[9p-E311-1~21] CS.7 Code-sharing session of 6.1 & 15.4

3:45 PM - 4:00 PM JST(6:45 AM - 7:00 AM UTC)Presentation by Applicant for JSAP Young Scientists Presentation Award

[9p-E311-10] Physical Reservoir Computing Utilizing Resistive Switching in Ferroelectric AlScN

〇Koki Yasuoka¹, Yusuke Aoki¹, Yu Ukezeki¹, Takeshi Yosimura^1,2 (1.Osaka Metro Univ., 2.Toyohashi Univ. Tech)

Keywords:

ScAlN,Ferroelectric,Physical reservoir computing

Physical reservoir computing (PRC) is a framework that implements machine-learning functions in hardware by exploiting the nonlinear dynamics of a reservoir layer. In this work, we focused on the ferroelectric AlScN, which exhibits a domain-wall-density-dependent multilevel resistance change, and implemented PRC using an epitaxial AlScN thin film grown on a Si substrate. Short-term memory and nonlinearity were confirmed through STM and XOR tasks.