Moiré synaptic transistor with room-temperature neuromorphic functionality

Xiaodong Yan, Zhiren Zheng, Vinod K. Sangwan, Justin H. Qian, Xueqiao Wang, Stephanie E. Liu, Kenji Watanabe, Takashi Taniguchi, Su-Yang Xu, Pablo Jarillo-Herrero (), Qiong Ma () and Mark C. Hersam ()
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Xiaodong Yan: Northwestern University
Zhiren Zheng: Massachusetts Institute of Technology
Vinod K. Sangwan: Northwestern University
Justin H. Qian: Northwestern University
Xueqiao Wang: Massachusetts Institute of Technology
Stephanie E. Liu: Northwestern University
Kenji Watanabe: National Institute for Materials Science
Takashi Taniguchi: National Institute for Materials Science
Su-Yang Xu: Harvard University
Pablo Jarillo-Herrero: Massachusetts Institute of Technology
Qiong Ma: Boston College
Mark C. Hersam: Northwestern University

Nature, 2023, vol. 624, issue 7992, 551-556

Abstract: Abstract Moiré quantum materials host exotic electronic phenomena through enhanced internal Coulomb interactions in twisted two-dimensional heterostructures1–4. When combined with the exceptionally high electrostatic control in atomically thin materials5–8, moiré heterostructures have the potential to enable next-generation electronic devices with unprecedented functionality. However, despite extensive exploration, moiré electronic phenomena have thus far been limited to impractically low cryogenic temperatures9–14, thus precluding real-world applications of moiré quantum materials. Here we report the experimental realization and room-temperature operation of a low-power (20 pW) moiré synaptic transistor based on an asymmetric bilayer graphene/hexagonal boron nitride moiré heterostructure. The asymmetric moiré potential gives rise to robust electronic ratchet states, which enable hysteretic, non-volatile injection of charge carriers that control the conductance of the device. The asymmetric gating in dual-gated moiré heterostructures realizes diverse biorealistic neuromorphic functionalities, such as reconfigurable synaptic responses, spatiotemporal-based tempotrons and Bienenstock–Cooper–Munro input-specific adaptation. In this manner, the moiré synaptic transistor enables efficient compute-in-memory designs and edge hardware accelerators for artificial intelligence and machine learning.

Date: 2023
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DOI: 10.1038/s41586-023-06791-1

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