Proceedings of MATSUS Fall 2026 Conference (MATSUSFall26)
Publication date: 22nd July 2026
Nanostructure-based neurocomputing has emerged as a promising approach to develope fast and effieicent non-CMOS neuromorphic systems, owing to its low energy consumption, nonlinear response, fast electronic dynamics, and tunable charge transport [1]. The ability to engineer the structure and electronic properties of nanomaterials, including one-dimensional nanowires and core-shell heterostructures, provides opportunities to realize diverse neuronal and synaptic functions at the field-effect transistor (FET) device level. In this framework, we investigate InAs nanowires and InAs-GaSb core-shell nanostructures for reservoir computing [2] and oscillatory neural networks [3]. InAs nanowire-based FETs are explored as physical reservoirs, where the intrinsic nonlinear and dynamic response of the device maps input signals into a high-dimensional state space, allowing the computational task to be learned using only a simple output layer. We further investigate InAs nanowire FETs for implementing astrocyte-like synaptic modulation, with the aim of reproducing the role of glial-cell-mediated regulation of neuronal signaling. In addition, an InAs-GaSb core-shell FET exhibiting negative differential resistance is developed and investigated as a building block for oscillatory neural networks [4]. Together, these results demonstrate the potential of nanostructure-based FETs to provide compact and energy-efficient building blocks for neuromorphic computing and highlight the role of engineered nanoscale transport phenomena in implementing brain-inspired computational functions.
References:
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- D. Nishioka, A. Tateyama, H. Kitano, T. Nakanishi, K. Terabe, and T. Tsuchiya, Ion-Gating Reservoir Computing for Preprocessing-Free Speech Recognition from Throat Vibrations. Advanced Electronic Materials (2026): e00006.
- Y. S. Chung, S. Y. Yun, J. K. Han, Y. K. Choi; Oscillatory Neural Network with Tunable Frequency for Brain-Inspired Neuromorphic Computing. Nano Lett. (2025); 25 (17): 6950–6956.
- M. Rocci, F. Rossella, U. P. Gomes, V. Zannier, F. Rossi, D. Ercolani, L. Sorba, F. Beltram, S. Roddaro; Tunable Esaki Effect in Catalyst-Free InAs/GaSb Core–Shell Nanowires. Nano Lett. (2016); 16 (12): 7950–7955.
This work was supported by Japan Science and Technology Agency (JST) as part of Adopting Sustainable Partnerships for Innovative Research Ecosystem (ASPIRE), Grant Number JPMJAP2530.
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