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 (>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 HfOx active layer and a ≈1.2 nm AlOx liner is designed. The highly efficient gate-tunable fast Cu-ion transport in the AlOx/HfOx UT-ECRAM enables 1) near-ideal linearity in weight updates (0.45) even achieved with a pulse width (tw) of 50 μs, 2) dynamic multilevel retention of 104 s, and 3) reliable cycling endurance of 104 cycles. A numerical analysis based on device scaling quantitatively reveals that a relatively high concentration of field-driven Cu ions (≈1020 cm−3) contributes to each synaptic weight update per gate voltage (VG) 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.
Original language | English |
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Journal | Advanced Intelligent Systems |
DOIs | |
State | Accepted/In press - 2025 |
Keywords
- electrochemical random-access memory
- neuromorphic computing system
- numerical modeling and analysis
- synaptic device characteristics
- synaptic linearity and symmetry
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
- Mechanical Engineering
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Materials Science (miscellaneous)