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Robust biodegradable synapse with sub-biological energy and extended memory for intelligent reflexive system.

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Titel: Robust biodegradable synapse with sub-biological energy and extended memory for intelligent reflexive system.
Autoren: Chang, Yoojin, Na, Sangyun, Ro, Yun Goo, Park, Cheolhong, Jung, Seokhee, Park, Yong-Jin, Kwak, Min Sub, Kim, Jeeyoon, Oh, Hyeji, Kim, Jaejun, Ko, Hyunhyub
Quelle: Nature Communications; 11/27/2025, Vol. 16 Issue 1, p1-13, 13p
Schlagwörter: LONG-term memory, ENERGY consumption, SYNAPSES, ARTIFICIAL intelligence, ION migration & velocity, DURABILITY, BIOLOGICALLY inspired computing
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. Artificial synapses for wearable and implantable applications are limited in widespread use due to environmental instability, limited ion-trapping capabilities and high energy consumption. Here, the authors present a biodegradable multilayer artificial synapse achieving 0.85 fJ per synaptic event. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
Beschreibung
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. Artificial synapses for wearable and implantable applications are limited in widespread use due to environmental instability, limited ion-trapping capabilities and high energy consumption. Here, the authors present a biodegradable multilayer artificial synapse achieving 0.85 fJ per synaptic event. [ABSTRACT FROM AUTHOR]
ISSN:20411723
DOI:10.1038/s41467-025-66511-3