Journal
SMALL
Volume 17, Issue 34, Pages -Publisher
WILEY-V C H VERLAG GMBH
DOI: 10.1002/smll.202102595
Keywords
artificial synapse; brain-inspired neuromorphic computing; convolutional neural network; two-dimensional MXene
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Funding
- Basic Science Research Program and Basic Research Lab Program through National Research Foundation of Korea (NRF) - Korea government (MSIP) [2018R1D1A1A09081931, 2020R1A4A2002806, 2019M3F3A1A01074451]
- Samsung Electronics Co., Ltd [IO201210-07994-01]
- Institute for Information & Communication Technology Planning & Evaluation (IITP), Republic of Korea [2019M3F3A1A01074451] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [4199990114441] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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The study found that synaptic dynamics originated from the gradual formation and annihilation of conductive metallic filaments on the MXene surface with distributed functional groups. Through training and inference tasks using a convolutional neural network for the Canadian Institute For Advanced Research-10 dataset, the applicability of the artificial MXene synapse to hardware neural networks was demonstrated.
MXenes, an emerging class of two-dimensional (2D) transition metal carbides and nitrides, have attracted wide attention because of their fascinating properties required in functional electronics. Here, an atomic-switch-type artificial synapse fabricated on Ti3C2Tx MXene nanosheets with lots of surface functional groups, which successfully mimics the dynamics of biological synapses, is reported. Through in-depth analysis by X-ray photoelectron spectroscopy, transmission electron microscopy, and energy dispersive X-ray spectroscopy, it is found that the synaptic dynamics originated from the gradual formation and annihilation of the conductive metallic filaments on the MXene surface with distributed functional groups. Subsequently, via training and inference tasks using a convolutional neural network for the Canadian-Institute-For-Advanced-Research-10 dataset, the applicability of the artificial MXene synapse to hardware neural networks is demonstrated.
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