Forming-less flexible memristor crossbar array for neuromorphic computing applications produced using low-temperature atomic layer deposition

Abstract

The rapid development of wearable artificial intelligence devices based on memristor crossbar arrays has increased the demand for flexible electronics. However, fabricating crossbar arrays on flexible substrates faces inherent challenges, notably due to the complex fabrication process at low temperatures. Moreover, ensuring the stability and reliability of memristor device remains a crucial issue. To address these issues, this study introduced N-doped TaOx (N:TaOx) as a flexible memristor crossbar array fabricated via atomic layer deposition directly on a flexible substrate at an exceptionally low temperature (150 degrees C). The flexible PET/ITO/N:TaOx/TiN memristor device exhibited forming-less bipolar resistive switching properties with analog memory characteristics. This was accomplished by increasing the nitrogen doping concentration and effectively reducing oxygen-related defects in TaOx. The amorphous-phase flexible N:TaOx memristor demonstrated remarkable stability, enduring 500 switching cycles and retaining its state for 24 h during bending tests involving 104 bending cycles at 2.5 mm bending radius. Furthermore, a 6 x 6 flexible memristor crossbar array was fabricated successfully, with all 36 devices exhibiting well-defined memristor behavior and minimal variation attributed to the film's uniformity achieved through ALD process. Additionally, by programming the tunable conductance of each device in the array, characters of desired shapes can be formed and read. Regarding their synaptic behavior via long-term potentiation and depression, the proposed flexible memristor device showed an outstanding accuracy of 96.44 % in image recognition tasks under extreme bending conditions, employing the MNIST and Fashion-MNIST datasets. The N:TaOx memristor deposited at low temperatures thus exhibits significant potential for use in wearable neuromorphic hardware applications due to its high density, high performance, reliability, and precise image recognition.