TY - JOUR
T1 - Very-large-scale mimetic optogenetic synapses for physical reservoir computing
AU - Han, Xinyi
AU - Qi, Zhiying
AU - Kundrat, Vojtech
AU - Li, Huanjing
AU - Li, Zhonggui
AU - Guo, Xiaoyu
AU - Mao, Pengcheng
AU - Zheng, Weiguo
AU - Hou, Shuai
AU - Liu, Ruibin
AU - Wu, Hanchun
AU - Wang, Panding
AU - Zak, Alla
AU - Liu, Weifan
AU - Tenne, Reshef
AU - Guo, Yao
N1 - Publisher Copyright:
© The Author(s) 2026.
PY - 2026/12
Y1 - 2026/12
N2 - The scaling law of deep learning, which governs the relationship between model size and performance, has led to critical concerns regarding efficiency and sustainability. To address these challenges, this study presents a computational approach using self-organized submillimeter-long tungsten disulfide nanotube cluster as a 3D very-large-scale physical reservoir. The reservoir, with its 0D van der Waals interfaces on the order of 108, or 1.0×1010 mm-3, matches the synaptic quantity and density of the fruit fly’s brain. The reservoir demonstrates the capability to perform a wide range of tasks from monomodal challenges to multimodal endeavors such as speech-to-image and medical image generation. The photosensitive mimetic synaptic connections in the very large scale reservoir emulate the optogenetic modulation of neuron circuits in in-vivo biological systems. By integrating the principles of the scaling law, multimodal task capabilities, and mimetic optogenetic mechanisms, this research paves a path toward advanced computing architectures tailored for next-generation energy-efficient artificial intelligence.
AB - The scaling law of deep learning, which governs the relationship between model size and performance, has led to critical concerns regarding efficiency and sustainability. To address these challenges, this study presents a computational approach using self-organized submillimeter-long tungsten disulfide nanotube cluster as a 3D very-large-scale physical reservoir. The reservoir, with its 0D van der Waals interfaces on the order of 108, or 1.0×1010 mm-3, matches the synaptic quantity and density of the fruit fly’s brain. The reservoir demonstrates the capability to perform a wide range of tasks from monomodal challenges to multimodal endeavors such as speech-to-image and medical image generation. The photosensitive mimetic synaptic connections in the very large scale reservoir emulate the optogenetic modulation of neuron circuits in in-vivo biological systems. By integrating the principles of the scaling law, multimodal task capabilities, and mimetic optogenetic mechanisms, this research paves a path toward advanced computing architectures tailored for next-generation energy-efficient artificial intelligence.
UR - https://www.scopus.com/pages/publications/105029842307
U2 - 10.1038/s41467-025-68229-8
DO - 10.1038/s41467-025-68229-8
M3 - Article
C2 - 41519787
AN - SCOPUS:105029842307
SN - 2041-1723
VL - 17
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 1514
ER -