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The device performance of indium zinc oxide (IZO) thin-film transistors (TFTs) is optimized through process optimizations. By jointly adjusting the annealing condition, the channel thickness and the sputtering atmosphere, the roughness and oxygen vacancies (Vos) are precisely regulated. The optimized IZO TFTs can achieve the highest field effect mobility of ~71.8 cm2/Vs with a threshold voltage of ~-0.6 V. Reliability of IZO TFTs under positive/negative bias stress is also examined. The interface quality and the Vo are two key factors influencing the device performance and reliability, confirmed by X-ray photoelectron spectroscopy and atomic force microscopy analysis.

With the advancements in Web of Things, Artificial Intelligence, and other emerging technologies, there is an increasing demand for artificial visual systems to perceive and learn about external environments. However, traditional sensing and computing systems are limited by the physical separation of sense, processing, and memory units that results in the challenges such as high energy consumption, large additional hardware costs, and long latency time. Integrating neuromorphic computing functions into the sensing unit is an effective way to overcome these challenges. Therefore, it is extremely important to design neuromorphic devices with sensing ability and the properties of low power consumption and high switching speed for exploring in-sensor computing devices and systems. In this review, we provide an elementary introduction to the structures and properties of two common optoelectronic materials, perovskites and transition metal dichalcogenides (TMDs). Subsequently, we discuss the fundamental concepts of neuromorphic devices, including device structures and working mechanisms. Furthermore, we summarize and extensively discuss the applications of perovskites and TMDs in in-sensor computing. Finally, we propose potential strategies to address challenges and offer a brief outlook on the application of optoelectronic materials in term of in-sensor computing.