TY - JOUR
T1 - Artificial Synapse Emulated by Charge Trapping-Based Resistive Switching Device
AU - Zhang, Shi-Rui
AU - Zhou, Li
AU - Mao, Jing-Yu
AU - Ren, Yi
AU - Yang, Jia-Qin
AU - Yang, Guang-Hu
AU - Zhu, Xin
AU - Han, Su-Ting
AU - Vellaisamy, A. L. Roy
AU - Zhou, Ye
PY - 2019/2
Y1 - 2019/2
N2 - The traditional Von Neumann architecture-based computers are considered to be inadequate in the coming artificial intelligence era due to increasing computation complexity and rising power consumption. Neuromorphic computing may be the key role to emulate the human brain functions and eliminate the Von Neumann bottleneck. As a basic unit in the nervous system, a synapse is responsible for transmitting information between neurons. Resistive random access memory (RRAM) is able to imitate the synaptic functions because of its tunable resistive switching behavior. Here, an artificial synapse based on solution processed polyvinylpyrrolidone (PVPy)–Au nanoparticle (NP) hybrid is fabricated, various synaptic functions including paired-pulse facilitation (PPF), posttetanic potentiation (PTP), transformation from short-term plasticity (STP) to long-term plasticity (LTP) and learning-forgetting-relearning process are emulated, making the polymer–metal NPs hybrid system valuable candidates for the design of novel artificial neural architectures.
AB - The traditional Von Neumann architecture-based computers are considered to be inadequate in the coming artificial intelligence era due to increasing computation complexity and rising power consumption. Neuromorphic computing may be the key role to emulate the human brain functions and eliminate the Von Neumann bottleneck. As a basic unit in the nervous system, a synapse is responsible for transmitting information between neurons. Resistive random access memory (RRAM) is able to imitate the synaptic functions because of its tunable resistive switching behavior. Here, an artificial synapse based on solution processed polyvinylpyrrolidone (PVPy)–Au nanoparticle (NP) hybrid is fabricated, various synaptic functions including paired-pulse facilitation (PPF), posttetanic potentiation (PTP), transformation from short-term plasticity (STP) to long-term plasticity (LTP) and learning-forgetting-relearning process are emulated, making the polymer–metal NPs hybrid system valuable candidates for the design of novel artificial neural architectures.
KW - artificial synapse
KW - charge trapping
KW - hybrid materials
KW - resistive random access memory
KW - solution process
UR - http://www.scopus.com/inward/record.url?scp=85054568638&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85054568638&origin=recordpage
U2 - 10.1002/admt.201800342
DO - 10.1002/admt.201800342
M3 - RGC 21 - Publication in refereed journal
SN - 2365-709X
VL - 4
JO - Advanced Materials Technologies
JF - Advanced Materials Technologies
IS - 2
M1 - 1800342
ER -