Oxide Phototransistor Array With Multiply-and-Accumulation Functions for In-Sensor Image Processing

Advanced in-sensor computing paradigm has gradually become a research hotspot in this IOT era of sensor data proliferation. However, most existing in-sensor computing devices are plagued by a complex structure, and the uniformity of the sensor array is difficult to ensure. Moreover, photoconductive devices are incapable of achieving on-chip current summation because the regulation of photoresponsivity usually leads to inconsistent dark current, thereby impeding the practical implementation of artificial neural networks (ANNs) on the sensor array. In this work, we developed a $3\times 3$ ultraviolet (UV) image sensor array based on solution-processed indium oxide (In2O3) phototransistors. The devices exhibit tunable responsivity and unified dark current under negative gate voltage (Vgs), enabling the direct execution of multiply-and-accumulation (MAC) operations. Consequently, two key applications of ANN were successfully demonstrated: image convolution and classification.