Metal Oxide Nano‐Interface Boosting the Deep Ultraviolet Adjustable Noise‐Filtering In‐Sensor Computing

Long‐afterglow light‐emitting devices (LALEDs), which combine the capabilities of sensing, memory, processing, and display integration, allow for the simultaneous implementation of optical and electrical in‐sensor computing. However, the inherently low conductivity of conventional deep‐ultraviolet (DUV) responsive materials hinders their use in the DUV‐responsive LALEDs (DUV‐LALEDs). Herein, we demonstrate that sol‐gel‐fractured indium‐magnesium oxide (InMgO) concurrently exhibits ideal nano‐interface for DUV photon absorption and semiconductor crystal for efficient charge transport via hopping, enabling to reach high mobility (0.6 cm 2 V −1 s −1 ), excellent memory dynamic range (70 dB), and responsivity (523.7 A/W). The InMgO‐based DUV‐LALEDs display an electrical and optical post‐synaptic output when irradiated with DUV light. Moreover, hardware‐level noise‐filtering processes to the pre‐synaptic weight are revealed in the DUV‐LALEDs, emerging as the inhibition of light emission due to the insufficient post‐synaptic charge injection from the channel layer. Consequently, an adjustable noise‐filtering in‐sensor computing is successfully achieved by modulating the channel length. By taking advantage of the DUV‐LALED multifunctional nature, fusion‐node reservoir computing networks are employed to accomplish multi‐dimensional recognition tasks, displaying a high recognition accuracy of 99%. These findings demonstrate that the joint materials and devices optimization is a powerful strategy for fabricating cost‐efficient DUV analytical chips.