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Ko, Hyunhyub
Functional Nanomaterials & Devices Lab.
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Robust biodegradable synapse with sub-biological energy and extended memory for intelligent reflexive system

Author(s)
Chang, YoojinNa, SangyunRo, Yun GooPark, CheolhongJung, SeokheePark, Yong-JinKwak, Min SubKim, JeeyoonOh, HyejiKim, JaejunKo, Hyunhyub
Issued Date
2025-11
DOI
10.1038/s41467-025-66511-3
URI
https://scholarworks.unist.ac.kr/handle/201301/91280
Citation
NATURE COMMUNICATIONS, v.16, no.1, pp.10610
Abstract
Biodegradable artificial synapses hold great promise for sustainable neuromorphic electronics, yet combining long-term memory, ultralow energy consumption, and mechanical robustness remains challenging. Here, we report a fully biodegradable multilayer artificial synapse (M-AS) composed of crosslinked chitosan-guar gum (CS-GG) ion-active layers (IALs) and a cellulose acetate (CA) ion-binding layer (IBL). This trilayer architecture enhances ion trapping via ion-dipole coupling (IDC) at the IAL-IBL interface, while hydrogen-bonded crosslinking within the CS-GG matrix enhances mechanical and environmental stability. Sodium chloride, embedded in the IALs, serves as a mobile ionic species analogous to biological neurotransmitters, enabling low-voltage ion migration. Upon electrical stimulation, ion migration and dipole alignment induce IDC, leading to partial ion retention and cascade-like postsynaptic current responses that support memory formation. The M-AS supports key synaptic functionalities-including paired-pulse facilitation, short-term and long-term plasticity, multilevel memory encoding, and bidirectional modulation-under sub-millivolt operation. It achieves the longest long-term memory time (5944 s) reported among biodegradable artificial synapses and an energy consumption (0.85 fJ/event) lower than that of biological synapses. Integration with a thermistor and robotic actuator enables a bioinspired reflexive system capable of adaptive, stimulus-dependent learning and reflex-like behaviors. These results demonstrate the potential of M-AS for low-power, intelligent human-machine interfaces.
Publisher
NATURE PORTFOLIO
ISSN
2041-1723
Keyword
PLASTICITY

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