Enhanced computing performance of MoS2-based Raman-ion-gating reservoir achieved by combining reservoir states from current response and resonant Raman scattering

Abstract

Reservoir computing (RC) is promising for achieving low power consumption neuromorphic devices. In this study, we developed an all-solid-state electric double layer transistor using multilayer MoS2 to realize high-performance physical RC. We have demonstrated the high performance of a MoS2-based Raman-ion-gating reservoir, in which gate voltage-dependent resonant Raman scattering spectra of MoS2 were used as computational resources in addition to drain and gate current responses. Our device achieved good performance, such as >97% accuracy in various nonlinear waveform transformations and 97.8% accuracy in solving a second-order nonlinear dynamic equation. Information processing capacity was evaluated to elucidate the origin of the high performance of our system.