(Invited) Neuromorphic Application of Oxide Semiconductors

Artificial intelligences are promising as key technologies in future societies, but the conventional ones are complicated software executed on high-specked hardware. Therefore, we are investigating "brain-type integrated system", namely, neural network built only by hardware, which can be compact, low power, robust, and integrated on everything. In this study, we have succeeded in hardware simplification and are trying to utilize oxide semiconductors for the neuromorphic application because they can be fabricated using low cost fabrication such as sputtering and printing. We made a sandwiched structure of Ti/a-IGZO/Ti and found that the conductance decreases as the time goes by, which is available to modified Hebbian rule, a learning rule we proposed for our network. We modeled the conductance degradation of the a-IGZO thin film, developed a simulator, and obtained the learning results. We would like to develop brain-type integrated system with three-dimensional structure utilizing the oxide semiconductors in future.