摘要
Emerging nanoscale devices, including memristors, have been extensively studied to implement biological synaptic functions such as learning and plasticity, which are the fundamental building blocks of brain-inspired neuromorphic computing. The memristor with analog switching ability exhibits linear tuning of weight during neural network training is a desirable synaptic device behavior. The importance of inserting a HfOx sandwiched layer in a TaOx/HfOx/TaOx memristor is to achieve analog set/reset operation along with improved spatial/temporal switching uniformity. The optimal resistive switching (RS) behavior can be attributed to asymmetric oxygen vacancy distribution in the stacked structure leading to the formation of an hourglass-shaped conductive filament. Furthermore, confining filament formation/rapture in the narrow fixed region displays superior endurance characteristics (dc cycles >2000 and ac cycles > 106) and uniform resistive switching with the set (reset) voltage variation constrained to 1.8 (2.9) %. Paired-pulse facilitation (PPF), a form of short-term synaptic plasticity is stimulated to replicate bio-synapse behavior. The stable long-term potentiation (LTP) and depression (LTD) behavior for more than 1000 epochs (>105 pulses) with excellent symmetry and linearity is achieved with 50 ns voltage pulse stimulation. The pattern recognition accuracy of 93% was achieved for an image of size 10 × 10 pixels after 13 epochs by deploying 100 synapses in Hopfield Neural Network (HNN) simulation. This comprehensive study demonstrates that the HfOx-inserted TaOx memristor has tremendous potential for application in future neuromorphic computing.
原文 | English |
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頁(從 - 到) | 16909-16917 |
頁數 | 9 |
期刊 | Ceramics International |
卷 | 49 |
發行號 | 11 |
DOIs | |
出版狀態 | Published - 1 6月 2023 |