Enhanced Reliability and Self‐Compliance of Synaptic Arrays for Multibit Encoded Neuromorphic Systems
Year: 2024
Type: article
Abstract: Utilizing memristors to increase the density of crossbar arrays requires reducing dependency on transistors. This paper presents an approach where the current limiting function is integrated within the memristor by inducing an AlO x /TaO x layer, thereby limiting overshoot current during filament formation. The reaction between TaO x and Al can be accelerated through annealing, which optimizes the on/off ratio and reduces device‐to‐device variation. Additionally, AlN is inserted to inhibit the movement of oxygen ions to the bottom electrode, improving conductive filament reoxidation. Furthermore, biological synaptic properties are examined using electrical pulse schemes, revealing multibit characteristics of >5‐bit. After the structure optimization, 24 × 24 crossbar arrays are fabricated, allowing 100% of cells to achieve self‐compliance filament formation without hard breakdown. Moreover, the crossbar array demonstrates an on/off ratio of over 4 × 10 2 . Additionally, a multibit‐encoded neuromorphic system is proposed based on the device's multibit capability. The number of synapses can be significantly reduced by grouping input data into a single memristor device. When comparing classification accuracies, 97.14% and 95.54% are observed without and with encoding. The improvements in device structure and encoding method presented in this study enable highly integrated crossbar arrays and efficient neuromorphic systems.
Source: Advanced Electronic Materials
Institutions: Korea University, Dongguk University, Seoul National University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,100
OpenAlex ID: W4402257271