Reconfigurable Artificial Synapses Based on Ambipolar Environmentally Stable Tellurium for Neuromorphic Computing

Neuromorphic computing, a promising solution to the von Neumann bottleneck, is paving the way for next-generation computing and sensing systems. However, most studies of artificial synapses mimic only static plasticity, which is far from achieving the complex behaviors of the human brain. Here, we report a reliable neuromorphic computing system that integrates a top floating gate memory architecture and uses peculiar ambipolar tellurium (Te) as a channel material to fabricate reliable nonvolatile memory cells. The memory device clearly exhibits exceptional retention (∼10 4 s) and endurance (∼10 4 cycles) properties for ambipolar memory with on/off ratios of 10 8 (electrons) and 10 6 (holes). Furthermore, we have also achieved reconfigurable excitatory and inhibitory synapse functions based on a Te ambipolarity device and explored its application in neuromorphic computing for recognition of different levels of complexity images with high accuracy generally above 90%, demonstrating its potential in neuromorphic computing. These findings highlight the prospects of ambipolar Te memory for advancing the future in memory computing hardware.