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Memristive Devices Based on Necklace-like Structure Ag@TiO2 Nanowire Networks for Neuromorphic Learning and Reservoir Computing.
- Source :
- ACS Applied Nano Materials; 9/13/2024, Vol. 7 Issue 17, p21018-21025, 8p
- Publication Year :
- 2024
-
Abstract
- Neuromorphic nanowire networks are of broad interest for applications in burgeoning memristive devices and neuromorphic computing areas due to their interesting features such as neural-like topology and nonlinear dynamics. However, the complexity of the neuromorphic nanowire network's behavior and in materia reservoir computing with imperfect device performance still hampers a straight transfer into emerging computing applications. Herein, reliable memristive devices based on unique necklace-like structure Ag@TiO<subscript>2</subscript> nanowire networks are demonstrated for neuromorphic learning and reservoir computing. The memristive devices utilizing necklace-like structure Ag@TiO<subscript>2</subscript> nanowire networks exhibit stable volatile threshold switching characteristics, with a ratio of up to 10<superscript>5</superscript>, low threshold voltage (<1 V), good endurance, and high uniformity. Besides, the devices have been successfully used to emulate diverse functions of synapses by exploiting the Ag filament dynamics within the nanowire network, including short-term plasticity, and transition from short-term plasticity to long-term plasticity. The nanowire networks that offer nonlinear and short-term dynamics are further harnessed to build a reservoir computing system for the waveform classification task, manifesting its great potential for the development of next-generation reservoir hardware. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25740970
- Volume :
- 7
- Issue :
- 17
- Database :
- Complementary Index
- Journal :
- ACS Applied Nano Materials
- Publication Type :
- Academic Journal
- Accession number :
- 179670185
- Full Text :
- https://doi.org/10.1021/acsanm.4c04063