Open AccessProgressive and Stable Synaptic Plasticity with Femtojoule Energy Consumption by the Interface Engineering of a Metal/Ferroelectric/Semiconductor
Author(s) -
Kim Sohwi,
Yoon Chansoo,
Oh Gwangtaek,
Lee Young Woong,
Shin Minjeong,
Kee Eun Hee,
Park Bae Ho,
Lee Ji Hye,
Park Sanghyun,
Kang Bo Soo,
Kim Young Heon
Publication year - 2022
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202201502
Subject(s) - neuromorphic engineering , materials science , ferroelectricity , optoelectronics , computer science , synaptic plasticity , heterojunction , synaptic weight , reading (process) , energy consumption , electrical engineering , artificial neural network , chemistry , artificial intelligence , engineering , biochemistry , receptor , dielectric , political science , law
In the era of “big data,” the cognitive system of the human brain is being mimicked through hardware implementation of highly accurate neuromorphic computing by progressive weight update in synaptic electronics. Low‐energy synaptic operation requires both low reading current and short operation time to be applicable to large‐scale neuromorphic computing systems. In this study, an energy‐efficient synaptic device is implemented comprising a Ni/Pb(Zr 0.52 Ti 0.48 )O 3 (PZT)/0.5 wt.% Nb‐doped SrTiO 3 (Nb:STO) heterojunction with a low reading current of 10 nA and short operation time of 20–100 ns. Ultralow femtojoule operation below 9 fJ at a synaptic event, which is comparable to the energy required for synaptic events in the human brain (10 fJ), is achieved by adjusting the Schottky barrier between the top electrode and ferroelectric film. Moreover, progressive domain switching in ferroelectric PZT successfully induces both low nonlinearity/asymmetry and good stability of the weight update. The synaptic device developed here can facilitate the development of large‐scale neuromorphic arrays for artificial neural networks with low energy consumption and high accuracy.