Programmable nonlinear optical neuromorphic computing with bare 2D material MoS2

Lei Tong, Yali Bi, Yilun Wang, Kai Peng, Xinyu Huang, Wei Ju, Zhuiri Peng, Zheng Li, Langlang Xu, Runfeng Lin, Xiangxiang Yu, Wenhao Shi, Hui Yu, Huajun Sun, Kanhao Xue, Qiang He, Ming Tang, Jianbin Xu, Xinliang Zhang, Jinshui Miao, Deep Jariwala, Wei Bao (), Xiangshui Miao (), Ping Wang () and Lei Ye ()
Additional contact information
Lei Tong: Huazhong University of Science and Technology
Yali Bi: Huazhong University of Science and Technology
Yilun Wang: Huazhong University of Science and Technology
Kai Peng: Rensselaer Polytechnic Institute
Xinyu Huang: Huazhong University of Science and Technology
Wei Ju: Huazhong University of Science and Technology
Zhuiri Peng: Huazhong University of Science and Technology
Zheng Li: Huazhong University of Science and Technology
Langlang Xu: Huazhong University of Science and Technology
Runfeng Lin: Huazhong University of Science and Technology
Xiangxiang Yu: Huazhong University of Science and Technology
Wenhao Shi: Huazhong University of Science and Technology
Hui Yu: The Chinese University of Hong Kong
Huajun Sun: Huazhong University of Science and Technology
Kanhao Xue: Huazhong University of Science and Technology
Qiang He: Huazhong University of Science and Technology
Ming Tang: Huazhong University of Science and Technology
Jianbin Xu: The Chinese University of Hong Kong
Xinliang Zhang: Huazhong University of Science and Technology
Jinshui Miao: Shanghai Institute of Technical Physics Chinese Academy of Sciences
Deep Jariwala: University of Pennsylvania
Wei Bao: Rensselaer Polytechnic Institute
Xiangshui Miao: Huazhong University of Science and Technology
Ping Wang: Huazhong University of Science and Technology
Lei Ye: Huazhong University of Science and Technology

Nature Communications, 2024, vol. 15, issue 1, 1-9

Abstract: Abstract Nonlinear optical responses in two-dimensional (2D) materials can build free-space optical neuromorphic computing systems. Ensuring the high performance and the tunability of the system is essential to encode diverse functions. However, common strategies, including the integration of external electrode arrays or photonic structures with 2D materials, and barely patterned 2D materials, exhibit a contradiction between performance and tunability. Because the unique band dispersions of 2D materials can provide hidden paths to boost nonlinear responses independently, here we introduced a new free-space optical computing concept within a bare molybdenum disulfide array. This system can preserve high modulation performance with fast speed, low energy consumption, and high signal-to-noise ratio. Due to the freedom from the restrictions of fixed photonic structures, the tunability is also enhanced through the synergistic encodings of the 2D cells and the excitation pulses. The computing mechanism of transition from two-photon absorption to synergistic excited states absorption intrinsically improved the modulation capability of nonlinear optical responses, revealed from the relative transmittance modulated by a pump-probe-control strategy. Optical artificial neural network (ANN) and digital processing were demonstrated, revealing the feasibility of the free-space optical computing based on bare 2D materials toward neuromorphic applications.

Date: 2024
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DOI: 10.1038/s41467-024-54776-z

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