Solution-processed inorganic δ-phase CsPbI3 electronic synapses with short- and long-term plasticity in a crossbar array structure

A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing

Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.

An Artificial Synapse Based on CsPbI3 thin Film

With the data explosion in the intelligent era; the traditional von Neumann computing system is facing great challenges of storage and computing speed. Compared to the neural computing system, the traditional computing system has higher consumption and slower speed. However; the feature size of the chip is limited due to the end of Moore’s Law. An artificial synapse based on halide perovskite CsPbI3 was fabricated to address these problems. The CsPbI3 thin film was obtained by a one-step spin-coating method, and the artificial synapse with the structure of Au/CsPbI3/ITO exhibited learning and memory behavior similar to biological neurons. In addition, the synaptic plasticity was proven, including short-term synaptic plasticity (STSP) and long-term synaptic plasticity (LTSP). We also discuss the possibility of forming long-term memory in the device through changing input signals.