Ultrathin (<10 nm) Electrochemical Random‐Access Memory that Overcomes the Tradeoff between Robust Weight Update and Speed in Neuromorphic Systems

Electrochemical random‐access memory (ECRAM) devices are a promising candidate for neuromorphic computing, as they mimic synaptic functions by modulating conductance through ion migration. However, the use of a thick electrolyte layer (>40 nm) in conventional ECRAMs leads to an unavoidable tradeoff between synaptic weight updates and operating speed. To address this problem, a Cu‐based ultrathin ECRAM (UT‐ECRAM) that uses a single 5 nm HfO x active layer and a ≈1.2 nm AlO x liner is designed. The highly efficient gate‐tunable fast Cu‐ion transport in the AlO x /HfO x UT‐ECRAM enables 1) near‐ideal linearity in weight updates (0.45) even achieved with a pulse width ( t w ) of 50 μs, 2) dynamic multilevel retention of 10 4 s, and 3) reliable cycling endurance of 10 4 cycles. A numerical analysis based on device scaling quantitatively reveals that a relatively high concentration of field‐driven Cu ions (≈10 20 cm −3 ) contributes to each synaptic weight update per gate voltage ( V G ) pulse in the UT‐ECRAM without becoming deactivated by traversing thicker layers. This improved gate sensitivity can ultimately overcome the linearity and the ratio/speed tradeoff relationships, paving the way for robust neuromorphic synaptic units.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2025-06-16
DOI
https://doi.org/10.1002/aisy.202500416
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Ultrathin (<10 nm) Electrochemical Random‐Access Memory that Overcomes the Tradeoff between Robust Weight Update and Speed in Neuromorphic Systems

Seonuk Jeon, Jiyong Woo, Nir Tessler, Seokjae Lim
Advanced Intelligent Systems
Advanced Memory and Neural Computing
article

Ultrathin (<10 nm) Electrochemical Random‐Access Memory that Overcomes the Tradeoff between Robust Weight Update and Speed in Neuromorphic Systems

Seonuk Jeon, Jiyong Woo, Nir Tessler, Seokjae Lim
article en

Abstract

Electrochemical random‐access memory (ECRAM) devices are a promising candidate for neuromorphic computing, as they mimic synaptic functions by modulating conductance through ion migration. However, the use of a thick electrolyte layer (&gt;40 nm) in conventional ECRAMs leads to an unavoidable tradeoff between synaptic weight updates and operating speed. To address this problem, a Cu‐based ultrathin ECRAM (UT‐ECRAM) that uses a single 5 nm HfO x active layer and a ≈1.2 nm AlO x liner is designed. The highly efficient gate‐tunable fast Cu‐ion transport in the AlO x /HfO x UT‐ECRAM enables 1) near‐ideal linearity in weight updates (0.45) even achieved with a pulse width ( t w ) of 50 μs, 2) dynamic multilevel retention of 10 4 s, and 3) reliable cycling endurance of 10 4 cycles. A numerical analysis based on device scaling quantitatively reveals that a relatively high concentration of field‐driven Cu ions (≈10 20 cm −3 ) contributes to each synaptic weight update per gate voltage ( V G ) pulse in the UT‐ECRAM without becoming deactivated by traversing thicker layers. This improved gate sensitivity can ultimately overcome the linearity and the ratio/speed tradeoff relationships, paving the way for robust neuromorphic synaptic units.

Advanced Intelligent SystemsVol. 7(8)
Technion – Israel Institute of Technology (IL), Kyungpook National University (KR), Gumi Electronics & Information Technology Research Institute (South Korea) (KR)
Ministry of Trade, Industry and Energy, Iran Telecommunication Research Center, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion
Openalex Percentile: Top 88%
Advanced Memory and Neural Computing
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