin, M. Metz, B. Bangalore Rajeeva, A. Augustus
article en
3 citations

Abstract

For the first time, advanced CMOS compatible HZO-based FeRAM trench capacitors, are demonstrated with non-destructive read (R) endurance <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&gt; 10^{4}$</tex> cycles at elevated temperature (85°C) after single write (W). This ensures continuous R between refresh cycles and eliminates rewrite after every R, leading to further reduction in both latency and energy of R operation, over FeRAM with destructive R. Compared to published non-destructive read operation (NDRO) scheme, a higher R bias of 0.8V is used to obtain <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&gt; 28\times$</tex> memory window (MW) boost [1], [2], which originates from high-charge response from domain walls (DWs) due to partial polarization switching. Furthermore, 5yr lifetime at elevated temperature is extrapolated under R/W-intensive NDRO, while low-frequency W access (or refresh) is identified as the worst-case scenario. Finally, a tight distribution of functional bits with NDRO in FeRAM capacitor array across 300mm wafer is demonstrated, showing that integrating low-voltage FE capacitors with proposed novel NDRO scheme has great performance potential for next-generation low-power, high-speed, dense embedded memory.

Intel (United States) (US)
Affordable and clean energy
Openalex Percentile: Top 11%
Advanced Memory and Neural Computing
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.