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

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.

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Publication Details

Journal
Applied Physics Letters
Published
2025-10-23
DOI
https://doi.org/10.1063/5.0266816
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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article

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

Daiki Nishioka, Takashi Tsuchiya, Kazuya Terabe, Yoshitaka Shingaya
Applied Physics Letters
Neural Networks and Reservoir Computing
article

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

Daiki Nishioka, Takashi Tsuchiya, Kazuya Terabe, Yoshitaka Shingaya
article en

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.

Applied Physics LettersVol. 127(17)
National Institute for Materials Science (JP)
Openalex Percentile: Top 83%
Neural Networks and Reservoir Computing
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