Wafer‐Scale 2D Hafnium Diselenide Based Memristor Crossbar Array for Energy‐Efficient Neural Network Hardware

Memristor crossbar with programmable conductance could overcome the energy consumption and speed limitations of neural networks when executing core computing tasks in image processing. However, the implementation of crossbar array (CBA) based on ultrathin 2D materials is hindered by challenges assoc...

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Veröffentlicht in:	Advanced materials (Weinheim) 2022-06, Vol.34 (25), p.e2103376-n/a
Hauptverfasser:	Li, Sifan, Pam, Mei‐Er, Li, Yesheng, Chen, Li, Chien, Yu‐Chieh, Fong, Xuanyao, Chi, Dongzhi, Ang, Kah‐Wee
Format:	Artikel
Sprache:	eng
Schlagworte:	2D hafnium diselenide Arrays Artificial neural networks Energy consumption Epitaxial growth Hafnium Hardware Image processing Materials science Memristors Microprocessors Molecular beam epitaxy multiply‐and‐accumulate operation neural network hardware Neural networks Power efficiency Switching Two dimensional materials van der Waals transfer
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