Considering that the human brain uses ≈10 synapses to operate, the development of effective artificial synapses is essential to build brain-inspired computing systems. In biological synapses, the voltage-gated ion channels are very important for regulating the action-potential firing. Here, an electrolyte-gated transistor using WO with a unique tunnel structure, which can emulate the ionic modulation process of biological synapses, is proposed. The transistor successfully realizes synaptic functions of both short-term and long-term plasticity. Short-term plasticity is mimicked with the help of electrolyte ion dynamics under low electrical bias, whereas the long-term plasticity is realized using proton insertion in WO under high electrical bias. This is a new working approach to control the transition from short-term memory to long-term memory using different gate voltage amplitude for artificial synapses. Other essential synaptic behaviors, such as paired pulse facilitation, the depression and potentiation of synaptic weight, as well as spike-timing-dependent plasticity are also implemented in this artificial synapse. These results provide a new recipe for designing synaptic electrolyte-gated transistors through the electrostatic and electrochemical effects.

Neuromorphic computing consisting of artificial synapses and neural network algorithms provides a promising approach for overcoming the inherent limitations of current computing architecture. Developments in electronic devices that can accurately mimic the synaptic plasticity of biological synapses, have promoted the research boom of neuromorphic computing. It is reported that robust ferroelectric tunnel junctions can be employed to design high‐performance electronic synapses. These devices show an excellent memristor function with many reproducible states (≈200) through gradual ferroelectric domain switching. Both short‐ and long‐term plasticity can be emulated by finely tuning the applied pulse parameters in the electronic synapse. The analog conductance switching exhibits high linearity and symmetry with small switching variations. A simulated artificial neural network with supervised learning built from these synaptic devices exhibited high classification accuracy (96.4%) for the Mixed National Institute of Standards and Technology (MNIST) handwritten recognition data set.

Hardware implementation of artificial synaptic devices that emulate the functions of biological synapses is inspired by the biological neuromorphic system and has drawn considerable interest. Here, a three‐terminal ferrite synaptic device based on a topotactic phase transition between crystalline phases is presented. The electrolyte‐gating‐controlled topotactic phase transformation between brownmillerite SrFeO2.5 and perovskite SrFeO3−δ is confirmed from the examination of the crystal and electronic structure. A synaptic transistor with electrolyte‐gated ferrite films by harnessing gate‐controllable multilevel conduction states, which originate from many distinct oxygen‐deficient perovskite structures of SrFeOx induced by topotactic phase transformation, is successfully constructed. This three‐terminal artificial synapse can mimic important synaptic functions, such as synaptic plasticity and spike‐timing‐dependent plasticity. Simulations of a neural network consisting of ferrite synaptic transistors indicate that the system offers high classification accuracy. These results provide insight into the potential application of advanced topotactic phase transformation materials for designing artificial synapses with high performance.

Artificial synaptic devices are the essential hardware of neuromorphic computing systems, which can simultaneously perform signal processing and information storage between two neighboring artificial neurons. Emerging electrolyte-gated transistors have attracted much attention for efficient synaptic emulation by using an addition gate terminal. Here, an electrolyte-gated synaptic device based on the SrCoO x (SCO) films is proposed. It is demonstrated that the reversible modulation of SCO phase transforms the brownmillerite SrCoO 2.5 and perovskite SrCoO 3−δ , through controlling the insertion and extraction of oxygen ions with electrolyte gating. Nonvolatile multilevel conduction states can be realized in the SCO films following this route. The synaptic functions such as the long-term potentiation and depression of synaptic weight, spike-timing-dependent plasticity, as well as spiking logic operations in the device are successfully mimicked. These results provide an alternative avenue for future neuromorphic devices via electrolyte-gated transistors with oxygen ions.

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Ultraviolet photodetectors have attracted considerable interest for a variety of applications in health, industry, and science areas. Self-driven visible-blind photodetectors represent an appealing type of sensor, due to the reduced size and high flexibility. In this work, we employed BaTiO3 (BTO) single crystals with a bandgap of 3.2 eV for the realization of a self-driven ultraviolet detector, by utilizing the ferroelectric properties of BTO. We found that the sign of the photocurrent can be reversed by flipping the ferroelectric polarization, which makes the photodetector suitable for electrical manipulation. The photoelectric performance of this photodetector was systematically investigated in terms of rectification character, stability of short-circuit photocurrent, spectral response, and transient photoelectric response. Particularly, the self-driven photodetectors based on BTO showed an ultrafast response time about 200 ps. It is expected that the present work can provide a route for the design of photodetectors based on ferroelectric oxides.

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