Amorphous InGaZnO (a-IGZO) Synaptic Transistor for Neuromorphic Computing
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Abstract
Brain-inspired neuromorphic computing emulates the biological functions of the human brain to achieve highly intensive data processing with low power consumption. In particular, spiking neural networks (SNNs) that consist of artificial synapses can process spatiotemporal information while enabling energy-efficient neuromorphic computations. Artificial synapses are a key element of sophisticated neuromorphic hardware, so a significant amount of research has been conducted to develop various materials and device structures. Of these, we assess amorphous InGaZnO (IGZO)-based synaptic transistors that have exhibited properties suitable for emerging hybrid optoelectronic neuromorphic systems. Here, we describe the fundamental principles of neuromorphic computations, neuron circuits, and synaptic devices according to recent studies. IGZO-based transistors are discussed, from their material properties to various device physics for electronic- and/or photonic-neuromorphic systems with extraordinary biological emulations.