Honey-CNT based Resistive Switching Device for Neuromorphic Computing Applications

Modern computing applications increasingly rely on technologies in artificial intelligence, machine learning, and big data analytics. These applications often demand more powerful and energy-efficient hardware. Resistive switching random access memory (ReRAM) has emerged as a promising solution to satisfy both the storage and computing needs. In this paper, a natural organic honey film embedded with carbon nanotube (CNT) was fabricated into a resistive switching device, and the resistive switching behaviors were investigated. Endurance test results show the cycle-to-cycle variation of set and reset voltages. On/Off ratio in retention test was found to be in the order of ~10 ⁵ which proves its potential as a non-volatile memory device to support neuromorphic computing applications. This research opens up opportunities to execute big data and machine learning applications with modest energy consumption and minimal electronic waste.