4.8 Article

Full-Inorganic Flexible Ag2S Memristor with Interface Resistance-Switching for Energy-Efficient Computing

Journal

ACS APPLIED MATERIALS & INTERFACES
Volume -, Issue -, Pages -

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsami.2c11183

Keywords

flexible memristor; Ag2S; interface resistance-switching; switching energy; energy-efficient computing

Funding

  1. National Natural Science Foundation of China (NSFC) [5181101519, 51625205]
  2. Shanghai government [20JC1415100]
  3. Uppsala University, Sweden
  4. Swedish Strategic Research Foundation [SSF FFL15-0174]
  5. Swedish Research Council [VR 2018-06030]
  6. Wallenberg Academy Fellow Program [KAW 2015-0127, 2020-0190]
  7. Swedish Research Council [2018-06030] Funding Source: Swedish Research Council

Ask authors/readers for more resources

This study reports a flexible memristor based on Ag2S with a distinct interface resistance-switching mechanism. Compared to the filamentary mechanism, the interface resistance-switching has lower energy consumption and better stability under bending conditions. Image processing was also demonstrated using this new mechanism, showing significantly lower power consumption compared to the traditional filamentary mechanism.
Flexible memristor-based neural network hardware is capable of implementing parallel computation within the memory units, thus holding great promise for fast and energy-efficient neuromorphic computing in flexible electronics. However, the current flexible memristor (FM) is mostly operated with a filamentary mechanism, which demands large energy consumption in both setting and computing. Herein, we report an Ag2S-based FM working with distinct interface resistance-switching (RS) mechanism. In direct contrast to conventional filamentary memristors, RS in this Ag2S device is facilitated by the space charge-induced Schottky barrier modification at the Ag/A(2)S interface, which can be achieved with the setting voltage below the threshold voltage required for filament formation. The memristor based on interface RS exhibits 105 endurance cycles and 104 s retention under bending condition, and multiple level conductive states with exceptional tunability and stability. Since interface RS does not require the formation of a continuous Ag filament via Ag+ ion reduction, it can achieve an ultralow switching energy of similar to 0.2 fJ. Furthermore, a hardware-based image processing with a software-comparable computing accuracy is demonstrated using the flexible Ag2S memristor array. And the image processing with interface RS indeed consumes 2 orders of magnitude lower power than that with filamentary RS on the same hardware. This study demonstrates a new resistance-switching mechanism for energy-efficient flexible neural network hardware.

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