| The rapid development of the optoelectronic industry has led to a rapid increase in the number of sensor nodes based on optoelectronic technology.This trend is also the same in the field of ultraviolet detection,and will continue in the future.In the era of big data,large amounts of inputting raw and unstructured data from sensors to backend circuits will inevitably lead to analog-to-digital signal conversion and data transmission,which poses a heavy burden on transmission bandwidth and power consumption.Although the traditional von Neumann architecture plays an important role,there are also some limitations that need to be gradually addressed through the continuous development of new architectures and technologies.In contrast,if sensors with intrinsic computing capabilities can perform signal conversion and information processing in the same physical unit,it can significantly reduce the cost of data transmission and simplify the system structure.Due to the low background radiation on Earth,solar blind ultraviolet detection technology is widely used in military and civilian fields due to its unique advantages.Ga2O3 materials,which are directly suitable for solar-blind ultraviolet wavelengths,have great potential in intelligent applications and are expected to break through the architectural challenges faced by traditional ultraviolet detection.In this article,we discuss the uniqueness and wide application of solar blind ultraviolet detection to emphasize the importance and irreplaceable nature of Ga2O3 materials in this field.Then,based on the characteristics and research status of Ga2O3 materials,we analyzed the shortcomings of traditional detector research in the past,and formulated a research route.Finally,this paper discusses several intelligent application issues related to solarblind ultraviolet Ga2O3 materials,and proposes corresponding device solutions based on many international and domestic research concepts and ideas on in-sensor computing devices.The main research contents of this paper are as follows:(1)Almost all the solar-blind photodetectors based on the photoelectric effect face the problem of responsivity-speed(RS)dilemma,namely high responsivity induces a long decay time.In order to solve the dilemma in traditional detector structures,in this work,we break the RS dilemma of photodetector by using a tailored alternating gate modulation(AGM)scheme based on amorphous gallium oxide(a-GaOx)solar-blind photodetector(SBPD).Instead of traditional control of the photosensitive channel state by a constant gate bias,dynamic accumulation and depletion mode by an AGM scheme in one single detection cycle facilitate high responsivity and fast decay speed,respectively.As a result,the responsivity of the a-GaOx PD increases from 586.8 to 2115.1 A/W,and the decay time shrinks three orders of magnitude from 4.32 s to 2 ms.In addition,the RS dilemma situation in different spectral ranges and different materials has also been eliminated by this AGM scheme.Furthermore,the AGM scheme has been demonstrated to facilitate the detection imaging with higher contrast and frame rate.Also,we confirmed the feasibility of gate modulation to perform self-adaptation as artificial pupil.(2)In order to understand the deeper physical intrinsic characteristics of devices at a microscopic time scale,we fabricated a synaptic device by amorphous gallium oxide.Starting from the PPC effect,we designed and conducted various simulations of human neural function on our device.Through KPFM measurement,we preliminarily determined that the source of PPC effect is hole capture.And then,we implemented several bionic behaviors on the device,such as "PPF","LTM","learning" and"forgetting",indicating that the device can store the UV visual information like a optical synapse.Inspired by the classical "Pavlov dog" conditioning,an efficient method to enhance UV stimulation has been realized,as the "bell-feed-bell" process.In general,the gallium a-GaOx based synapse has broadened the path of deep UV sensors.The comprehensive performance of this synaptic device exhibited great potential in the simulation of human visual system,and has good application prospects in bionic or neuromorphic devices.(3)We proposed a fully-hardware DUV in-sensor RC system composed of a photosynapse reservoir layer and a memristor readout layer for latent fingerprint recognition.It is found that the oxygen-vacancy-related hole traps dominate the PPC effect and induce the nonlinear neuromorphic features of the a-GaOx DUV photo-synapse for insenor RC.As a result,the inputs of the reservoir can be nonlinearly mapped to dimensionality-reduced outputs,which constitute the feature space.Acting as the readout network,memristor device array with analog conductivity takes charge of the training of reservoir outputs and parallel in-memory computing.Based on such a hardware system,the high recognition accuracy of DUV fingerprint images nearly matches the simulation results when adopting a dual-feature strategy.The system achieves 100%recognition accuracy after 100 training epochs and maintains 90%accuracy even under 15%background noise level consistent with the anti-noise characteristics of DUV light.This fully-hardware DUV in-sensor RC system provides a prototype for efficient identification and security applications. |
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