Oxygen Vacancies Controlled Highly Stable Bilayer Analog Synapse Used for Neuromorphic Computing Systems

This study investigated an oxygen-vacancy-controlled bilayer TiN/TaOy/ TaOx/Pt memristive synaptic device for neuromorphic computing. Multilevel character-istics of the synaptic device were observed with RESET voltage varying between -1.4 and -1.9 V. The device shows highly stable reparative 200 potentiation and depression cycles. The high nonlinearity results of alpha p = 0.83 for potentiation and alpha d = -2.03 for depression were observed with the device's potentiation and depression functions. The device also exhibits a highly stable DC endurance of at least 1000 cycles, an AC pulse endurance of 1 M, and a steady retention of 104 s at 100 & DEG;C without any degradation. Furthermore, a Hopfield neural network (HNN) is trained to recognize a 28 x 28 pixels image as an input, representing 784 synapses. In 23 epochs, the HNN successfully identified the input image with training accuracy over 92%. This bilayer memristive device can be highly suitable for neuromorphic devices in the development of neuromorphic-computing field.