TY - JOUR
T1 - Two-Dimensional Zeolitic Imidazolate Framework Based Optoelectronic Synaptic Transistor
AU - Jia, Ziqi
AU - Zhong, Wenmin
AU - Zhou, Kui
AU - Zeng, Wei
AU - Li, Yan
AU - Feng, Zihao
AU - Xue, Haozhe
AU - Zhao, Pengfei
AU - Chen, Xue
AU - Wang, Hongxiang
AU - Cai, Xingke
AU - Xue, Shuangmei
AU - Zhai, Yongbiao
AU - Lv, Ziyu
AU - Yan, Yan
AU - Zhang, Meng
AU - Yang, Xueqing
AU - Ding, Guanglong
AU - Han, Su Ting
AU - Kuo, Chi Ching
AU - Zhou, Ye
N1 - Publisher Copyright:
© 2025 American Chemical Society.
PY - 2025/3/17
Y1 - 2025/3/17
N2 - Neuromorphic computing systems that integrate memory and computation offer a solution to the limitations of traditional von Neumann architectures. Optoelectronic synaptic transistors, responding to both optical and electrical signals, enable multifunctional operation with low power consumption. However, challenges such as short data retention and low processing efficiency remain. This study presents an optoelectronic synaptic transistor utilizing two-dimensional (2D) MoS2, 2D zeolitic imidazolate framework (ZIF) Zn2(bim)4, and gold (Au) nanoparticles (NPs) as semiconductor, tunneling layer, and floating gate materials, respectively. By adjusting the tunneling layer thickness, the charge-blocking capacity of Zn2(bim)4 is modulated, improving long-term data retention. The optoelectronic properties of MoS2 and the charge-trapping ability of Au NPs enable the transistor to mimic synaptic behaviors such as postsynaptic current (PSC), long-term potentiation (LTP), and transition from short-term to long-term memory (STM-LTM). This device can also be integrated into an artificial neural network (ANN) for smart healthcare applications, achieving 88.1% accuracy in electrocardiogram classification through optoelectronic dual-mode stimulation.
AB - Neuromorphic computing systems that integrate memory and computation offer a solution to the limitations of traditional von Neumann architectures. Optoelectronic synaptic transistors, responding to both optical and electrical signals, enable multifunctional operation with low power consumption. However, challenges such as short data retention and low processing efficiency remain. This study presents an optoelectronic synaptic transistor utilizing two-dimensional (2D) MoS2, 2D zeolitic imidazolate framework (ZIF) Zn2(bim)4, and gold (Au) nanoparticles (NPs) as semiconductor, tunneling layer, and floating gate materials, respectively. By adjusting the tunneling layer thickness, the charge-blocking capacity of Zn2(bim)4 is modulated, improving long-term data retention. The optoelectronic properties of MoS2 and the charge-trapping ability of Au NPs enable the transistor to mimic synaptic behaviors such as postsynaptic current (PSC), long-term potentiation (LTP), and transition from short-term to long-term memory (STM-LTM). This device can also be integrated into an artificial neural network (ANN) for smart healthcare applications, achieving 88.1% accuracy in electrocardiogram classification through optoelectronic dual-mode stimulation.
UR - http://www.scopus.com/inward/record.url?scp=105000296041&partnerID=8YFLogxK
U2 - 10.1021/acs.jpclett.5c00009
DO - 10.1021/acs.jpclett.5c00009
M3 - Journal article
C2 - 40094623
AN - SCOPUS:105000296041
SN - 1948-7185
VL - 16
SP - 3012
EP - 3021
JO - Journal of Physical Chemistry Letters
JF - Journal of Physical Chemistry Letters
IS - 12
ER -