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A bio-inspired electronic synapse using solution processable organic small molecule

delete2019-01-01
delete64
PRE
AI
J
Jingyu Mao
周
周丽 (Li Zhou)
Y
Yi Ren
J
Jia‐Qin Yang
C
Chih‐Li Chang
H
Heng‐Chuan Lin
H
Ho‐Hsiu Chou *
S
Shirui Zhang
Y
Ye Zhou
Han Suting 封面图
Han Suting (Su‐Ting Han) *
DOI:10.1039/c8tc05489ddelete
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摘要

摘要

En 中文
Mimicking bioLogicaL synapses with resistive random switching memory (RRAM) can Lay a concrete foundation for the future of artificiaL inteLLigence. RRAMs based on Low-cost and solution-processed organic materials provide a competitive approach. Here, we report an artificiaL synaptic device with a soLution- processed small moLecuLe (bis-4-(N-carbazoLypphenypphenyLphosphine oxide (BCPO) based RRAM. The BCPO-based RRAM exhibits reproducible resistive switching behavior, a Long retention time as weLL as good thermal tolerance with a sufficient on/off current ratio. In situ KeLvin probe force microscopy (KPFM), conductive atomic force microscopy (C-AFM) and density function theory (DFT) caLcuLations demonstrate that both the redox state and the trap-fiLLed space charge Limited current (SCLC) determine the resistive switching of a BCPO-based RRAM. Furthermore, the fabricated device was employed to emulate a bioLogicaL synapse in which several synaptic functions, including spike-rate dependent pLasticity (SRDP), a transition from short-term pLasticity (STP) to Long-term pLasticity (LTP) and spike-time-dependent pLasticity (STDP), were realized. To the best of our knowledge, this is the first successful demonstration of solution-processed small moLecuLes in artificiaL synaptic devices. The BCPO Layer is solution-processed at Low temperature which is compatible with a fLexibLe substrate and printable electronics. We believe this electronic synapse wiLL have a wide range of applications in future neuromorphic computing.
Keyword:
ARTIFICIAL SYNAPSE
RESISTIVE MEMORY
PLASTICITY
DEVICES
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期刊

Journal of Materials Chemistry C 封面图
Journal of Materials Chemistry C
IF:
5.1
论文数:
2.0W
被引数:
8.0W

机构

N
National Tsing Hua University
学者数:
1.6W
论文数: 1.4W
被引数: 1.7W
S
shenzhen university
学者数:
4.6W
论文数: 3.4W
被引数: 72
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