Ferroelectric devices

The next-generation ferroelectric memory has gained attention so far for its potential to operate at higher speed with lower power consumption compared to the conventional flash memory. But its commercialization has been deterred due to the high processing temperature, difficulty in scaling, and non-compatibility with the conventional semiconductor processes. Our lab presented unique integration strategies to overcome these issues by introducing the hafnia-based ferroelectrics and oxide semiconductors. The new material and structure ensured low power consumption and high speed, and achieved high stability by using oxide semiconductors as channel material to lower the process temperature and suppress the formation of the unwanted interface layer. As a result, the fabricated device could operate at a voltage four times lower than that of the conventional flash memory at a speed several hundred times faster and remain stable even when repeatedly used more than 100 million times. In particular, a ferroelectric material and an oxide semiconductor were stacked by an atomic layer deposition to secure a processing technology suitable for manufacturing 3D devices. This study suggested that ALD-based ferroelectric thin film transistors have the potential in future high-density 3D memory applications.

Neuromorphic computing is a promising alternative to conventional computing systems as it could enable parallel computation and adaptive learning process. However, the development of energy efficient neuromorphic hardware systems has been hindered by the limited performance of analog synaptic devices. Here, we demonstrate the analog conductance modulation behavior in the ferroelectric thin-film transistors (FeTFT) that have the nanoscale ferroelectric material and oxide semiconductors. Accurate control of polarization changes in the nanoscale ferroelectric layer induces conductance modulation to demonstrate linear potentiation and depression characteristics of FeTFTs. Our devices show potentiation and depression properties, including high linearity, multiple states, and small cycle-to-cycle/device-to-device variations. In simulations with measured properties, a neuromorphic system with FeTFT achieves 91.1% recognition accuracy of handwritten digits. This work may provide a way to realize the neuromorphic hardware systems that use FeTFTs as the synaptic devices.

A number of synapse devices have been intensively studied for the neuromorphic system which is the next‐generation energy‐efficient computing method. Among these various types of synapse devices, photonic synapse devices recently attracted significant attention. In particular, the photonic synapse devices using persistent photoconductivity (PPC) phenomena in oxide semiconductors are receiving much attention due to the similarity between relaxation characteristics of PPC phenomena and Ca2+ dynamics of biological synapses. However, these devices have limitations in its controllability of the relaxation characteristics of PPC behaviors. To utilize the oxide semiconductor as photonic synapse devices, relaxation behavior needs to be accurately controlled. In this study, a photonic synapse device with controlled relaxation characteristics by using an oxide semiconductor and a ferroelectric layer is demonstrated. This device exploits the PPC characteristics to demonstrate synaptic functions including short‐term plasticity, paired‐pulse facilitation (PPF), and long‐term plasticity (LTP). The relaxation properties are controlled by the polarization of the ferroelectric layer, and this polarization is used to control the amount by which the conductance levels increase during PPF operation and to enhance LTP characteristics. This study provides an important step toward the development of photonic synapses with tunable synaptic functions.