Simulation of biological visual perception has gained considerable attention. In this paper, an optoelectrical In2O3 transistor array with a negative photoconductivity behavior is designed using a side-gate structure and a screen-printed ion-gel as the gate insulator. This paper is the first to observe a negative photoconductivity in electrolyte-gated oxide devices. Furthermore, an artificial visual perception system capable of self-adapting to environmental lightness is mimicked using the proposed device array. The transistor device array shows a self-adaptive behavior of light under different levels of light intensity, successfully demonstrating the visual adaption with an adjustable threshold range to the external environment. This study provides a new way to create an environmentally adaptive artificial visual perception system and has far-reaching significance for the future of neuromorphic electronics.

Optically readable organic synaptic devices have great potential in both artificial intelligence and photonic neuromorphic computing. Herein, a novel optically readable organic electrochemical synaptic transistor (OR-OEST) strategy is first proposed. The electrochemical doping mechanism of the device was systematically investigated, and the basic biological synaptic behaviors that can be read by optical means are successfully achieved. Furthermore, the flexible OR-OESTs are capable of electrically switching the transparency of semiconductor channel materials in a nonvolatile manner, and thus the multilevel memory can be achieved through optical readout. Finally, the OR-OESTs are developed for the preprocessing of photonic images, such as contrast enhancement and denoising, and feeding the processed images into an artificial neural network, achieving a recognition rate of over 90%. Overall, this work provides a new strategy for the implementation of photonic neuromorphic systems.

The emergence of light-tunable synaptic transistors provides opportunities to break through the von Neumann bottleneck and enable neuromorphic computing. Herein, a multifunctional synaptic transistor is constructed by using 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT) and indium gallium arsenide (InGaAs) nanowires (NWs) hybrid heterojunction thin film as the active layer. Under illumination, the Type-I C8-BTBT/InGaAs NWs heterojunction would make the dissociated photogenerated excitons more difficult to recombine. The persistent photoconductivity caused by charge trapping can then be used to mimic photosynaptic behaviors, including excitatory postsynaptic current, long/short-term memory and Pavlovian learning. Furthermore, a high classification accuracy of 89.72% can be achieved through the single-layer-perceptron hardware-based neural network built from C8-BTBT/InGaAs NWs synaptic transistors. Thus, this work could provide new insights into the fabrication of high-performance optoelectronic synaptic devices.

High-k dielectrics are frequently used for organic thin-film transistors (OTFTs), which facilitate the reduction of the device's operating voltage and enhance the total electrical performance. Along these lines, in this work, the fabrication of high-k AlO x dielectrics with high capacitance and low leakage current is proposed. On top of that, low-voltage flexible OTFTs with a solution-processed 2,7-dioctyl benzothieno[3,2-b] benzothiophene channel layer were demonstrated. The AlO x dielectric film was deposited by employing the reactive magnetron sputtering technique from a metal Al target by using a gas mixture of Ar and O2 at room temperature. At the same time, the surface morphology of the semiconductor film was optimized by controlling the solid solubility of polystyrene and polymethyl methacrylate in the semiconductor solution, which is important for improving the device performance. In this way, the prepared flexible OTFTs showed a low operating voltage of 3 V, a high switch ratio of 4.2 × 107, a high mobility is 2.39 cm2/V s, and a steep subthreshold swing close to the theoretical limit of 68 mV/decade. It is, thus, expected that this method will be applicable to the development of high-performance OTFTs.

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