Two‐Dimensional MXene Synapse for Brain‐Inspired Neuromorphic Computing

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 surfa...

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Veröffentlicht in:Small (Weinheim an der Bergstrasse, Germany) Germany), 2021-08, Vol.17 (34), p.e2102595-n/a
Hauptverfasser: Ju, Jae Hyeok, Seo, Seunghwan, Baek, Sungpyo, Lee, Dongyoung, Lee, Seojoo, Lee, Taeran, Kim, Byeongchan, Lee, Je‐Jun, Koo, Jiwan, Choo, Hyeongseok, Lee, Sungjoo, Park, Jin‐Hong
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Sprache:eng
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Zusammenfassung: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. An atomic‐switch‐type artificial synapse fabricated on Ti3C2TX MXene nanosheets with lots of surface functional groups successfully mimics the dynamics of biological synapse. The synaptic dynamics originate from the gradual formation and annihilation of the conductive metallic filaments on the MXene surface with distributed functional groups. Subsequently, its feasibility for an HW‐NN with learning ability is demonstrated using a convolutional neural network composed MXene synapse devices.
ISSN:1613-6810
1613-6829
DOI:10.1002/smll.202102595