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Updated: Nov 1, 2025
08:07
Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
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12-state multi-level cell storage implemented in a 128 Mb phase change memory chip.
Zhitang Song1, Daolin Cai, Yan Cheng
1State Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Micro-system and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China. ztsong@mail.sim.ac.cn caidl@mail.sim.ac.cn.
Nanoscale
|June 17, 2021
Summary
Carbon-doped Ge2Te2Te5 phase change memory (PCM) chips achieve high endurance and 12 multi-level states. This advancement supports large-scale, energy-efficient neuromorphic computing systems.
Area of Science:
- Materials Science
- Electrical Engineering
- Computer Science
Background:
- Phase Change Memory (PCM) chips are crucial for artificial intelligence applications.
- PCM cells typically feature a TiN bottom electrode, phase change material, and top metal.
- High thermal stability and oxidation resistance are key for electrode durability.
Purpose of the Study:
- To enhance the endurance and conductivity-drift of 128 Mb PCM chips.
- To improve the performance of carbon-doped Ge2Te2Te5 (CGST) phase change materials.
- To advance the development of large-scale, energy-efficient neuromorphic computing systems.
Main Methods:
- Utilizing TiN films prepared by atomic layer deposition with a WN coating for electrode stability.
- Incorporating carbon into Ge2Te2Te5 (GST) to form CGST, refining grain size and enhancing atomic migration barriers.
- Analyzing the effects of carbon confinement on composition segregation and atomic relaxation during Reset/Set operations.
Main Results:
- Achieved high endurance of the TiN electrode over 10^11 cycles with WN coating.
- CGST material demonstrated refined grain size and suppressed composition segregation.
- The 128 Mb PCM chip reached stability over 5 x 10^8 cycles with 12 multi-level stable states.
Conclusions:
- The developed CGST material and TiN electrode structure significantly enhance PCM chip endurance and stability.
- This research provides a pathway for creating large-scale, energy-efficient neuromorphic computing hardware.
- Optimized PCM materials are essential for next-generation AI and computing systems.
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