A Ti/AlO_x/TaO_x/Pt Analog Synapse for Memristive Neural Network

Abstract

Electronic synapse with precise analog weight tuning ability and long-term retention is the vital device foundation of memristor-based neuromorphic computing systems. In this letter, we propose a Ti/AlO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>x</i></sub> /TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>x</i></sub> /Pt memristor as an analog synapse for memristive neural network applications. The device shows high uniformity, excellent analog switching behaviors (up to 200 resistance states under triangle pulses) and excellent long-term retention of each state (up to 30 000 s). Furthermore, the precise modulation of the device resistance state (with 1.7% tolerance) can also be achieved by a finer writing program within 50 cycles.