Flexible3Dmemristor array for binary storage and multi-states neuromorphic computing applications

The demand of flexible neuromorphic computing electronics is increasing with the rapid development of wearable artificial intelligent devices. The flexible resistive random-access memory (RRAM) is one excellent candidate of high-density storage devices. However, due to the limitations of fabrication process, materials system and device structure, it is difficult to prepare flexible 3D high-density network for neuromorphic computing. In this paper, a 3D flexible memristors network is developed via low-temperature atomic layer deposition (ALD) at 130 degrees C, with potential of extending to various flexible electronics. The typical bipolar switching characteristics are verified in RRAM units of 3D network, including first, second and third layers. Besides binary storage, the multibit storage in single unit is demonstrated and the storage density is further increased. As a connection link between binary storage and brain-inspired neuromorphic computing, the multibit storage capability paves the way for the tunable synaptic plasticity, for example, long-term potentiation/depression (LTP/LTD). The 3D memristors network successfully mimicked the typical neuromorphic functionality and realized ultra-multi conductance states modulation under 600 spikes. The robust mechanical flexibility is further demonstrated via LTP/LTD emulation under bending states (radius = 10 mm). The 3D flexible memristors network shows significant potential of applications in high-performance, high-density and reliable wearable neuromorphic computing system.

Automated summary

This paper explores a 3D flexible memristors network fabricated via low-temperature atomic layer deposition, demonstrating its potential for high-density storage and neuromorphic computing. The network exhibits typical bipolar switching characteristics and multibit storage capability, enhancing storage density. The study indicates the significant potential of the 3D flexible memristors network in high-performance, high-density, and reliable wearable neuromorphic computing systems.