Interfacial Electronic Charge Trapping and Photonic Carrier Excitation Coupling in Solution-Processed Zinc–Tin Oxide Thin-Film Transistors Applied for Logic Gate Design and Quantized Neural Network

Components needed in Artificial Intelligence with a higher information capacity are critically needed and have garnered significant attention at the forefront of information technology. This study utilizes solution-processed zinc–tin oxide (ZTO) thin-film phototransistors and modulates the values of V_G, which allows for the regulation of electron trapping/detrapping at the ZTO/SiO₂ interface. By coupling the excited photonic carrier and electronic trapping, logic gates such as “AND,” “OR,” “NAND,” and “NOR” can be achieved. With the exponential growth in data generation, efficient processing and storage solutions are imperative. However, extensive data transfer between computing units and storage limits the level of artificial neural networks (ANNs). Consequently, quantized neural networks (QNNs) have gained interest for their reduced computational resource requirements and lower consumption. In this context, we introduce an optimized ternary logic circuit based on ZTO devices. By utilizing optical modulation to adjust the turn-on voltage of the single device, we demonstrate the achievement of ternary current states, thereby providing three distinct discrete states. This configuration can be extended to QNN computing, demonstrating multilevel quantized current values for in-memory computation. We achieved a handwriting digit recognition rate of 91.6%, thereby demonstrating reliable QNN hardware performance. This robust QNN performance indicates that the metal oxide phototransistor shows significant potential for future ternary computing systems.