Neuromorphic functions with a polyelectrolyte-confined fluidic memristor
Author(s) -
Tianyi Xiong,
Changwei Li,
Xiulan He,
Boyang Xie,
Jianwei Zong,
Yanan Jiang,
Wenjie Ma,
Fei Wu,
Junjie Fei,
Ping Yu,
Lanqun Mao
Publication year - 2023
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.adc9150
Subject(s) - neuromorphic engineering , fluidics , memristor , polyelectrolyte , nanotechnology , materials science , ion , computer science , optoelectronics , electronic engineering , artificial neural network , chemistry , engineering , electrical engineering , artificial intelligence , organic chemistry , composite material , polymer
Reproducing ion channel-based neural functions with artificial fluidic systems has long been an aspirational goal for both neuromorphic computing and biomedical applications. In this study, neuromorphic functions were successfully accomplished with a polyelectrolyte-confined fluidic memristor (PFM), in which confined polyelectrolyte-ion interactions contributed to hysteretic ion transport, resulting in ion memory effects. Various electric pulse patterns were emulated by PFM with ultralow energy consumption. The fluidic property of PFM enabled the mimicking of chemical-regulated electric pulses. More importantly, chemical-electric signal transduction was implemented with a single PFM. With its structural similarity to ion channels, PFM is versatile and easily interfaces with biological systems, paving a way to building neuromorphic devices with advanced functions by introducing rich chemical designs.
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